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25=new Uint16Array('ᵁ<Õıʊҝջאٵ۞ޢߖࠏ੊ઑඡ๭༉༦჊ረዡᐕᒝᓃᓟᔥ\0\0\0\0\0\0ᕫᛍᦍᰒᷝ὾⁠↰⊍⏀⏻⑂⠤⤒ⴈ⹈⿎〖㊺㘹㞬㣾㨨㩱㫠㬮ࠀEMabcfglmnoprstu\\bfms�„‹•˜¦³¹ÈÏlig耻Æ䃆P耻&䀦cute耻Á䃁reve;䄂Āiyx}rc耻Â䃂;䐐r;쀀𝔄rave耻À䃀pha;䎑acr;䄀d;橓Āgp¡on;䄄f;쀀𝔸plyFunction;恡ing耻Å䃅Ācs¾Ãr;쀀𝒜ign;扔ilde耻Ã䃃ml耻Ä䃄ЀaceforsuåûþėĜĢħĪĀcrêòkslash;或Ŷöø;櫧ed;挆y;䐑ƀcrtąċĔause;戵noullis;愬a;䎒r;쀀𝔅pf;쀀𝔹eve;䋘còēmpeq;扎܀HOacdefhilorsuōőŖƀƞƢƵƷƺǜȕɳɸɾcy;䐧PY耻©䂩ƀcpyŝŢźute;䄆Ā;iŧŨ拒talDifferentialD;慅leys;愭ȀaeioƉƎƔƘron;䄌dil耻Ç䃇rc;䄈nint;戰ot;䄊ĀdnƧƭilla;䂸terDot;䂷òſi;䎧rcleȀDMPTLJNjǑǖot;抙inus;抖lus;投imes;抗oĀcsǢǸkwiseContourIntegral;戲eCurlyĀDQȃȏoubleQuote;思uote;怙ȀlnpuȞȨɇɕonĀ;eȥȦ户;橴ƀgitȯȶȺruent;扡nt;戯ourIntegral;戮ĀfrɌɎ;愂oduct;成nterClockwiseContourIntegral;戳oss;樯cr;쀀𝒞pĀ;Cʄʅ拓ap;才րDJSZacefiosʠʬʰʴʸˋ˗ˡ˦̳ҍĀ;oŹʥtrahd;椑cy;䐂cy;䐅cy;䐏ƀgrsʿ˄ˇger;怡r;憡hv;櫤Āayː˕ron;䄎;䐔lĀ;t˝˞戇a;䎔r;쀀𝔇Āaf˫̧ĀcmË°Ì¢riticalȀADGT̖̜̀̆cute;䂴oŴ̋̍;䋙bleAcute;䋝rave;䁠ilde;䋜ond;拄ferentialD;慆Ѱ̽\0\0\0͔͂\0Ѕf;쀀𝔻ƀ;DE͈͉͍䂨ot;惜qual;扐blèCDLRUVͣͲ΂ϏϢϸontourIntegraìȹoɴ͹\0\0ͻ»͉nArrow;懓Āeo·ΤftƀARTΐΖΡrrow;懐ightArrow;懔eåˊngĀLRΫτeftĀARγιrrow;柸ightArrow;柺ightArrow;柹ightĀATϘϞrrow;懒ee;抨pɁϩ\0\0ϯrrow;懑ownArrow;懕erticalBar;戥ǹABLRTaВЪаўѿͼrrowƀ;BUНОТ憓ar;椓pArrow;懵reve;䌑eft˒к\0ц\0ѐightVector;楐eeVector;楞ectorĀ;Bљњ憽ar;楖ightǔѧ\0ѱeeVector;楟ectorĀ;BѺѻ懁ar;楗eeĀ;A҆҇护rrow;憧ĀctҒҗr;쀀𝒟rok;䄐ࠀNTacdfglmopqstuxҽӀӄӋӞӢӧӮӵԡԯԶՒ՝ՠեG;䅊H耻Ð䃐cute耻É䃉ƀaiyӒӗӜron;䄚rc耻Ê䃊;䐭ot;䄖r;쀀𝔈rave耻È䃈ement;戈ĀapÓºÓ¾cr;䄒tyɓԆ\0\0ԒmallSquare;旻erySmallSquare;斫ĀgpÔ¦Ôªon;䄘f;쀀𝔼silon;䎕uĀaiԼՉlĀ;TՂՃ橵ilde;扂librium;懌Āci՗՚r;愰m;橳a;䎗ml耻Ë䃋ĀipÕªÕ¯sts;戃onentialE;慇ʀcfiosօֈ֍ֲ׌y;䐤r;쀀𝔉lledɓ֗\0\0Ö£mallSquare;旼erySmallSquare;斪Ͱֺ\0Ö¿\0\0ׄf;쀀𝔽All;戀riertrf;愱cò׋؀JTabcdfgorstר׬ׯ׺؀ؒؖ؛؝أ٬ٲcy;䐃耻>䀾mmaĀ;d׷׸䎓;䏜reve;䄞ƀeiy؇،ؐdil;䄢rc;䄜;䐓ot;䄠r;쀀𝔊;拙pf;쀀𝔾eater̀EFGLSTصلَٖٛ٦qualĀ;Lؾؿ扥ess;招ullEqual;执reater;檢ess;扷lantEqual;橾ilde;扳cr;쀀𝒢;扫ЀAacfiosuڅڋږڛڞڪھۊRDcy;䐪Āctڐڔek;䋇;䁞irc;䄤r;愌lbertSpace;愋ǰگ\0Ú²f;愍izontalLine;攀Āctۃۅòکrok;䄦mpńېۘownHumðįqual;扏܀EJOacdfgmnostuۺ۾܃܇܎ܚܞܡܨ݄ݸދޏޕcy;䐕lig;䄲cy;䐁cute耻Í䃍Āiyܓܘrc耻Î䃎;䐘ot;䄰r;愑rave耻Ì䃌ƀ;apܠܯܿĀcgÜ´Ü·r;䄪inaryI;慈lieóϝǴ݉\0ݢĀ;eݍݎ戬Āgrݓݘral;戫section;拂isibleĀCTݬݲomma;恣imes;恢ƀgptݿރވon;䄮f;쀀𝕀a;䎙cr;愐ilde;䄨ǫޚ\0ޞcy;䐆l耻Ï䃏ʀcfosuެ޷޼߂ߐĀiyÞ±Þµrc;䄴;䐙r;쀀𝔍pf;쀀𝕁ǣ߇\0ߌr;쀀𝒥rcy;䐈kcy;䐄΀HJacfosߤߨ߽߬߱ࠂࠈcy;䐥cy;䐌ppa;䎚Āey߶߻dil;䄶;䐚r;쀀𝔎pf;쀀𝕂cr;쀀𝒦րJTaceflmostࠥࠩࠬࡐࡣ঳সে্਷ੇcy;䐉耻<䀼ʀcmnpr࠷࠼ࡁࡄࡍute;䄹bda;䎛g;柪lacetrf;愒r;憞ƀaeyࡗ࡜ࡡron;䄽dil;䄻;䐛Āfsࡨ॰tԀACDFRTUVarࡾࢩࢱࣦ࣠ࣼयज़ΐ४Ānrࢃ࢏gleBracket;柨rowƀ;BR࢙࢚࢞憐ar;懤ightArrow;懆eiling;挈oǵࢷ\0ࣃbleBracket;柦nǔࣈ\0࣒eeVector;楡ectorĀ;Bࣛࣜ懃ar;楙loor;挊ightĀAV࣯ࣵrrow;憔ector;楎Āerँगeƀ;AVउऊऐ抣rrow;憤ector;楚iangleƀ;BEतथऩ抲ar;槏qual;抴pƀDTVषूौownVector;楑eeVector;楠ectorĀ;Bॖॗ憿ar;楘ectorĀ;B॥०憼ar;楒ightáΜs̀EFGLSTॾঋকঝঢভqualGreater;拚ullEqual;扦reater;扶ess;檡lantEqual;橽ilde;扲r;쀀𝔏Ā;eঽা拘ftarrow;懚idot;䄿ƀnpw৔ਖਛgȀLRlr৞৷ਂਐeftĀAR০৬rrow;柵ightArrow;柷ightArrow;柶eftĀarγਊightáοightáϊf;쀀𝕃erĀLRਢਬeftArrow;憙ightArrow;憘ƀchtਾੀੂòࡌ;憰rok;䅁;扪Ѐacefiosuਗ਼੝੠੷੼અઋ઎p;椅y;䐜Ādl੥੯iumSpace;恟lintrf;愳r;쀀𝔐nusPlus;戓pf;쀀𝕄cò੶;䎜ҀJacefostuણધભીଔଙඑ඗ඞcy;䐊cute;䅃ƀaey઴હાron;䅇dil;䅅;䐝ƀgswે૰଎ativeƀMTV૓૟૨ediumSpace;怋hiĀcn૦૘ë૙eryThiî૙tedĀGL૸ଆreaterGreateòٳessLesóੈLine;䀊r;쀀𝔑ȀBnptଢନଷ଺reak;恠BreakingSpace;䂠f;愕ڀ;CDEGHLNPRSTV୕ୖ୪୼஡௫ఄ౞಄ದ೘ൡඅ櫬Āou୛୤ngruent;扢pCap;扭oubleVerticalBar;戦ƀlqxஃஊ஛ement;戉ualĀ;Tஒஓ扠ilde;쀀≂̸ists;戄reater΀;EFGLSTஶஷ஽௉௓௘௥扯qual;扱ullEqual;쀀≧̸reater;쀀≫̸ess;批lantEqual;쀀⩾̸ilde;扵umpń௲௽ownHump;쀀≎̸qual;쀀≏̸eĀfsఊధtTriangleƀ;BEచఛడ拪ar;쀀⧏̸qual;括s̀;EGLSTవశ఼ౄోౘ扮qual;扰reater;扸ess;쀀≪̸lantEqual;쀀⩽̸ilde;扴estedĀGL౨౹reaterGreater;쀀⪢̸essLess;쀀⪡̸recedesƀ;ESಒಓಛ技qual;쀀⪯̸lantEqual;拠ĀeiಫಹverseElement;戌ghtTriangleƀ;BEೋೌ೒拫ar;쀀⧐̸qual;拭ĀquೝഌuareSuĀbp೨೹setĀ;E೰ೳ쀀⊏̸qual;拢ersetĀ;Eഃആ쀀⊐̸qual;拣ƀbcpഓതൎsetĀ;Eഛഞ쀀⊂⃒qual;抈ceedsȀ;ESTലള഻െ抁qual;쀀⪰̸lantEqual;拡ilde;쀀≿̸ersetĀ;E൘൛쀀⊃⃒qual;抉ildeȀ;EFT൮൯൵ൿ扁qual;扄ullEqual;扇ilde;扉erticalBar;戤cr;쀀𝒩ilde耻Ñ䃑;䎝܀Eacdfgmoprstuvලෂ෉෕ෛ෠෧෼ขภยา฿ไlig;䅒cute耻Ó䃓Āiy෎ීrc耻Ô䃔;䐞blac;䅐r;쀀𝔒rave耻Ò䃒ƀaei෮ෲ෶cr;䅌ga;䎩cron;䎟pf;쀀𝕆enCurlyĀDQฎบoubleQuote;怜uote;怘;橔Āclวฬr;쀀𝒪ash耻Ø䃘iŬื฼de耻Õ䃕es;樷ml耻Ö䃖erĀBP๋๠Āar๐๓r;怾acĀek๚๜;揞et;掴arenthesis;揜Ҁacfhilors๿ງຊຏຒດຝະ໼rtialD;戂y;䐟r;쀀𝔓i;䎦;䎠usMinus;䂱Āipຢອncareplanåڝf;愙Ȁ;eio຺ູ໠໤檻cedesȀ;EST່້໏໚扺qual;檯lantEqual;扼ilde;找me;怳Ādp໩໮uct;戏ortionĀ;aȥ໹l;戝Āci༁༆r;쀀𝒫;䎨ȀUfos༑༖༛༟OT耻"䀢r;쀀𝔔pf;愚cr;쀀𝒬؀BEacefhiorsu༾གྷཇའཱིྦྷྪྭ႖ႩႴႾarr;椐G耻®䂮ƀcnrཎནབute;䅔g;柫rĀ;tཛྷཝ憠l;椖ƀaeyཧཬཱron;䅘dil;䅖;䐠Ā;vླྀཹ愜erseĀEUྂྙĀlq྇ྎement;戋uilibrium;懋pEquilibrium;楯r»ཹo;䎡ghtЀACDFTUVa࿁࿫࿳ဢဨၛႇϘĀnr࿆࿒gleBracket;柩rowƀ;BL࿜࿝࿡憒ar;懥eftArrow;懄eiling;按oǵ࿹\0စbleBracket;柧nǔည\0နeeVector;楝ectorĀ;Bဝသ懂ar;楕loor;挋Āerိ၃eƀ;AVဵံြ抢rrow;憦ector;楛iangleƀ;BEၐၑၕ抳ar;槐qual;抵pƀDTVၣၮၸownVector;楏eeVector;楜ectorĀ;Bႂႃ憾ar;楔ectorĀ;B႑႒懀ar;楓Āpuႛ႞f;愝ndImplies;楰ightarrow;懛ĀchႹႼr;愛;憱leDelayed;槴ڀHOacfhimoqstuფჱჷჽᄙᄞᅑᅖᅡᅧᆵᆻᆿĀCcჩხHcy;䐩y;䐨FTcy;䐬cute;䅚ʀ;aeiyᄈᄉᄎᄓᄗ檼ron;䅠dil;䅞rc;䅜;䐡r;쀀𝔖ortȀDLRUᄪᄴᄾᅉownArrow»ОeftArrow»࢚ightArrow»࿝pArrow;憑gma;䎣allCircle;战pf;쀀𝕊ɲᅭ\0\0ᅰt;戚areȀ;ISUᅻᅼᆉᆯ斡ntersection;抓uĀbpᆏᆞsetĀ;Eᆗᆘ抏qual;抑ersetĀ;Eᆨᆩ抐qual;抒nion;抔cr;쀀𝒮ar;拆ȀbcmpᇈᇛሉላĀ;sᇍᇎ拐etĀ;Eᇍᇕqual;抆ĀchᇠህeedsȀ;ESTᇭᇮᇴᇿ扻qual;檰lantEqual;扽ilde;承Tháྌ;我ƀ;esሒሓሣ拑rsetĀ;Eሜም抃qual;抇et»ሓրHRSacfhiorsሾቄ቉ቕ቞ቱቶኟዂወዑORN耻Þ䃞ADE;愢ĀHc቎ቒcy;䐋y;䐦Ābuቚቜ;䀉;䎤ƀaeyብቪቯron;䅤dil;䅢;䐢r;쀀𝔗Āeiቻ኉Dzኀ\0ኇefore;戴a;䎘Ācn኎ኘkSpace;쀀  Space;怉ldeȀ;EFTካኬኲኼ戼qual;扃ullEqual;扅ilde;扈pf;쀀𝕋ipleDot;惛Āctዖዛr;쀀𝒯rok;䅦ૡዷጎጚጦ\0ጬጱ\0\0\0\0\0ጸጽ፷ᎅ\0᏿ᐄᐊᐐĀcrዻጁute耻Ú䃚rĀ;oጇገ憟cir;楉rǣጓ\0጖y;䐎ve;䅬Āiyጞጣrc耻Û䃛;䐣blac;䅰r;쀀𝔘rave耻Ù䃙acr;䅪Ādiፁ፩erĀBPፈ፝Āarፍፐr;䁟acĀekፗፙ;揟et;掵arenthesis;揝onĀ;P፰፱拃lus;抎Āgp፻፿on;䅲f;쀀𝕌ЀADETadps᎕ᎮᎸᏄϨᏒᏗᏳrrowƀ;BDᅐᎠᎤar;椒ownArrow;懅ownArrow;憕quilibrium;楮eeĀ;AᏋᏌ报rrow;憥ownáϳerĀLRᏞᏨeftArrow;憖ightArrow;憗iĀ;lᏹᏺ䏒on;䎥ing;䅮cr;쀀𝒰ilde;䅨ml耻Ü䃜ҀDbcdefosvᐧᐬᐰᐳᐾᒅᒊᒐᒖash;披ar;æ««y;䐒ashĀ;lᐻᐼ抩;櫦Āerᑃᑅ;拁ƀbtyᑌᑐᑺar;怖Ā;iᑏᑕcalȀBLSTᑡᑥᑪᑴar;戣ine;䁼eparator;杘ilde;所ThinSpace;怊r;쀀𝔙pf;쀀𝕍cr;쀀𝒱dash;抪ʀcefosᒧᒬᒱᒶᒼirc;䅴dge;拀r;

25쀀𝔚pf;쀀𝕎cr;쀀𝒲Ȁfiosᓋᓐᓒᓘr;쀀𝔛;䎞pf;쀀𝕏cr;쀀𝒳ҀAIUacfosuᓱᓵᓹᓽᔄᔏᔔᔚᔠcy;䐯cy;䐇cy;䐮cute耻Ý䃝Āiyᔉᔍrc;䅶;䐫r;쀀𝔜pf;쀀𝕐cr;쀀𝒴ml;䅸ЀHacdefosᔵᔹᔿᕋᕏᕝᕠᕤcy;䐖cute;䅹Āayᕄᕉron;䅽;䐗ot;䅻Dzᕔ\0ᕛoWidtè૙a;䎖r;愨pf;愤cr;쀀𝒵௡ᖃᖊᖐ\0ᖰᖶᖿ\0\0\0\0ᗆᗛᗫᙟ᙭\0ᚕ᚛ᚲᚹ\0ᚾcute耻á䃡reve;䄃̀;Ediuyᖜᖝᖡᖣᖨᖭ戾;쀀∾̳;房rc耻â䃢te肻´̆;䐰lig耻æ䃦Ā;r²ᖺ;쀀𝔞rave耻à䃠ĀepᗊᗖĀfpᗏᗔsym;愵èᗓha;䎱ĀapᗟcĀclᗤᗧr;䄁g;樿ɤᗰ\0\0ᘊʀ;adsvᗺᗻᗿᘁᘇ戧nd;橕;橜lope;橘;橚΀;elmrszᘘᘙᘛᘞᘿᙏᙙ戠;榤e»ᘙsdĀ;aᘥᘦ戡ѡᘰᘲᘴᘶᘸᘺᘼᘾ;榨;榩;榪;榫;榬;榭;榮;榯tĀ;vᙅᙆ戟bĀ;dᙌᙍ抾;榝Āptᙔᙗh;戢»¹arr;捼Āgpᙣᙧon;䄅f;쀀𝕒΀;Eaeiop዁ᙻᙽᚂᚄᚇᚊ;橰cir;橯;扊d;手s;䀧roxĀ;e዁ᚒñᚃing耻å䃥ƀctyᚡᚦᚨr;쀀𝒶;䀪mpĀ;e዁ᚯñʈilde耻ã䃣ml耻ä䃤Āciᛂᛈoninôɲnt;樑ࠀNabcdefiklnoprsu᛭ᛱᜰ᜼ᝃᝈ᝸᝽០៦ᠹᡐᜍ᤽᥈ᥰot;櫭Ācrᛶ᜞kȀcepsᜀᜅᜍᜓong;扌psilon;䏶rime;怵imĀ;e᜚᜛戽q;拍Ŷᜢᜦee;抽edĀ;gᜬᜭ挅e»ᜭrkĀ;t፜᜷brk;掶Āoyᜁᝁ;䐱quo;怞ʀcmprtᝓ᝛ᝡᝤᝨausĀ;eĊĉptyv;榰séᜌnoõēƀahwᝯ᝱ᝳ;䎲;愶een;扬r;쀀𝔟g΀costuvwឍឝឳេ៕៛៞ƀaiuបពរðݠrc;旯p»፱ƀdptឤឨឭot;樀lus;樁imes;樂ɱឹ\0\0ើcup;樆ar;昅riangleĀdu៍្own;施p;斳plus;樄eåᑄåᒭarow;植ƀako៭ᠦᠵĀcn៲ᠣkƀlst៺֫᠂ozenge;槫riangleȀ;dlr᠒᠓᠘᠝斴own;斾eft;旂ight;斸k;搣Ʊᠫ\0ᠳƲᠯ\0ᠱ;斒;斑4;斓ck;斈ĀeoᠾᡍĀ;qᡃᡆ쀀=⃥uiv;쀀≡⃥t;挐Ȁptwxᡙᡞᡧᡬf;쀀𝕓Ā;tᏋᡣom»Ꮜtie;拈؀DHUVbdhmptuvᢅᢖᢪᢻᣗᣛᣬ᣿ᤅᤊᤐᤡȀLRlrᢎᢐᢒᢔ;敗;敔;敖;敓ʀ;DUduᢡᢢᢤᢦᢨ敐;敦;敩;敤;敧ȀLRlrᢳᢵᢷᢹ;敝;敚;敜;教΀;HLRhlrᣊᣋᣍᣏᣑᣓᣕ救;敬;散;敠;敫;敢;敟ox;槉ȀLRlrᣤᣦᣨᣪ;敕;敒;攐;攌ʀ;DUduڽ᣷᣹᣻᣽;敥;敨;攬;攴inus;抟lus;択imes;抠ȀLRlrᤙᤛᤝ᤟;敛;敘;攘;攔΀;HLRhlrᤰᤱᤳᤵᤷ᤻᤹攂;敪;敡;敞;攼;攤;攜Āevģ᥂bar耻¦䂦Ȁceioᥑᥖᥚᥠr;쀀𝒷mi;恏mĀ;e᜚᜜lƀ;bhᥨᥩᥫ䁜;槅sub;柈Ŭᥴ᥾lĀ;e᥹᥺怢t»᥺pƀ;Eeįᦅᦇ;檮Ā;qۜۛೡᦧ\0᧨ᨑᨕᨲ\0ᨷᩐ\0\0᪴\0\0᫁\0\0ᬡᬮ᭍᭒\0᯽\0ᰌƀcpr᦭ᦲ᧝ute;䄇̀;abcdsᦿᧀᧄ᧊᧕᧙戩nd;橄rcup;橉Āau᧏᧒p;橋p;橇ot;橀;쀀∩︀Āeo᧢᧥t;恁îړȀaeiu᧰᧻ᨁᨅǰ᧵\0᧸s;橍on;䄍dil耻ç䃧rc;䄉psĀ;sᨌᨍ橌m;橐ot;䄋ƀdmnᨛᨠᨦil肻¸ƭptyv;榲t脀¢;eᨭᨮ䂢räƲr;쀀𝔠ƀceiᨽᩀᩍy;䑇ckĀ;mᩇᩈ朓ark»ᩈ;䏇r΀;Ecefms᩟᩠ᩢᩫ᪤᪪᪮旋;槃ƀ;elᩩᩪᩭ䋆q;扗eɡᩴ\0\0᪈rrowĀlr᩼᪁eft;憺ight;憻ʀRSacd᪒᪔᪖᪚᪟»ཇ;擈st;抛irc;抚ash;抝nint;樐id;櫯cir;槂ubsĀ;u᪻᪼晣it»᪼ˬ᫇᫔᫺\0ᬊonĀ;eᫍᫎ䀺Ā;qÇÆɭ᫙\0\0᫢aĀ;t᫞᫟䀬;䁀ƀ;fl᫨᫩᫫戁îᅠeĀmx᫱᫶ent»᫩eóɍǧ᫾\0ᬇĀ;dኻᬂot;橭nôɆƀfryᬐᬔᬗ;쀀𝕔oäɔ脀©;sŕᬝr;愗Āaoᬥᬩrr;憵ss;朗Ācuᬲᬷr;쀀𝒸Ābpᬼ᭄Ā;eᭁᭂ櫏;櫑Ā;eᭉᭊ櫐;櫒dot;拯΀delprvw᭠᭬᭷ᮂᮬᯔ᯹arrĀlr᭨᭪;椸;椵ɰ᭲\0\0᭵r;拞c;拟arrĀ;p᭿ᮀ憶;椽̀;bcdosᮏᮐᮖᮡᮥᮨ截rcap;橈Āauᮛᮞp;橆p;橊ot;抍r;橅;쀀∪︀Ȁalrv᮵ᮿᯞᯣrrĀ;mᮼᮽ憷;椼yƀevwᯇᯔᯘqɰᯎ\0\0ᯒreã᭳uã᭵ee;拎edge;拏en耻¤䂤earrowĀlrᯮ᯳eft»ᮀight»ᮽeäᯝĀciᰁᰇoninôǷnt;戱lcty;挭ঀAHabcdefhijlorstuwz᰸᰻᰿ᱝᱩᱵᲊᲞᲬᲷ᳻᳿ᴍᵻᶑᶫᶻ᷆᷍rò΁ar;楥Ȁglrs᱈ᱍ᱒᱔ger;怠eth;愸òᄳhĀ;vᱚᱛ怐»ऊūᱡᱧarow;椏aã̕Āayᱮᱳron;䄏;䐴ƀ;ao̲ᱼᲄĀgrʿᲁr;懊tseq;橷ƀglmᲑᲔᲘ耻°䂰ta;䎴ptyv;榱ĀirᲣᲨsht;楿;쀀𝔡arĀlrᲳᲵ»ࣜ»သʀaegsv᳂͸᳖᳜᳠mƀ;oș᳊᳔ndĀ;ș᳑uit;晦amma;䏝in;拲ƀ;io᳧᳨᳸䃷de脀÷;o᳧ᳰntimes;拇nø᳷cy;䑒cɯᴆ\0\0ᴊrn;挞op;挍ʀlptuwᴘᴝᴢᵉᵕlar;䀤f;쀀𝕕ʀ;emps̋ᴭᴷᴽᵂqĀ;d͒ᴳot;扑inus;戸lus;戔quare;抡blebarwedgåúnƀadhᄮᵝᵧownarrowóᲃarpoonĀlrᵲᵶefôᲴighôᲶŢᵿᶅkaro÷གɯᶊ\0\0ᶎrn;挟op;挌ƀcotᶘᶣᶦĀryᶝᶡ;쀀𝒹;䑕l;槶rok;䄑Ādrᶰᶴot;拱iĀ;fᶺ᠖斿Āah᷀᷃ròЩaòྦangle;榦Āci᷒ᷕy;䑟grarr;柿ऀDacdefglmnopqrstuxḁḉḙḸոḼṉṡṾấắẽỡἪἷὄ὎὚ĀDoḆᴴoôᲉĀcsḎḔute耻é䃩ter;橮ȀaioyḢḧḱḶron;䄛rĀ;cḭḮ扖耻ê䃪lon;払;䑍ot;䄗ĀDrṁṅot;扒;쀀𝔢ƀ;rsṐṑṗ檚ave耻è䃨Ā;dṜṝ檖ot;檘Ȁ;ilsṪṫṲṴ檙nters;揧;愓Ā;dṹṺ檕ot;檗ƀapsẅẉẗcr;䄓tyƀ;svẒẓẕ戅et»ẓpĀ1;ẝẤijạả;怄;怅怃ĀgsẪẬ;䅋p;怂ĀgpẴẸon;䄙f;쀀𝕖ƀalsỄỎỒrĀ;sỊị拕l;槣us;橱iƀ;lvỚớở䎵on»ớ;䏵ȀcsuvỪỳἋἣĀioữḱrc»Ḯɩỹ\0\0ỻíՈantĀglἂἆtr»ṝess»Ṻƀaeiἒ἖Ἒls;䀽st;扟vĀ;DȵἠD;橸parsl;槥ĀDaἯἳot;打rr;楱ƀcdiἾὁỸr;愯oô͒ĀahὉὋ;䎷耻ð䃰Āmrὓὗl耻ë䃫o;悬ƀcipὡὤὧl;䀡sôծĀeoὬὴctatioîՙnentialåչৡᾒ\0ᾞ\0ᾡᾧ\0\0ῆῌ\0ΐ\0ῦῪ \0 ⁚llingdotseñṄy;䑄male;晀ƀilrᾭᾳ῁lig;耀ffiɩᾹ\0\0᾽g;耀ffig;耀ffl;쀀𝔣lig;耀filig;쀀fjƀaltῙ῜ῡt;晭ig;耀flns;斱of;䆒ǰ΅\0ῳf;쀀𝕗ĀakֿῷĀ;vῼ´拔;櫙artint;樍Āao‌⁕Ācs‑⁒ႉ‸⁅⁈\0⁐β•‥‧‪‬\0‮耻½䂽;慓耻¼䂼;慕;慙;慛Ƴ‴\0‶;慔;慖ʴ‾⁁\0\0⁃耻¾䂾;慗;慜5;慘ƶ⁌\0⁎;慚;慝8;慞l;恄wn;挢cr;쀀𝒻ࢀEabcdefgijlnorstv₂₉₟₥₰₴⃰⃵⃺⃿℃ℒℸ̗ℾ⅒↞Ā;lٍ₇;檌ƀcmpₐₕ₝ute;䇵maĀ;dₜ᳚䎳;檆reve;䄟Āiy₪₮rc;䄝;䐳ot;䄡Ȁ;lqsؾق₽⃉ƀ;qsؾٌ⃄lanô٥Ȁ;cdl٥⃒⃥⃕c;檩otĀ;o⃜⃝檀Ā;l⃢⃣檂;檄Ā;e⃪⃭쀀⋛︀s;檔r;쀀𝔤Ā;gٳ؛mel;愷cy;䑓Ȁ;Eajٚℌℎℐ;檒;檥;檤ȀEaesℛℝ℩ℴ;扩pĀ;p℣ℤ檊rox»ℤĀ;q℮ℯ檈Ā;q℮ℛim;拧pf;쀀𝕘Āci⅃ⅆr;愊mƀ;el٫ⅎ⅐;檎;檐茀>;cdlqr׮ⅠⅪⅮⅳⅹĀciⅥⅧ;檧r;橺ot;拗Par;榕uest;橼ʀadelsↄⅪ←ٖ↛ǰ↉\0↎proø₞r;楸qĀlqؿ↖lesó₈ií٫Āen↣↭rtneqq;쀀≩︀Å↪ԀAabcefkosy⇄⇇⇱⇵⇺∘∝∯≨≽ròΠȀilmr⇐⇔⇗⇛rsðᒄf»․ilôکĀdr⇠⇤cy;䑊ƀ;cwࣴ⇫⇯ir;楈;憭ar;意irc;䄥ƀalr∁∎∓rtsĀ;u∉∊晥it»∊lip;怦con;抹r;쀀𝔥sĀew∣∩arow;椥arow;椦ʀamopr∺∾≃≞≣rr;懿tht;戻kĀlr≉≓eftarrow;憩ightarrow;憪f;쀀𝕙bar;怕ƀclt≯≴≸r;쀀𝒽asè⇴rok;䄧Ābp⊂⊇ull;恃hen»ᱛૡ⊣\0⊪\0⊸⋅⋎\0⋕⋳\0\0⋸⌢⍧⍢⍿\0⎆⎪⎴cute耻í䃭ƀ;iyݱ⊰⊵rc耻î䃮;䐸Ācx⊼⊿y;䐵cl耻¡䂡ĀfrΟ⋉;쀀𝔦rave耻ì䃬Ȁ;inoܾ⋝⋩⋮Āin⋢⋦nt;樌t;戭fin;槜ta;愩lig;䄳ƀaop⋾⌚⌝ƀcgt⌅⌈⌗r;䄫ƀelpܟ⌏⌓inåގarôܠh;䄱f;抷ed;䆵ʀ;cfotӴ⌬⌱⌽⍁are;愅inĀ;t⌸⌹戞ie;槝doô⌙ʀ;celpݗ⍌⍐⍛⍡al;抺Āgr⍕⍙eróᕣã⍍arhk;樗rod;樼Ȁcgpt⍯⍲⍶⍻y;䑑on;䄯f;쀀𝕚a;䎹uest耻¿䂿Āci⎊⎏r;쀀𝒾nʀ;EdsvӴ⎛⎝⎡ӳ;拹ot;拵Ā;v⎦⎧拴;拳Ā;iݷ⎮lde;䄩ǫ⎸\0⎼cy;䑖l耻ï䃯̀cfmosu⏌⏗⏜⏡⏧⏵Āiy⏑⏕rc;䄵;䐹r;쀀𝔧ath;䈷pf;쀀𝕛ǣ⏬\0⏱r;쀀𝒿rcy;䑘kcy;䑔Ѐacfghjos␋␖␢␧␭␱␵␻ppaĀ;v␓␔䎺;䏰Āey␛␠dil;䄷;䐺r;쀀𝔨reen;䄸cy;䑅cy;䑜pf;쀀𝕜cr;쀀𝓀஀ABEHabcdefghjlmnoprstuv⑰⒁⒆⒍⒑┎┽╚▀♎♞♥♹♽⚚⚲⛘❝❨➋⟀⠁⠒ƀart⑷⑺⑼rò৆òΕail;椛arr;椎Ā;gঔ⒋;檋ar;楢ॣ⒥\0⒪\0⒱\0\0\0\0\0⒵Ⓔ\0ⓆⓈⓍ\0⓹ute;䄺mptyv;榴raîࡌbda;䎻gƀ;dlࢎⓁⓃ;榑åࢎ;檅uo耻«䂫rЀ;bfhlpst࢙ⓞⓦⓩ⓫⓮⓱⓵Ā;f࢝ⓣs;椟s;椝ë≒p;憫l;椹im;楳l;憢ƀ;ae⓿─┄檫il;椙Ā;s┉┊檭;쀀⪭︀ƀabr┕┙┝rr;椌rk;杲Āak┢┬cĀek┨┪;䁻;䁛Āes┱┳;榋lĀdu┹┻;榏;榍Ȁaeuy╆╋╖╘ron;䄾Ādi═╔il;䄼ìࢰâ┩;

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25'.split("").map(e=>e.charCodeAt(0))),iw=new Uint16Array("Ȁaglq	��\x1BÉ­�\0\0�p;䀦os;䀧t;䀾t;䀼uot;䀢".split("").map(e=>e.charCodeAt(0)));var Xi;const aw=new Map([[0,65533],[128,8364],[130,8218],[131,402],[132,8222],[133,8230],[134,8224],[135,8225],[136,710],[137,8240],[138,352],[139,8249],[140,338],[142,381],[145,8216],[146,8217],[147,8220],[148,8221],[149,8226],[150,8211],[151,8212],[152,732],[153,8482],[154,353],[155,8250],[156,339],[158,382],[159,376]]),ow=(Xi=String.fromCodePoint)!==null&&Xi!==void 0?Xi:function(e){let t="";return e>65535&&(e-=65536,t+=String.fromCharCode(e>>>10&1023|55296),e=56320|e&1023),t+=String.fromCharCode(e),t};function sw(e){var t;return e>=55296&&e<=57343||e>1114111?65533:(t=aw.get(e))!==null&&t!==void 0?t:e}var ve;(function(e){e[e.NUM=35]="NUM",e[e.SEMI=59]="SEMI",e[e.EQUALS=61]="EQUALS",e[e.ZERO=48]="ZERO",e[e.NINE=57]="NINE",e[e.LOWER_A=97]="LOWER_A",e[e.LOWER_F=102]="LOWER_F",e[e.LOWER_X=120]="LOWER_X",e[e.LOWER_Z=122]="LOWER_Z",e[e.UPPER_A=65]="UPPER_A",e[e.UPPER_F=70]="UPPER_F",e[e.UPPER_Z=90]="UPPER_Z"})(ve||(ve={}));const lw=32;var Dt;(function(e){e[e.VALUE_LENGTH=49152]="VALUE_LENGTH",e[e.BRANCH_LENGTH=16256]="BRANCH_LENGTH",e[e.JUMP_TABLE=127]="JUMP_TABLE"})(Dt||(Dt={}));function Da(e){return e>=ve.ZERO&&e<=ve.NINE}function uw(e){return e>=ve.UPPER_A&&e<=ve.UPPER_F||e>=ve.LOWER_A&&e<=ve.LOWER_F}function cw(e){return e>=ve.UPPER_A&&e<=ve.UPPER_Z||e>=ve.LOWER_A&&e<=ve.LOWER_Z||Da(e)}function dw(e){return e===ve.EQUALS||cw(e)}var ye;(function(e){e[e.EntityStart=0]="EntityStart",e[e.NumericStart=1]="NumericStart",e[e.NumericDecimal=2]="NumericDecimal",e[e.NumericHex=3]="NumericHex",e[e.NamedEntity=4]="NamedEntity"})(ye||(ye={}));var Et;(function(e){e[e.Legacy=0]="Legacy",e[e.Strict=1]="Strict",e[e.Attribute=2]="Attribute"})(Et||(Et={}));class hw{constructor(t,n,r){this.decodeTree=t,this.emitCodePoint=n,this.errors=r,this.state=ye.EntityStart,this.consumed=1,this.result=0,this.treeIndex=0,this.excess=1,this.decodeMode=Et.Strict}startEntity(t){this.decodeMode=t,this.state=ye.EntityStart,this.result=0,this.treeIndex=0,this.excess=1,this.consumed=1}write(t,n){switch(this.state){case ye.EntityStart:return t.charCodeAt(n)===ve.NUM?(this.state=ye.NumericStart,this.consumed+=1,this.stateNumericStart(t,n+1)):(this.state=ye.NamedEntity,this.stateNamedEntity(t,n));case ye.NumericStart:return this.stateNumericStart(t,n);case ye.NumericDecimal:return this.stateNumericDecimal(t,n);case ye.NumericHex:return this.stateNumericHex(t,n);case ye.NamedEntity:return this.stateNamedEntity(t,n)}}stateNumericStart(t,n){return n>=t.length?-1:(t.charCodeAt(n)|lw)===ve.LOWER_X?(this.state=ye.NumericHex,this.consumed+=1,this.stateNumericHex(t,n+1)):(this.state=ye.NumericDecimal,this.stateNumericDecimal(t,n))}addToNumericResult(t,n,r,a){if(n!==r){const o=r-n;this.result=this.result*Math.pow(a,o)+parseInt(t.substr(n,o),a),this.consumed+=o}}stateNumericHex(t,n){const r=n;for(;n<t.length;){const a=t.charCodeAt(n);if(Da(a)||uw(a))n+=1;else return this.addToNumericResult(t,r,n,16),this.emitNumericEntity(a,3)}return this.addToNumericResult(t,r,n,16),-1}stateNumericDecimal(t,n){const r=n;for(;n<t.length;){const a=t.charCodeAt(n);if(Da(a))n+=1;else return this.addToNumericResult(t,r,n,10),this.emitNumericEntity(a,2)}return this.addToNumericResult(t,r,n,10),-1}emitNumericEntity(t,n){var r;if(this.consumed<=n)return(r=this.errors)===null||r===void 0||r.absenceOfDigitsInNumericCharacterReference(this.consumed),0;if(t===ve.SEMI)this.consumed+=1;else if(this.decodeMode===Et.Strict)return 0;return this.emitCodePoint(sw(this.result),this.consumed),this.errors&&(t!==ve.SEMI&&this.errors.missingSemicolonAfterCharacterReference(),this.errors.validateNumericCharacterReference(this.result)),this.consumed}stateNamedEntity(t,n){const{decodeTree:r}=this;let a=r[this.treeIndex],o=(a&Dt.VALUE_LENGTH)>>14;for(;n<t.length;n++,this.excess++){const s=t.charCodeAt(n);if(this.treeIndex=fw(r,a,this.treeIndex+Math.max(1,o),s),this.treeIndex<0)return this.result===0||this.decodeMode===Et.Attribute&&(o===0||dw(s))?0:this.emitNotTerminatedNamedEntity();if(a=r[this.treeIndex],o=(a&Dt.VALUE_LENGTH)>>14,o!==0){if(s===ve.SEMI)return this.emitNamedEntityData(this.treeIndex,o,this.consumed+this.excess);this.decodeMode!==Et.Strict&&(this.result=this.treeIndex,this.consumed+=this.excess,this.excess=0)}}return-1}emitNotTerminatedNamedEntity(){var t;const{result:n,decodeTree:r}=this,a=(r[n]&Dt.VALUE_LENGTH)>>14;return this.emitNamedEntityData(n,a,this.consumed),(t=this.errors)===null||t===void 0||t.missingSemicolonAfterCharacterReference(),this.consumed}emitNamedEntityData(t,n,r){const{decodeTree:a}=this;return this.emitCodePoint(n===1?a[t]&~Dt.VALUE_LENGTH:a[t+1],r),n===3&&this.emitCodePoint(a[t+2],r),r}end(){var t;switch(this.state){case ye.NamedEntity:return this.result!==0&&(this.decodeMode!==Et.Attribute||this.result===this.treeIndex)?this.emitNotTerminatedNamedEntity():0;case ye.NumericDecimal:return this.emitNumericEntity(0,2);case ye.NumericHex:return this.emitNumericEntity(0,3);case ye.NumericStart:return(t=this.errors)===null||t===void 0||t.absenceOfDigitsInNumericCharacterReference(this.consumed),0;case ye.EntityStart:return 0}}}function Ec(e){let t="";const n=new hw(e,r=>t+=ow(r));return function(a,o){let s=0,l=0;for(;(l=a.indexOf("&",l))>=0;){t+=a.slice(s,l),n.startEntity(o);const c=n.write(a,l+1);if(c<0){s=l+n.end();break}s=l+c,l=c===0?s+1:s}const u=t+a.slice(s);return t="",u}}function fw(e,t,n,r){const a=(t&Dt.BRANCH_LENGTH)>>7,o=t&Dt.JUMP_TABLE;if(a===0)return o!==0&&r===o?n:-1;if(o){const u=r-o;return u<0||u>=a?-1:e[n+u]-1}let s=n,l=s+a-1;for(;s<=l;){const u=s+l>>>1,c=e[u];if(c<r)s=u+1;else if(c>r)l=u-1;else return e[u+a]}return-1}const mw=Ec(rw);Ec(iw);function Tc(e,t=Et.Legacy){return mw(e,t)}function pw(e){return Object.prototype.toString.call(e)}function mo(e){return pw(e)==="[object String]"}const gw=Object.prototype.hasOwnProperty;function xw(e,t){return gw.call(e,t)}

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38n--)if(e[n].content){p=e[n].content.charCodeAt(e[n].content.length-1);break}let g=32;if(u<c)g=l.charCodeAt(u);else for(n=a+1;n<e.length&&!(e[n].type==="softbreak"||e[n].type==="hardbreak");n++)if(e[n].content){g=e[n].content.charCodeAt(0);break}const y=Bn(p)||Ln(String.fromCharCode(p)),v=Bn(g)||Ln(String.fromCharCode(g)),S=Mn(p),w=Mn(g);if(w?h=!1:v&&(S||y||(h=!1)),S?m=!1:y&&(w||v||(m=!1)),g===34&&d[0]==='"'&&p>=48&&p<=57&&(m=h=!1),h&&m&&(h=y,m=v),!h&&!m){f&&(o.content=mr(o.content,d.index,yl));continue}if(m)for(n=r.length-1;n>=0;n--){let N=r[n];if(r[n].level<s)break;if(N.single===f&&r[n].level===s){N=r[n];let C,k;f?(C=t.md.options.quotes[2],k=t.md.options.quotes[3]):(C=t.md.options.quotes[0],k=t.md.options.quotes[1]),o.content=mr(o.content,d.index,k),e[N.token].content=mr(e[N.token].content,N.pos,C),u+=k.length-1,N.token===a&&(u+=C.length-1),l=o.content,c=l.length,r.length=n;continue e}}h?r.push({token:a,pos:d.index,single:f,level:s}):m&&f&&(o.content=mr(o.content,d.index,yl))}}}function Zw(e){if(e.md.options.typographer)for(let t=e.tokens.length-1;t>=0;t--)e.tokens[t].type!=="inline"||!Qw.test(e.tokens[t].content)||Jw(e.tokens[t].children,e)}function Xw(e){let t,n;const r=e.tokens,a=r.length;for(let o=0;o<a;o++){if(r[o].type!=="inline")continue;const s=r[o].children,l=s.length;for(t=0;t<l;t++)s[t].type==="text_special"&&(s[t].type="text");for(t=n=0;t<l;t++)s[t].type==="text"&&t+1<l&&s[t+1].type==="text"?s[t+1].content=s[t].content+s[t+1].content:(t!==n&&(s[n]=s[t]),n++);t!==n&&(s.length=n)}}const ea=[["normalize",Mw],["block",Lw],["inline",Bw],["linkify",zw],["replacements",Kw],["smartquotes",Zw],["text_join",Xw]];function go(){this.ruler=new Ie;for(let e=0;e<ea.length;e++)this.ruler.push(ea[e][0],ea[e][1])}go.prototype.process=function(e){const t=this.ruler.getRules("");for(let n=0,r=t.length;n<r;n++)t[n](e)};go.prototype.State=_c;function mt(e,t,n,r){this.src=e,this.md=t,this.env=n,this.tokens=r,this.bMarks=[],this.eMarks=[],this.tShift=[],this.sCount=[],this.bsCount=[],this.blkIndent=0,this.line=0,this.lineMax=0,this.tight=!1,this.ddIndent=-1,this.listIndent=-1,this.parentType="root",this.level=0;const a=this.src;for(let o=0,s=0,l=0,u=0,c=a.length,d=!1;s<c;s++){const h=a.charCodeAt(s);if(!d)if(le(h)){l++,h===9?u+=4-u%4:u++;continue}else d=!0;(h===10||s===c-1)&&(h!==10&&s++,this.bMarks.push(o),this.eMarks.push(s),this.tShift.push(l),this.sCount.push(u),this.bsCount.push(0),d=!1,l=0,u=0,o=s+1)}this.bMarks.push(a.length),this.eMarks.push(a.length),this.tShift.push(0),this.sCount.push(0),this.bsCount.push(0),this.lineMax=this.bMarks.length-1}mt.prototype.push=function(e,t,n){const r=new Xe(e,t,n);return r.block=!0,n<0&&this.level--,r.level=this.level,n>0&&this.level++,this.tokens.push(r),r};mt.prototype.isEmpty=function(t){return this.bMarks[t]+this.tShift[t]>=this.eMarks[t]};mt.prototype.skipEmptyLines=function(t){for(let n=this.lineMax;t<n&&!(this.bMarks[t]+this.tShift[t]<this.eMarks[t]);t++);return t};mt.prototype.skipSpaces=function(t){for(let n=this.src.length;t<n;t++){const r=this.src.charCodeAt(t);if(!le(r))break}return t};mt.prototype.skipSpacesBack=function(t,n){if(t<=n)return t;for(;t>n;)if(!le(this.src.charCodeAt(--t)))return t+1;return t};mt.prototype.skipChars=function(t,n){for(let r=this.src.length;t<r&&this.src.charCodeAt(t)===n;t++);return t};mt.prototype.skipCharsBack=function(t,n,r){if(t<=r)return t;for(;t>r;)if(n!==this.src.charCodeAt(--t))return t+1;return t};mt.prototype.getLines=function(t,n,r,a){if(t>=n)return"";const o=new Array(n-t);for(let s=0,l=t;l<n;l++,s++){let u=0;const c=this.bMarks[l];let d=c,h;for(l+1<n||a?h=this.eMarks[l]+1:h=this.eMarks[l];d<h&&u<r;){const m=this.src.charCodeAt(d);if(le(m))m===9?u+=4-(u+this.bsCount[l])%4:u++;else if(d-c<this.tShift[l])u++;else break;d++}u>r?o[s]=new Array(u-r+1).join(" ")+this.src.slice(d,h):o[s]=this.src.slice(d,h)}return o.join("")};mt.prototype.Token=Xe;const e2=65536;function ta(e,t){const n=e.bMarks[t]+e.tShift[t],r=e.eMarks[t];return e.src.slice(n,r)}function wl(e){const t=[],n=e.length;let r=0,a=e.charCodeAt(r),o=!1,s=0,l="";for(;r<n;)a===124&&(o?(l+=e.substring(s,r-1),s=r):(t.push(l+e.substring(s,r)),l="",s=r+1)),o=a===92,r++,a=e.charCodeAt(r);return t.push(l+e.substring(s)),t}function t2(e,t,n,r){if(t+2>n)return!1;let a=t+1;if(e.sCount[a]<e.blkIndent||e.sCount[a]-e.blkIndent>=4)return!1;let o=e.bMarks[a]+e.tShift[a];if(o>=e.eMarks[a])return!1;

38const s=e.src.charCodeAt(o++);if(s!==124&&s!==45&&s!==58||o>=e.eMarks[a])return!1;const l=e.src.charCodeAt(o++);if(l!==124&&l!==45&&l!==58&&!le(l)||s===45&&le(l))return!1;for(;o<e.eMarks[a];){const N=e.src.charCodeAt(o);if(N!==124&&N!==45&&N!==58&&!le(N))return!1;o++}let u=ta(e,t+1),c=u.split("|");const d=[];for(let N=0;N<c.length;N++){const C=c[N].trim();if(!C){if(N===0||N===c.length-1)continue;return!1}if(!/^:?-+:?$/.test(C))return!1;C.charCodeAt(C.length-1)===58?d.push(C.charCodeAt(0)===58?"center":"right"):C.charCodeAt(0)===58?d.push("left"):d.push("")}if(u=ta(e,t).trim(),u.indexOf("|")===-1||e.sCount[t]-e.blkIndent>=4)return!1;c=wl(u),c.length&&c[0]===""&&c.shift(),c.length&&c[c.length-1]===""&&c.pop();const h=c.length;if(h===0||h!==d.length)return!1;if(r)return!0;const m=e.parentType;e.parentType="table";const f=e.md.block.ruler.getRules("blockquote"),p=e.push("table_open","table",1),g=[t,0];p.map=g;const y=e.push("thead_open","thead",1);y.map=[t,t+1];const v=e.push("tr_open","tr",1);v.map=[t,t+1];for(let N=0;N<c.length;N++){const C=e.push("th_open","th",1);d[N]&&(C.attrs=[["style","text-align:"+d[N]]]);const k=e.push("inline","",0);k.content=c[N].trim(),k.children=[],e.push("th_close","th",-1)}e.push("tr_close","tr",-1),e.push("thead_close","thead",-1);let S,w=0;for(a=t+2;a<n&&!(e.sCount[a]<e.blkIndent);a++){let N=!1;for(let k=0,I=f.length;k<I;k++)if(f[k](e,a,n,!0)){N=!0;break}if(N||(u=ta(e,a).trim(),!u)||e.sCount[a]-e.blkIndent>=4||(c=wl(u),c.length&&c[0]===""&&c.shift(),c.length&&c[c.length-1]===""&&c.pop(),w+=h-c.length,w>e2))break;if(a===t+2){const k=e.push("tbody_open","tbody",1);k.map=S=[t+2,0]}const C=e.push("tr_open","tr",1);C.map=[a,a+1];for(let k=0;k<h;k++){const I=e.push("td_open","td",1);d[k]&&(I.attrs=[["style","text-align:"+d[k]]]);const W=e.push("inline","",0);W.content=c[k]?c[k].trim():"",W.children=[],e.push("td_close","td",-1)}e.push("tr_close","tr",-1)}return S&&(e.push("tbody_close","tbody",-1),S[1]=a),e.push("table_close","table",-1),g[1]=a,e.parentType=m,e.line=a,!0}function n2(e,t,n){if(e.sCount[t]-e.blkIndent<4)return!1;let r=t+1,a=r;for(;r<n;){if(e.isEmpty(r)){r++;continue}if(e.sCount[r]-e.blkIndent>=4){r++,a=r;continue}break}e.line=a;const o=e.push("code_block","code",0);return o.content=e.getLines(t,a,4+e.blkIndent,!1)+`
39`,o.map=[t,e.line],!0}function r2(e,t,n,r){let a=e.bMarks[t]+e.tShift[t],o=e.eMarks[t];if(e.sCount[t]-e.blkIndent>=4||a+3>o)return!1;const s=e.src.charCodeAt(a);if(s!==126&&s!==96)return!1;let l=a;a=e.skipChars(a,s);let u=a-l;if(u<3)return!1;const c=e.src.slice(l,a),d=e.src.slice(a,o);if(s===96&&d.indexOf(String.fromCharCode(s))>=0)return!1;if(r)return!0;let h=t,m=!1;for(;h++,!(h>=n||(a=l=e.bMarks[h]+e.tShift[h],o=e.eMarks[h],a<o&&e.sCount[h]<e.blkIndent));)if(e.src.charCodeAt(a)===s&&!(e.sCount[h]-e.blkIndent>=4)&&(a=e.skipChars(a,s),!(a-l<u)&&(a=e.skipSpaces(a),!(a<o)))){m=!0;break}u=e.sCount[t],e.line=h+(m?1:0);const f=e.push("fence","code",0);return f.info=d,f.content=e.getLines(t+1,h,u,!0),f.markup=c,f.map=[t,e.line],!0}function i2(e,t,n,r){let a=e.bMarks[t]+e.tShift[t],o=e.eMarks[t];const s=e.lineMax;if(e.sCount[t]-e.blkIndent>=4||e.src.charCodeAt(a)!==62)return!1;if(r)return!0;const l=[],u=[],c=[],d=[],h=e.md.block.ruler.getRules("blockquote"),m=e.parentType;e.parentType="blockquote";let f=!1,p;for(p=t;p<n;p++){const w=e.sCount[p]<e.blkIndent;if(a=e.bMarks[p]+e.tShift[p],o=e.eMarks[p],a>=o)break;if(e.src.charCodeAt(a++)===62&&!w){let C=e.sCount[p]+1,k,I;e.src.charCodeAt(a)===32?(a++,C++,I=!1,k=!0):e.src.charCodeAt(a)===9?(k=!0,(e.bsCount[p]+C)%4===3?(a++,C++,I=!1):I=!0):k=!1;let W=C;for(l.push(e.bMarks[p]),e.bMarks[p]=a;a<o;){const E=e.src.charCodeAt(a);if(le(E))E===9?W+=4-(W+e.bsCount[p]+(I?1:0))%4:W++;else break;a++}f=a>=o,u.push(e.bsCount[p]),e.bsCount[p]=e.sCount[p]+1+(k?1:0),c.push(e.sCount[p]),e.sCount[p]=W-C,d.push(e.tShift[p]),e.tShift[p]=a-e.bMarks[p];continue}if(f)break;let N=!1;for(let C=0,k=h.length;C<k;C++)if(h[C](e,p,n,!0)){N=!0;break}if(N){e.lineMax=p,e.blkIndent!==0&&(l.push(e.bMarks[p]),u.push(e.bsCount[p]),d.push(e.tShift[p]),c.push(e.sCount[p]),e.sCount[p]-=e.blkIndent);break}l.push(e.bMarks[p]),u.push(e.bsCount[p]),d.push(e.tShift[p]),c.push(e.sCount[p]),e.sCount[p]=-1}const g=e.blkIndent;e.blkIndent=0;const y=e.push("blockquote_open","blockquote",1);y.markup=">";const v=[t,0];y.map=v,e.md.block.tokenize(e,t,p);const S=e.push("blockquote_close","blockquote",-1);S.markup=">",e.lineMax=s,e.parentType=m,v[1]=e.line;for(let w=0;w<d.length;w++)e.bMarks[w+t]=l[w],e.tShift[w+t]=d[w],e.sCount[w+t]=c[w],e.bsCount[w+t]=u[w];return e.blkIndent=g,!0}function a2(e,t,n,r){const a=e.eMarks[t];if(e.sCount[t]-e.blkIndent>=4)return!1;let o=e.bMarks[t]+e.tShift[t];

39const s=e.src.charCodeAt(o++);if(s!==42&&s!==45&&s!==95)return!1;let l=1;for(;o<a;){const c=e.src.charCodeAt(o++);if(c!==s&&!le(c))return!1;c===s&&l++}if(l<3)return!1;if(r)return!0;e.line=t+1;const u=e.push("hr","hr",0);return u.map=[t,e.line],u.markup=Array(l+1).join(String.fromCharCode(s)),!0}function vl(e,t){const n=e.eMarks[t];let r=e.bMarks[t]+e.tShift[t];const a=e.src.charCodeAt(r++);if(a!==42&&a!==45&&a!==43)return-1;if(r<n){const o=e.src.charCodeAt(r);if(!le(o))return-1}return r}function kl(e,t){const n=e.bMarks[t]+e.tShift[t],r=e.eMarks[t];let a=n;if(a+1>=r)return-1;let o=e.src.charCodeAt(a++);if(o<48||o>57)return-1;for(;;){if(a>=r)return-1;if(o=e.src.charCodeAt(a++),o>=48&&o<=57){if(a-n>=10)return-1;continue}if(o===41||o===46)break;return-1}return a<r&&(o=e.src.charCodeAt(a),!le(o))?-1:a}function o2(e,t){const n=e.level+2;for(let r=t+2,a=e.tokens.length-2;r<a;r++)e.tokens[r].level===n&&e.tokens[r].type==="paragraph_open"&&(e.tokens[r+2].hidden=!0,e.tokens[r].hidden=!0,r+=2)}function s2(e,t,n,r){let a,o,s,l,u=t,c=!0;if(e.sCount[u]-e.blkIndent>=4||e.listIndent>=0&&e.sCount[u]-e.listIndent>=4&&e.sCount[u]<e.blkIndent)return!1;let d=!1;r&&e.parentType==="paragraph"&&e.sCount[u]>=e.blkIndent&&(d=!0);let h,m,f;if((f=kl(e,u))>=0){if(h=!0,s=e.bMarks[u]+e.tShift[u],m=Number(e.src.slice(s,f-1)),d&&m!==1)return!1}else if((f=vl(e,u))>=0)h=!1;else return!1;if(d&&e.skipSpaces(f)>=e.eMarks[u])return!1;if(r)return!0;const p=e.src.charCodeAt(f-1),g=e.tokens.length;h?(l=e.push("ordered_list_open","ol",1),m!==1&&(l.attrs=[["start",m]])):l=e.push("bullet_list_open","ul",1);const y=[u,0];l.map=y,l.markup=String.fromCharCode(p);let v=!1;const S=e.md.block.ruler.getRules("list"),w=e.parentType;for(e.parentType="list";u<n;){o=f,a=e.eMarks[u];const N=e.sCount[u]+f-(e.bMarks[u]+e.tShift[u]);let C=N;for(;o<a;){const P=e.src.charCodeAt(o);if(P===9)C+=4-(C+e.bsCount[u])%4;else if(P===32)C++;else break;o++}const k=o;let I;k>=a?I=1:I=C-N,I>4&&(I=1);const W=N+I;l=e.push("list_item_open","li",1),l.markup=String.fromCharCode(p);const E=[u,0];l.map=E,h&&(l.info=e.src.slice(s,f-1));const O=e.tight,R=e.tShift[u],D=e.sCount[u],L=e.listIndent;if(e.listIndent=e.blkIndent,e.blkIndent=W,e.tight=!0,e.tShift[u]=k-e.bMarks[u],e.sCount[u]=C,k>=a&&e.isEmpty(u+1)?e.line=Math.min(e.line+2,n):e.md.block.tokenize(e,u,n,!0),(!e.tight||v)&&(c=!1),v=e.line-u>1&&e.isEmpty(e.line-1),e.blkIndent=e.listIndent,e.listIndent=L,e.tShift[u]=R,e.sCount[u]=D,e.tight=O,l=e.push("list_item_close","li",-1),l.markup=String.fromCharCode(p),u=e.line,E[1]=u,u>=n||e.sCount[u]<e.blkIndent||e.sCount[u]-e.blkIndent>=4)break;let B=!1;for(let P=0,M=S.length;P<M;P++)if(S[P](e,u,n,!0)){B=!0;break}if(B)break;if(h){if(f=kl(e,u),f<0)break;s=e.bMarks[u]+e.tShift[u]}else if(f=vl(e,u),f<0)break;if(p!==e.src.charCodeAt(f-1))break}return h?l=e.push("ordered_list_close","ol",-1):l=e.push("bullet_list_close","ul",-1),l.markup=String.fromCharCode(p),y[1]=u,e.line=u,e.parentType=w,c&&o2(e,g),!0}function l2(e,t,n,r){let a=e.bMarks[t]+e.tShift[t],o=e.eMarks[t],s=t+1;if(e.sCount[t]-e.blkIndent>=4||e.src.charCodeAt(a)!==91)return!1;function l(S){const w=e.lineMax;if(S>=w||e.isEmpty(S))return null;let N=!1;if(e.sCount[S]-e.blkIndent>3&&(N=!0),e.sCount[S]<0&&(N=!0),!N){const I=e.md.block.ruler.getRules("reference"),W=e.parentType;e.parentType="reference";let E=!1;for(let O=0,R=I.length;O<R;O++)if(I[O](e,S,w,!0)){E=!0;break}if(e.parentType=W,E)return null}const C=e.bMarks[S]+e.tShift[S],k=e.eMarks[S];return e.src.slice(C,k+1)}let u=e.src.slice(a,o+1);o=u.length;let c=-1;for(a=1;a<o;a++){const S=u.charCodeAt(a);if(S===91)return!1;if(S===93){c=a;break}else if(S===10){const w=l(s);w!==null&&(u+=w,o=u.length,s++)}else if(S===92&&(a++,a<o&&u.charCodeAt(a)===10)){const w=l(s);w!==null&&(u+=w,o=u.length,s++)}}if(c<0||u.charCodeAt(c+1)!==58)return!1;for(a=c+2;a<o;a++){const S=u.charCodeAt(a);if(S===10){const w=l(s);w!==null&&(u+=w,o=u.length,s++)}else if(!le(S))break}const d=e.md.helpers.parseLinkDestination(u,a,o);if(!d.ok)return!1;const h=e.md.normalizeLink(d.str);if(!e.md.validateLink(h))return!1;a=d.pos;const m=a,f=s,p=a;for(;a<o;a++){const S=u.charCodeAt(a);if(S===10){const w=l(s);w!==null&&(u+=w,o=u.length,s++)}else if(!le(S))break}let g=e.md.helpers.parseLinkTitle(u,a,o);for(;g.can_continue;){const S=l(s);if(S===null)break;u+=S,a=o,o=u.length,s++,g=e.md.helpers.parseLinkTitle(u,a,o,g)}let y;for(a<o&&p!==a&&g.ok?(y=g.str,a=g.pos):(y="",a=m,s=f);a<o;){const S=u.charCodeAt(a);if(!le(S))break;a++}if(a<o&&u.charCodeAt(a)!==10&&y)for(y="",a=m,s=f;a<o;){const S=u.charCodeAt(a);if(!le(S))break;a++}if(a<o&&u.charCodeAt(a)!==10)return!1;const v=ui(u.slice(1,c));return v?(r||(typeof e.env.references>"u"&&(e.env.references={}),typeof e.env.references[v]>"u"&&(e.env.references[v]={title:y,href:h}),e.line=s),!0):!1}const u2=["address","article","aside","base","basefont","blockquote","body","caption","center","col","colgroup","dd","details","dialog","dir","div","dl","dt","fieldset","figcaption","figure","footer","form","frame","frameset","h1","h2","h3","h4","h5","h6","head","header","hr","html","iframe","legend","li","link","main","menu","menuitem","nav","noframes","ol","optgroup","option","p","param","search","section","summary","table","tbody","td","tfoot","th","thead","title","tr","track","ul"],c2="[a-zA-Z_:][a-zA-Z0-9:._-]*",d2="[^\"'=<>`\\x00-\\x20]+",h2="'[^']*'",f2='"[^"]*"',m2="(?:"+d2+"|"+h2+"|"+f2+")",p2="(?:\\s+"+c2+"(?:\\

39s*=\\s*"+m2+")?)",Fc="<[A-Za-z][A-Za-z0-9\\-]*"+p2+"*\\s*\\/?>",Pc="<\\/[A-Za-z][A-Za-z0-9\\-]*\\s*>",g2="<!---?>|<!--(?:[^-]|-[^-]|--[^>])*-->",x2="<[?][\\s\\S]*?[?]>",b2="<![A-Za-z][^>]*>",y2="<!\\[CDATA\\[[\\s\\S]*?\\]\\]>",w2=new RegExp("^(?:"+Fc+"|"+Pc+"|"+g2+"|"+x2+"|"+b2+"|"+y2+")"),v2=new RegExp("^(?:"+Fc+"|"+Pc+")"),Kt=[[/^<(script|pre|style|textarea)(?=(\s|>|$))/i,/<\/(script|pre|style|textarea)>/i,!0],[/^<!--/,/-->/,!0],[/^<\?/,/\?>/,!0],[/^<![A-Z]/,/>/,!0],[/^<!\[CDATA\[/,/\]\]>/,!0],[new RegExp("^</?("+u2.join("|")+")(?=(\\s|/?>|$))","i"),/^$/,!0],[new RegExp(v2.source+"\\s*$"),/^$/,!1]];function k2(e,t,n,r){let a=e.bMarks[t]+e.tShift[t],o=e.eMarks[t];if(e.sCount[t]-e.blkIndent>=4||!e.md.options.html||e.src.charCodeAt(a)!==60)return!1;let s=e.src.slice(a,o),l=0;for(;l<Kt.length&&!Kt[l][0].test(s);l++);if(l===Kt.length)return!1;if(r)return Kt[l][2];let u=t+1;if(!Kt[l][1].test(s)){for(;u<n&&!(e.sCount[u]<e.blkIndent);u++)if(a=e.bMarks[u]+e.tShift[u],o=e.eMarks[u],s=e.src.slice(a,o),Kt[l][1].test(s)){s.length!==0&&u++;break}}e.line=u;const c=e.push("html_block","",0);return c.map=[t,u],c.content=e.getLines(t,u,e.blkIndent,!0),!0}function A2(e,t,n,r){let a=e.bMarks[t]+e.tShift[t],o=e.eMarks[t];if(e.sCount[t]-e.blkIndent>=4)return!1;let s=e.src.charCodeAt(a);if(s!==35||a>=o)return!1;let l=1;for(s=e.src.charCodeAt(++a);s===35&&a<o&&l<=6;)l++,s=e.src.charCodeAt(++a);if(l>6||a<o&&!le(s))return!1;if(r)return!0;o=e.skipSpacesBack(o,a);const u=e.skipCharsBack(o,35,a);u>a&&le(e.src.charCodeAt(u-1))&&(o=u),e.line=t+1;const c=e.push("heading_open","h"+String(l),1);c.markup="########".slice(0,l),c.map=[t,e.line];const d=e.push("inline","",0);d.content=e.src.slice(a,o).trim(),d.map=[t,e.line],d.children=[];const h=e.push("heading_close","h"+String(l),-1);return h.markup="########".slice(0,l),!0}function S2(e,t,n){const r=e.md.block.ruler.getRules("paragraph");if(e.sCount[t]-e.blkIndent>=4)return!1;const a=e.parentType;e.parentType="paragraph";let o=0,s,l=t+1;for(;l<n&&!e.isEmpty(l);l++){if(e.sCount[l]-e.blkIndent>3)continue;if(e.sCount[l]>=e.blkIndent){let f=e.bMarks[l]+e.tShift[l];const p=e.eMarks[l];if(f<p&&(s=e.src.charCodeAt(f),(s===45||s===61)&&(f=e.skipChars(f,s),f=e.skipSpaces(f),f>=p))){o=s===61?1:2;break}}if(e.sCount[l]<0)continue;let m=!1;for(let f=0,p=r.length;f<p;f++)if(r[f](e,l,n,!0)){m=!0;break}if(m)break}if(!o)return!1;const u=e.getLines(t,l,e.blkIndent,!1).trim();e.line=l+1;const c=e.push("heading_open","h"+String(o),1);c.markup=String.fromCharCode(s),c.map=[t,e.line];const d=e.push("inline","",0);d.content=u,d.map=[t,e.line-1],d.children=[];const h=e.push("heading_close","h"+String(o),-1);return h.markup=String.fromCharCode(s),e.parentType=a,!0}function j2(e,t,n){const r=e.md.block.ruler.getRules("paragraph"),a=e.parentType;let o=t+1;for(e.parentType="paragraph";o<n&&!e.isEmpty(o);o++){if(e.sCount[o]-e.blkIndent>3||e.sCount[o]<0)continue;let c=!1;for(let d=0,h=r.length;d<h;d++)if(r[d](e,o,n,!0)){c=!0;break}if(c)break}const s=e.getLines(t,o,e.blkIndent,!1).trim();e.line=o;const l=e.push("paragraph_open","p",1);l.map=[t,e.line];const u=e.push("inline","",0);return u.content=s,u.map=[t,e.line],u.children=[],e.push("paragraph_close","p",-1),e.parentType=a,!0}const pr=[["table",t2,["paragraph","reference"]],["code",n2],["fence",r2,["paragraph","reference","blockquote","list"]],["blockquote",i2,["paragraph","reference","blockquote","list"]],["hr",a2,["paragraph","reference","blockquote","list"]],["list",s2,["paragraph","reference","blockquote"]],["reference",l2],["html_block",k2,["paragraph","reference","blockquote"]],["heading",A2,["paragraph","reference","blockquote"]],["lheading",S2],["paragraph",j2]];function ci(){this.ruler=new Ie;for(let e=0;e<pr.length;e++)this.ruler.push(pr[e][0],pr[e][1],{alt:(pr[e][2]||[]).slice()})}ci.prototype.tokenize=function(e,t,n){const r=this.ruler.getRules(""),a=r.length,o=e.md.options.maxNesting;let s=t,l=!1;for(;s<n&&(e.line=s=e.skipEmptyLines(s),!(s>=n||e.sCount[s]<e.blkIndent));){if(e.level>=o){e.line=n;break}const u=e.line;let c=!1;for(let d=0;d<a;d++)if(c=r[d](e,s,n,!1),c){if(u>=e.line)throw new Error("block rule didn't increment state.line");break}if(!c)throw new Error("none of the block rules matched");e.tight=!l,e.isEmpty(e.line-1)&&(l=!0),s=e.line,s<n&&e.isEmpty(s)&&(l=!0,s++,e.line=s)}};ci.prototype.parse=function(e,t,n,r){if(!e)return;const a=new this.State(e,t,n,r);this.tokenize(a,a.line,a.lineMax)};ci.prototype.State=mt;function Xn(e,t,n,r){this.src=e,this.env=n,this.md=t,this.tokens=r,this.tokens_meta=Array(r.length),this.pos=0,this.posMax=this.src.length,this.level=0,this.pending="",this.pendingLevel=0,this.cache={},this.delimiters=[],this._prev_delimiters=[],this.backticks={},this.backticksScanned=!1,this.linkLevel=0}Xn.prototype.pushPending=function(){const e=new Xe("text","",0);return e.content=this.pending,e.level=this.pendingLevel,this.tokens.push(e),this.pending="",e};Xn.prototype.push=function(e,t,n){this.pending&&this.pushPending();const r=new Xe(e,t,n);let a=null;return n<0&&(this.level--,this.delimiters=this._prev_delimiters.pop()),r.level=this.level,n>0&&(this.level++,this._prev_delimiters.push(this.delimiters),this.delimiters=[],a={delimiters:this.delimiters}),this.pendingLevel=this.level,this.tokens.push(r),this.tokens_meta.push(a),r};

39Xn.prototype.scanDelims=function(e,t){const n=this.posMax,r=this.src.charCodeAt(e),a=e>0?this.src.charCodeAt(e-1):32;let o=e;for(;o<n&&this.src.charCodeAt(o)===r;)o++;const s=o-e,l=o<n?this.src.charCodeAt(o):32,u=Bn(a)||Ln(String.fromCharCode(a)),c=Bn(l)||Ln(String.fromCharCode(l)),d=Mn(a),h=Mn(l),m=!h&&(!c||d||u),f=!d&&(!u||h||c);return{can_open:m&&(t||!f||u),can_close:f&&(t||!m||c),length:s}};Xn.prototype.Token=Xe;function N2(e){switch(e){case 10:case 33:case 35:case 36:case 37:case 38:case 42:case 43:case 45:case 58:case 60:case 61:case 62:case 64:case 91:case 92:case 93:case 94:case 95:case 96:case 123:case 125:case 126:return!0;default:return!1}}function C2(e,t){let n=e.pos;for(;n<e.posMax&&!N2(e.src.charCodeAt(n));)n++;return n===e.pos?!1:(t||(e.pending+=e.src.slice(e.pos,n)),e.pos=n,!0)}const E2=/(?:^|[^a-z0-9.+-])([a-z][a-z0-9.+-]*)$/i;function T2(e,t){if(!e.md.options.linkify||e.linkLevel>0)return!1;const n=e.pos,r=e.posMax;if(n+3>r||e.src.charCodeAt(n)!==58||e.src.charCodeAt(n+1)!==47||e.src.charCodeAt(n+2)!==47)return!1;const a=e.pending.match(E2);if(!a)return!1;const o=a[1],s=e.md.linkify.matchAtStart(e.src.slice(n-o.length));if(!s)return!1;let l=s.url;if(l.length<=o.length)return!1;let u=l.length;for(;u>0&&l.charCodeAt(u-1)===42;)u--;u!==l.length&&(l=l.slice(0,u));const c=e.md.normalizeLink(l);if(!e.md.validateLink(c))return!1;if(!t){e.pending=e.pending.slice(0,-o.length);const d=e.push("link_open","a",1);d.attrs=[["href",c]],d.markup="linkify",d.info="auto";const h=e.push("text","",0);h.content=e.md.normalizeLinkText(l);const m=e.push("link_close","a",-1);m.markup="linkify",m.info="auto"}return e.pos+=l.length-o.length,!0}function I2(e,t){let n=e.pos;if(e.src.charCodeAt(n)!==10)return!1;const r=e.pending.length-1,a=e.posMax;if(!t)if(r>=0&&e.pending.charCodeAt(r)===32)if(r>=1&&e.pending.charCodeAt(r-1)===32){let o=r-1;for(;o>=1&&e.pending.charCodeAt(o-1)===32;)o--;e.pending=e.pending.slice(0,o),e.push("hardbreak","br",0)}else e.pending=e.pending.slice(0,-1),e.push("softbreak","br",0);else e.push("softbreak","br",0);for(n++;n<a&&le(e.src.charCodeAt(n));)n++;return e.pos=n,!0}const xo=[];for(let e=0;e<256;e++)xo.push(0);"\\!\"#$%&'()*+,./:;<=>?@[]^_`{|}~-".split("").forEach(function(e){xo[e.charCodeAt(0)]=1});function D2(e,t){let n=e.pos;const r=e.posMax;if(e.src.charCodeAt(n)!==92||(n++,n>=r))return!1;let a=e.src.charCodeAt(n);if(a===10){for(t||e.push("hardbreak","br",0),n++;n<r&&(a=e.src.charCodeAt(n),!!le(a));)n++;return e.pos=n,!0}let o=e.src[n];if(a>=55296&&a<=56319&&n+1<r){const l=e.src.charCodeAt(n+1);l>=56320&&l<=57343&&(o+=e.src[n+1],n++)}const s="\\"+o;if(!t){const l=e.push("text_special","",0);a<256&&xo[a]!==0?l.content=o:l.content=s,l.markup=s,l.info="escape"}return e.pos=n+1,!0}function _2(e,t){let n=e.pos;if(e.src.charCodeAt(n)!==96)return!1;const a=n;n++;const o=e.posMax;for(;n<o&&e.src.charCodeAt(n)===96;)n++;const s=e.src.slice(a,n),l=s.length;if(e.backticksScanned&&(e.backticks[l]||0)<=a)return t||(e.pending+=s),e.pos+=l,!0;let u=n,c;for(;(c=e.src.indexOf("`",u))!==-1;){for(u=c+1;u<o&&e.src.charCodeAt(u)===96;)u++;const d=u-c;if(d===l){if(!t){const h=e.push("code_inline","code",0);h.markup=s,h.content=e.src.slice(n,c).replace(/\n/g," ").replace(/^ (.+) $/,"$1")}return e.pos=u,!0}e.backticks[d]=c}return e.backticksScanned=!0,t||(e.pending+=s),e.pos+=l,!0}function R2(e,t){const n=e.pos,r=e.src.charCodeAt(n);if(t||r!==126)return!1;const a=e.scanDelims(e.pos,!0);let o=a.length;const s=String.fromCharCode(r);if(o<2)return!1;let l;o%2&&(l=e.push("text","",0),l.content=s,o--);for(let u=0;u<o;u+=2)l=e.push("text","",0),l.content=s+s,e.delimiters.push({marker:r,length:0,token:e.tokens.length-1,end:-1,open:a.can_open,close:a.can_close});return e.pos+=a.length,!0}function Al(e,t){let n;const r=[],a=t.length;for(let o=0;o<a;o++){const s=t[o];if(s.marker!==126||s.end===-1)continue;const l=t[s.end];n=e.tokens[s.token],n.type="s_open",n.tag="s",n.nesting=1,n.markup="~~",n.content="",n=e.tokens[l.token],n.type="s_close",n.tag="s",n.nesting=-1,n.markup="~~",n.content="",e.tokens[l.token-1].type==="text"&&e.tokens[l.token-1].content==="~"&&r.push(l.token-1)}for(;r.length;){const o=r.pop();let s=o+1;for(;s<e.tokens.length&&e.tokens[s].type==="s_close";)s++;s--,o!==s&&(n=e.tokens[s],e.tokens[s]=e.tokens[o],e.tokens[o]=n)}}function F2(e){const t=e.tokens_meta,n=e.tokens_meta.length;Al(e,e.delimiters);for(let r=0;r<n;r++)t[r]&&t[r].delimiters&&Al(e,t[r].delimiters)}const Oc={tokenize:R2,postProcess:F2};

39function P2(e,t){const n=e.pos,r=e.src.charCodeAt(n);if(t||r!==95&&r!==42)return!1;const a=e.scanDelims(e.pos,r===42);for(let o=0;o<a.length;o++){const s=e.push("text","",0);s.content=String.fromCharCode(r),e.delimiters.push({marker:r,length:a.length,token:e.tokens.length-1,end:-1,open:a.can_open,close:a.can_close})}return e.pos+=a.length,!0}function Sl(e,t){const n=t.length;for(let r=n-1;r>=0;r--){const a=t[r];if(a.marker!==95&&a.marker!==42||a.end===-1)continue;const o=t[a.end],s=r>0&&t[r-1].end===a.end+1&&t[r-1].marker===a.marker&&t[r-1].token===a.token-1&&t[a.end+1].token===o.token+1,l=String.fromCharCode(a.marker),u=e.tokens[a.token];u.type=s?"strong_open":"em_open",u.tag=s?"strong":"em",u.nesting=1,u.markup=s?l+l:l,u.content="";const c=e.tokens[o.token];c.type=s?"strong_close":"em_close",c.tag=s?"strong":"em",c.nesting=-1,c.markup=s?l+l:l,c.content="",s&&(e.tokens[t[r-1].token].content="",e.tokens[t[a.end+1].token].content="",r--)}}function O2(e){const t=e.tokens_meta,n=e.tokens_meta.length;Sl(e,e.delimiters);for(let r=0;r<n;r++)t[r]&&t[r].delimiters&&Sl(e,t[r].delimiters)}const Mc={tokenize:P2,postProcess:O2};function M2(e,t){let n,r,a,o,s="",l="",u=e.pos,c=!0;if(e.src.charCodeAt(e.pos)!==91)return!1;const d=e.pos,h=e.posMax,m=e.pos+1,f=e.md.helpers.parseLinkLabel(e,e.pos,!0);if(f<0)return!1;let p=f+1;if(p<h&&e.src.charCodeAt(p)===40){for(c=!1,p++;p<h&&(n=e.src.charCodeAt(p),!(!le(n)&&n!==10));p++);if(p>=h)return!1;if(u=p,a=e.md.helpers.parseLinkDestination(e.src,p,e.posMax),a.ok){for(s=e.md.normalizeLink(a.str),e.md.validateLink(s)?p=a.pos:s="",u=p;p<h&&(n=e.src.charCodeAt(p),!(!le(n)&&n!==10));p++);if(a=e.md.helpers.parseLinkTitle(e.src,p,e.posMax),p<h&&u!==p&&a.ok)for(l=a.str,p=a.pos;p<h&&(n=e.src.charCodeAt(p),!(!le(n)&&n!==10));p++);}(p>=h||e.src.charCodeAt(p)!==41)&&(c=!0),p++}if(c){if(typeof e.env.references>"u")return!1;if(p<h&&e.src.charCodeAt(p)===91?(u=p+1,p=e.md.helpers.parseLinkLabel(e,p),p>=0?r=e.src.slice(u,p++):p=f+1):p=f+1,r||(r=e.src.slice(m,f)),o=e.env.references[ui(r)],!o)return e.pos=d,!1;s=o.href,l=o.title}if(!t){e.pos=m,e.posMax=f;const g=e.push("link_open","a",1),y=[["href",s]];g.attrs=y,l&&y.push(["title",l]),e.linkLevel++,e.md.inline.tokenize(e),e.linkLevel--,e.push("link_close","a",-1)}return e.pos=p,e.posMax=h,!0}function L2(e,t){let n,r,a,o,s,l,u,c,d="";const h=e.pos,m=e.posMax;if(e.src.charCodeAt(e.pos)!==33||e.src.charCodeAt(e.pos+1)!==91)return!1;const f=e.pos+2,p=e.md.helpers.parseLinkLabel(e,e.pos+1,!1);if(p<0)return!1;if(o=p+1,o<m&&e.src.charCodeAt(o)===40){for(o++;o<m&&(n=e.src.charCodeAt(o),!(!le(n)&&n!==10));o++);if(o>=m)return!1;for(c=o,l=e.md.helpers.parseLinkDestination(e.src,o,e.posMax),l.ok&&(d=e.md.normalizeLink(l.str),e.md.validateLink(d)?o=l.pos:d=""),c=o;o<m&&(n=e.src.charCodeAt(o),!(!le(n)&&n!==10));o++);if(l=e.md.helpers.parseLinkTitle(e.src,o,e.posMax),o<m&&c!==o&&l.ok)for(u=l.str,o=l.pos;o<m&&(n=e.src.charCodeAt(o),!(!le(n)&&n!==10));o++);else u="";if(o>=m||e.src.charCodeAt(o)!==41)return e.pos=h,!1;o++}else{if(typeof e.env.references>"u")return!1;if(o<m&&e.src.charCodeAt(o)===91?(c=o+1,o=e.md.helpers.parseLinkLabel(e,o),o>=0?a=e.src.slice(c,o++):o=p+1):o=p+1,a||(a=e.src.slice(f,p)),s=e.env.references[ui(a)],!s)return e.pos=h,!1;d=s.href,u=s.title}if(!t){r=e.src.slice(f,p);const g=[];e.md.inline.parse(r,e.md,e.env,g);const y=e.push("image","img",0),v=[["src",d],["alt",""]];y.attrs=v,y.children=g,y.content=r,u&&v.push(["title",u])}return e.pos=o,e.posMax=m,!0}const B2=/^([a-zA-Z0-9.!#$%&'*+/=?^_`{|}~-]+@[a-zA-Z0-9](?:[a-zA-Z0-9-]{0,61}[a-zA-Z0-9])?(?:\.[a-zA-Z0-9](?:[a-zA-Z0-9-]{0,61}[a-zA-Z0-9])?)*)$/,W2=/^([a-zA-Z][a-zA-Z0-9+.-]{1,31}):([^<>\x00-\x20]*)$/;function G2(e,t){let n=e.pos;if(e.src.charCodeAt(n)!==60)return!1;const r=e.pos,a=e.posMax;for(;;){if(++n>=a)return!1;const s=e.src.charCodeAt(n);if(s===60)return!1;if(s===62)break}const o=e.src.slice(r+1,n);if(W2.test(o)){const s=e.md.normalizeLink(o);if(!e.md.validateLink(s))return!1;if(!t){const l=e.push("link_open","a",1);l.attrs=[["href",s]],l.markup="autolink",l.info="auto";const u=e.push("text","",0);u.content=e.md.normalizeLinkText(o);const c=e.push("link_close","a",-1);c.markup="autolink",c.info="auto"}return e.pos+=o.length+2,!0}if(B2.test(o)){const s=e.md.normalizeLink("mailto:"+o);if(!e.md.validateLink(s))return!1;if(!t){const l=e.push("link_open","a",1);l.attrs=[["href",s]],l.markup="autolink",l.info="auto";const u=e.push("text","",0);u.content=e.md.normalizeLinkText(o);const c=e.push("link_close","a",-1);c.markup="autolink",c.info="auto"}return e.pos+=o.length+2,!0}return!1}function z2(e){return/^<a[>\s]/i.test(e)}function q2(e){return/^<\/a\s*>/i.test(e)}function $2(e){const t=e|32;return t>=97&&t<=122}function U2(e,t){if(!e.md.options.html)return!1;

39const n=e.posMax,r=e.pos;if(e.src.charCodeAt(r)!==60||r+2>=n)return!1;const a=e.src.charCodeAt(r+1);if(a!==33&&a!==63&&a!==47&&!$2(a))return!1;const o=e.src.slice(r).match(w2);if(!o)return!1;if(!t){const s=e.push("html_inline","",0);s.content=o[0],z2(s.content)&&e.linkLevel++,q2(s.content)&&e.linkLevel--}return e.pos+=o[0].length,!0}const H2=/^&#((?:x[a-f0-9]{1,6}|[0-9]{1,7}));/i,V2=/^&([a-z][a-z0-9]{1,31});/i;function Y2(e,t){const n=e.pos,r=e.posMax;if(e.src.charCodeAt(n)!==38||n+1>=r)return!1;if(e.src.charCodeAt(n+1)===35){const o=e.src.slice(n).match(H2);if(o){if(!t){const s=o[1][0].toLowerCase()==="x"?parseInt(o[1].slice(1),16):parseInt(o[1],10),l=e.push("text_special","",0);l.content=po(s)?Gr(s):Gr(65533),l.markup=o[0],l.info="entity"}return e.pos+=o[0].length,!0}}else{const o=e.src.slice(n).match(V2);if(o){const s=Tc(o[0]);if(s!==o[0]){if(!t){const l=e.push("text_special","",0);l.content=s,l.markup=o[0],l.info="entity"}return e.pos+=o[0].length,!0}}}return!1}function jl(e){const t={},n=e.length;if(!n)return;let r=0,a=-2;const o=[];for(let s=0;s<n;s++){const l=e[s];if(o.push(0),(e[r].marker!==l.marker||a!==l.token-1)&&(r=s),a=l.token,l.length=l.length||0,!l.close)continue;t.hasOwnProperty(l.marker)||(t[l.marker]=[-1,-1,-1,-1,-1,-1]);const u=t[l.marker][(l.open?3:0)+l.length%3];let c=r-o[r]-1,d=c;for(;c>u;c-=o[c]+1){const h=e[c];if(h.marker===l.marker&&h.open&&h.end<0){let m=!1;if((h.close||l.open)&&(h.length+l.length)%3===0&&(h.length%3!==0||l.length%3!==0)&&(m=!0),!m){const f=c>0&&!e[c-1].open?o[c-1]+1:0;o[s]=s-c+f,o[c]=f,l.open=!1,h.end=s,h.close=!1,d=-1,a=-2;break}}}d!==-1&&(t[l.marker][(l.open?3:0)+(l.length||0)%3]=d)}}function K2(e){const t=e.tokens_meta,n=e.tokens_meta.length;jl(e.delimiters);for(let r=0;r<n;r++)t[r]&&t[r].delimiters&&jl(t[r].delimiters)}function Q2(e){let t,n,r=0;const a=e.tokens,o=e.tokens.length;for(t=n=0;t<o;t++)a[t].nesting<0&&r--,a[t].level=r,a[t].nesting>0&&r++,a[t].type==="text"&&t+1<o&&a[t+1].type==="text"?a[t+1].content=a[t].content+a[t+1].content:(t!==n&&(a[n]=a[t]),n++);t!==n&&(a.length=n)}const na=[["text",C2],["linkify",T2],["newline",I2],["escape",D2],["backticks",_2],["strikethrough",Oc.tokenize],["emphasis",Mc.tokenize],["link",M2],["image",L2],["autolink",G2],["html_inline",U2],["entity",Y2]],ra=[["balance_pairs",K2],["strikethrough",Oc.postProcess],["emphasis",Mc.postProcess],["fragments_join",Q2]];function er(){this.ruler=new Ie;for(let e=0;e<na.length;e++)this.ruler.push(na[e][0],na[e][1]);this.ruler2=new Ie;for(let e=0;e<ra.length;e++)this.ruler2.push(ra[e][0],ra[e][1])}er.prototype.skipToken=function(e){const t=e.pos,n=this.ruler.getRules(""),r=n.length,a=e.md.options.maxNesting,o=e.cache;if(typeof o[t]<"u"){e.pos=o[t];return}let s=!1;if(e.level<a){for(let l=0;l<r;

39l++)if(e.level++,s=n[l](e,!0),e.level--,s){if(t>=e.pos)throw new Error("inline rule didn't increment state.pos");break}}else e.pos=e.posMax;s||e.pos++,o[t]=e.pos};er.prototype.tokenize=function(e){const t=this.ruler.getRules(""),n=t.length,r=e.posMax,a=e.md.options.maxNesting;for(;e.pos<r;){const o=e.pos;let s=!1;if(e.level<a){for(let l=0;l<n;l++)if(s=t[l](e,!1),s){if(o>=e.pos)throw new Error("inline rule didn't increment state.pos");break}}if(s){if(e.pos>=r)break;continue}e.pending+=e.src[e.pos++]}e.pending&&e.pushPending()};er.prototype.parse=function(e,t,n,r){const a=new this.State(e,t,n,r);this.tokenize(a);const o=this.ruler2.getRules(""),s=o.length;for(let l=0;l<s;l++)o[l](a)};er.prototype.State=Xn;function J2(e){const t={};e=e||{},t.src_Any=Sc.source,t.src_Cc=jc.source,t.src_Z=Cc.source,t.src_P=fo.source,t.src_ZPCc=[t.src_Z,t.src_P,t.src_Cc].join("|"),t.src_ZCc=[t.src_Z,t.src_Cc].join("|");const n="[><｜]";return t.src_pseudo_letter="(?:(?!"+n+"|"+t.src_ZPCc+")"+t.src_Any+")",t.src_ip4="(?:(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\\.){3}(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)",t.src_auth="(?:(?:(?!"+t.src_ZCc+"|[@/\\[\\]()]).)+@)?",t.src_port="(?::(?:6(?:[0-4]\\d{3}|5(?:[0-4]\\d{2}|5(?:[0-2]\\d|3[0-5])))|[1-5]?\\d{1,4}))?",t.src_host_terminator="(?=$|"+n+"|"+t.src_ZPCc+")(?!"+(e["---"]?"-(?!--)|":"-|")+"_|:\\d|\\.-|\\.(?!$|"+t.src_ZPCc+"))",t.src_path="(?:[/?#](?:(?!"+t.src_ZCc+"|"+n+`|[()[\\]{}.,"'?!\\-;]).|\\[(?:(?!`+t.src_ZCc+"|\\]).)*\\]|\\((?:(?!"+t.src_ZCc+"|[)]).)*\\)|\\{(?:(?!"+t.src_ZCc+'|[}]).)*\\}|\\"(?:(?!'+t.src_ZCc+`|["]).)+\\"|\\'(?:(?!`+t.src_ZCc+"|[']).)+\\'|\\'(?="+t.src_pseudo_letter+"|[-])|\\.{2,}[a-zA-Z0-9%/&]|\\.(?!"+t.src_ZCc+"|[.]|$)|"+(e["---"]?"\\-(?!--(?:[^-]|$))(?:-*)|":"\\-+|")+",(?!"+t.src_ZCc+"|$)|;(?!"+t.src_ZCc+"|$)|\\!+(?!"+t.src_ZCc+"|[!]|$)|\\?(?!"+t.src_ZCc+"|[?]|$))+|\\/)?",t.src_email_name='[\\-;:&=\\+\\$,\\.a-zA-Z0-9_][\\-;:&=\\+\\$,\\"\\.a-zA-Z0-9_]*',t.src_xn="xn--[a-z0-9\\-]{1,59}",t.src_domain_root="(?:"+t.src_xn+"|"+t.src_pseudo_letter+"{1,63})",t.src_domain="(?:"+t.src_xn+"|(?:"+t.src_pseudo_letter+")|(?:"+t.src_pseudo_letter+"(?:-|"+t.src_pseudo_letter+"){0,61}"+t.src_pseudo_letter+"))",t.src_host="(?:(?:(?:(?:"+t.src_domain+")\\.)*"+t.src_domain+"))",t.tpl_host_fuzzy="(?:"+t.src_ip4+"|(?:(?:(?:"+t.src_domain+")\\.)+(?:%TLDS%)))",t.tpl_host_no_ip_fuzzy="(?:(?:(?:"+t.src_domain+")\\.)+(?:%TLDS%))",t.src_host_strict=t.src_host+t.src_host_terminator,t.tpl_host_fuzzy_strict=t.tpl_host_fuzzy+t.src_host_terminator,t.src_host_port_strict=t.src_host+t.src_port+t.src_host_terminator,t.tpl_host_port_fuzzy_strict=t.tpl_host_fuzzy+t.src_port+t.src_host_terminator,t.tpl_host_port_no_ip_fuzzy_strict=t.tpl_host_no_ip_fuzzy+t.src_port+t.src_host_terminator,t.tpl_host_fuzzy_test="localhost|www\\.|\\.\\d{1,3}\\.|(?:\\.(?:%TLDS%)(?:"+t.src_ZPCc+"|>|$))",t.tpl_email_fuzzy="(^|"+n+'|"|\\(|'+t.src_ZCc+")("+t.src_email_name+"@"+t.tpl_host_fuzzy_strict+")",t.tpl_link_fuzzy="(^|(?![.:

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l.replace("%TLDS%",t.src_tlds)}t.email_fuzzy=RegExp(r(t.tpl_email_fuzzy),"i"),t.link_fuzzy=RegExp(r(t.tpl_link_fuzzy),"i"),t.link_no_ip_fuzzy=RegExp(r(t.tpl_link_no_ip_fuzzy),"i"),t.host_fuzzy_test=RegExp(r(t.tpl_host_fuzzy_test),"i");const a=[];e.__compiled__={};function o(l,u){throw new Error('(LinkifyIt) Invalid schema "'+l+'": '+u)}Object.keys(e.__schemas__).forEach(function(l){const u=e.__schemas__[l];if(u===null)return;const c={validate:null,link:null};if(e.__compiled__[l]=c,X2(u)){ev(u.validate)?c.validate=sv(u.validate):Nl(u.validate)?c.validate=u.validate:o(l,u),Nl(u.normalize)?c.normalize=u.normalize:u.normalize?o(l,u):c.normalize=Cl();return}if(Z2(u)){a.push(l);return}o(l,u)}),a.forEach(function(l){e.__compiled__[e.__schemas__[l]]&&(e.__compiled__[l].validate=e.__compiled__[e.__schemas__[l]].validate,e.__compiled__[l].normalize=e.__compiled__[e.__schemas__[l]].normalize)}),e.__compiled__[""]={validate:null,normalize:Cl()};const 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40
41---
42
43## ABOUT ICS.AI
44
45ICS.AI is one of the UK's fastest-growing AI companies, founded in 2018 with the mission "Transforming lives through AI." The company specialises in conversational AI for the public sector — primarily Local Government, Education, and Health.
46
47**Key credentials:**
48- Founding members of the **Microsoft AI Inner Circle** partner programme
49- Built on the **Microsoft ecosystem with Azure AI Foundry** — UK-hosted, enterprise-grade infrastructure
50- The SMART: platform provides the AI front door deployment for **62% of UK councils** that have adopted "front door" AI
51- **11 million+** real-world AI interactions processed across UK councils
52- **600,000+** unique users on the SMART: platform
53- **95%** success rate — AI assistants consistently deliver at or above human parity performance
54- **4,500+** pre-trained sector-specific topics
55- **12** SMART: Copilots available across different use cases
56- **3 patents pending** (European, PCT, US)
57- **93%** customer satisfaction across deployed services
58- **90%+** competitive win rate when evaluated against alternatives
59- Bootstrapped — no venture capital. Sustainable, profitable growth since founding
60- Available via **G-Cloud 15** (listed across 7 sectors with 269 products) for compliant procurement
61- Referenced in the **House of Lords** by Lord Holmes of Richmond and cited in **Parliament** by Luke Murphy MP
62- EY Entrepreneur of the Year shortlisted (CEO Martin Neale)
63
64**Leadership team:**
65- **Martin Neale** — CEO & Founder. Built the platform from inception in 2018.
66- **Tim Irons** — CFO. Deloitte-trained finance leader.
67- **Neil Howell** — COO. Founding member, oversees delivery and governance.
68- **Dr. Crispin Bloomfield** — CESO. Former Microsoft education strategist.
69- **Rahim Bayjou** — CTO. Leads product and engineering strategy.
70- **Fiona Watson** — CMO. 20+ years in brand, content, and growth strategy.
71- **Dwayne Johnson** — CLGO. Former council Chief Executive with 40 years' experience.
72- **Andrew Smith** — CCO. Commercial leader in Microsoft-aligned AI solutions.
73- **Rob Donnelly** — Non-Executive Director. Former Leader of Basingstoke Council.
74
75**Awards won:**
76- Socitm Awards 2025 — Winner, Partner and Customer Collaboration (ICS.AI & Derby City Council)
77- National AI Awards 2024 — Highly Commended, Best Application of AI in Public Sector (ICS.AI & Derby City Council)
78- iESE Awards — Winner, AI Innovation in Local Government (Derby City Council)
79- APSE Awards — Overall Council of the Year for Service Delivery (Renfrewshire Council)
80- COSLA Awards 2025 — Leading Innovation Award (Renfrewshire Council)
81- Scottish Public Service Awards 2025 — Digital Public Services Award (Renfrewshire Council)
82- British Data Awards 2026 — Finalist, Data-Driven Public Sector Innovation (ICS.AI)
83
84---
85
86## THE LGR CONTEXT
87
88Around 200 councils across 21 county areas in England are reorganising into new unitary authorities serving 20 million residents. Estimated cost: £30M per area. Government capacity funding: just £900K each. This is a five-year job on a two-year deadline.
89
90The government mandate is "safe and legal" — but that's the floor, not the ceiling. Financial viability requires genuine transformation during the shadow period, not after it.
91
92**Key challenges every LGR area faces:**
93- Officers twin-hatting between predecessor and shadow authority work, manually learning unfamiliar systems, policies, and terminology
94- The "Day One veneer" problem — new branding masking old wiring, with years of transformation ahead
95- Shadow AI risk — over 70% of UK employees use unapproved consumer AI tools, creating GDPR and data governance risks
96- Capacity constraints — simultaneous work across dozens of workstreams (contract review, policy harmonisation, asset mapping, budget aggregation, TUPE analysis, etc.)
97- Financial risk — Somerset Council requested exceptional financial support within 7 months of vesting day, forced into a £30–40M restructuring programme
98
99---
100
101## THE SMART: DAY ONE LGR ACCELERATOR
102
103The Accelerator is a modular AI platform with **four components** that compress months of work into days. It works alongside existing strategic partners or independently — amplifying capacity, not replacing relationships. Each component delivers standalone value, and they share the same Service Graph and Digital Dome governance when combined.
104
105### Component 1: SMART: LGR Front Door (For Citizens, Businesses & Partners)

106**One council, one answer. One front door, many back ends.**
107
108A unified, conversational AI engagement layer across **five channels**: AI-first website, phone (the "Golden Number"), web chat, email triage, and SMS. It deploys during the shadow period as the "Intelligent Shield" — providing early reassurance, absorbing query surges, and becoming the permanent digital front door after vesting day.
109
110Key capabilities:
111- **AI-First Website** — The AI IS the website. Conversational service journeys with intelligent form pre-fill and payment.
112- **Phone AI (Golden Number)** — Single natural-language phone number replacing all legacy switchboard numbers. 96% routing accuracy. Handles 60% of council demand.
113- **Web Chat, Email Triage & SMS** — Real-time chat, automated email classification and routing, outbound SMS for notifications.
114- **Postcode-aware routing with temporal awareness** — Residents in former District A get District A answers today, unified answers after vesting day.
115- **Semantic mapping** — "Bulky waste collection" = "large item uplift." Automatic cross-council terminology translation.
116- **Friction Heat Map** — Aggregates resident interactions to reveal where legacy fragmentation causes frustration, guiding backend harmonisation priorities.
117- **Zero GDPR complexity** — During shadow period, ingests only public-domain data (published policies, fee schedules, legacy websites).
118- **Human handoff** — Complex cases, vulnerable residents, safeguarding concerns always escalated. Context preserved on transfer.
119
120### Component 2: SMART: Workforce AI (For Council Staff)
121**Accelerate organisational redesign. Land a transformed workforce.**
122
123Helps merge multiple councils by reconciling different job titles, pay grades, terms and conditions. Combined with expert organisational design capabilities, it accelerates workforce harmonisation from the outset — reducing equal pay risk.
124
125Key capabilities:
126- **Workforce data reconciliation** — AI-powered reconciliation of inconsistent job titles, terms, pay levels, spans of control across all predecessors. Months compressed to weeks.
127- **Organisational design acceleration** — Rapidly model "to-be" workforce structures with expert partners.
128- **Cross-council knowledge navigation** — "How does District B handle housing allocations?" Instant, grounded answers from actual policy with source citations.
129- **Document drafting** — Committee papers, transition briefings, policy summaries drafted with AI assistance.
130- **Staff FAQ** — Officers' transition questions (TUPE rights, reporting line changes) answered 24/7 from published HR guidance.
131- **Shadow AI prevention** — Governed enterprise AI through the Digital Dome. Better than ChatGPT. Auditable. Makes Shadow AI unnecessary.
132
133### Component 3: SMART: LGR Command Workbench (For the Programme Team)
134**Five tools. AI Native team. Safe, legal and financially viable from Day One.**
135
136Two halves of one solution: five integrated AI tools configured for LGR, AND a six-week AI Native education programme. Without structured education, AI adoption plateaus at 15–25%. With the Workbench, teams reach 70–90% value capture.
137
138The five tools:
1391. **SMART: LGR Command Portal** — Purpose-built lifecycle management for Contracts, Finance, DDaT, HR, and Property.
1402. **ICS.AI's SMART: Workforce AI** — Internal knowledge and operations engine.
1413. **Claude** — Document processing with precision. Reads complex structures, validates data, formats outputs.
1424. **ChatGPT** — Research and cross-validation. Legislation, precedent, scenario analysis.
1435. **Gemini** — Visual intelligence. Floor plans, org charts, process diagrams, scanned records.
144
145The AI Native Education Programme:
146- Weeks 1–2: Foundations across all five tools
147- Weeks 3–4: Role-specific applied skills
148- Weeks 5–6: Advanced practice and AI Champion certification
149- Ongoing: Weekly drop-in clinics and embedded support
150- AI Champions embedded in every workstream as permanent multipliers
151
152**ROI: £320K investment → £2.9M central value = 9.1x ROI. Compresses 20.0 FTE-years into 4.3 FTE-years.**
153
154Enterprise security: Microsoft Entra ID with enforced MFA. 100% UK Data Residency on Azure UK South. Every AI answer includes strict source citation.
155
156### Component 4: SMART: AI Application Forge (For the Digital Estate)
157**A unified digital estate, not a veneer.**
158
159Uses coordinated AI Swarms to move rapidly to a transformed digital estate — removing duplicate applications, eliminating years of costly rationalisation, and building modern replacements at machine speed.
160
161Key capabilities:
162- **Coordinated Digital Swarms** — Specialised AI agents (Code Generator, Test Engineer, UI Designer, Security Auditor) execute the full software lifecycle in parallel.
163- **SMART: Master Application Template** — Every app inherits consistent branding, accessibility, security. Eliminates up to 60% of conventional dev effort.
164- **Human-in-the-Loop Gates** — No build starts without human-approved blueprints. No deployment without human review.
165- **Semantic crawling** — Swarms crawl all predecessor public digital estates, recognise different terminology, build the Service Graph.
166- **Management Swarm** — Post-vesting, automatically detects legacy system retirement and remaps integrations.
167
168---
169
170## THE SERVICE GRAPH
171
172The structured representation of every service, policy, process, fee, and rule across all predecessor councils. Built by the Forge through semantic crawling. Powers both the Front Door (what residents are told) and Workforce AI (what staff know). Updated once, consistent everywhere. Eliminates the most dangerous drift: residents being told one thing and staff knowing another.
173
174---
175
176## THE DIGITAL DOME (Governance)
177
178The governance layer wrapping every AI interaction. "No autonomy without control."
179- **Granular permissions & ethical walls** — AI agents only access authorised data. Children's services invisible to revenue collection AI.
180- **Immutable audit logging & kill switches** — Every interaction logged. Instant kill switches for any AI agent.
181- **Compliance validation** — Responses checked against regulatory requirements before delivery.
182- **Escalation rules** — AI knows when to stop. Safeguarding, complex legal, complaints always escalated.
183- **Shadow AI prevention** — The governed alternative that makes consumer AI unnecessary.
184
185---
186
187## DEPLOYMENT TIMELINE
188
189All four elements deploy BEFORE Vesting Day. Nothing launches cold.
190
191- **Phase A (Decision Day + 4–8 weeks):** Initial deployment. Transition front door, implementation team tools, semantic crawling begins, education programme starts.
192- **Phase B (Shadow Period):** Full operational deployment. All elements active. Glide-path testing with real residents. AI Champions certified.
193- **Phase C (Vesting Day):** Role expansion, not debut. All redirects live. Already tested with thousands of real interactions.

194- **Phase D (Post-Vesting):** Permanent infrastructure. Front Door becomes permanent digital front door. Workforce AI becomes permanent staff platform. Portal becomes knowledge infrastructure. Forge manages ongoing legacy retirement.
195
196---
197
198## CASE STUDIES
199
200### Derby City Council (Flagship — England)
201- **"Darcie"** — AI-powered assistant handling council tax, benefits, housing, waste, highways
202- **£12M+** savings identified across all departments
203- **1.4M** citizen enquiries handled annually
204- **2.9M+** total questions answered
205- **56%** call resolution rate (without human intervention)
206- **94%** reduction in misdirected calls
207- Referenced in the **House of Lords** by Lord Holmes of Richmond
208- Winner at iESE Awards, Socitm Awards 2025, Highly Commended at National AI Awards
209
210### Renfrewshire Council (Scotland)
211- **"Millie"** — First local authority in Scotland to deploy AI-powered phone services
212- **392,000+** resident calls handled
213- **40%** resolved without human intervention (original projection was 5–10%)
214- **~100,000** calls handled outside office hours
215- **24 weeks** from initiation to go-live
216- **£110,000** in direct savings delivered
217- Winner at APSE, COSLA 2025, Scottish Public Service Awards 2025
218
219---
220
221## LESSONS FROM PREVIOUS LGR
222
223### North Yorkshire
2248 websites, 11,211 pages, 720,000+ annual calls, 580 IT systems. Scrutiny committee recommended future reorganisations adopt a "glide path" approach with pre-vesting testing.
225
226### Cumberland
227"Surface dressing" — new frontend for 20% of content, legacy pages for the rest. Staff navigated unfamiliar systems with no AI support. Years later, still linking to former council websites.
228
229### Somerset
230Requested exceptional financial support within 7 months of vesting day. Could have faced a Section 114 bankruptcy warning. Forced into a £30–40M restructuring programme. Business case depended on savings to cover rising costs from genuine transformation, not just structural reorganisation.
231
232---
233
234## HOW WE WORK WITH YOU (5-Step Engagement)
235
2361. **30-Minute Briefing Call** — Focused call to understand your LGR area, timeline, priorities. No slides — just a conversation.
2372. **We Visit Your Team** — We come to you with a **working prototype** of your new council's AI front door (phone and web) and your SMART: LGR Command Workbench, already built with your predecessor councils' data. **No one else can do this.**
2383. **You Choose Your Elements** — One, some, or all. No obligation to buy the full platform.
2394. **Accelerated Assessment** — Detailed pricing, deployment plan, timeline, expected outcomes specific to your LGR area.
2405. **We Begin Work** — Deployment starts within weeks via G-Cloud 15. No lengthy procurement.
241
242---
243
244## PROCUREMENT
245
246All SMART: products are on **G-Cloud 15** — compliant procurement without full competitive tender.
247- **Continuing authority** (county reconstituted as unitary): Procurement authority carries forward.
248- **New authority** (shadow authority): Commissioned through joint committee, shadow authority budget, or lead council.
249- Funding options: Joint committee budget, lead council procurement, flexible capital receipts, shadow authority preparation budget.
250
251---
252
253## FAQ KNOWLEDGE
254
255**"Why not Microsoft Copilot or generic AI tools?"**
256Generic AI tools are not grounded in your council's services, policies, and processes. They cannot distinguish between predecessor councils' approaches. They have no governance for statutory authorities. They create Shadow AI risk rather than solving it.
257
258**"Why not a consultancy?"**
259Consultancies provide advice and project management but not permanent AI infrastructure. When the consultancy leaves, you have a static website and recommendations. The Accelerator IS the infrastructure — it stays, learns, evolves.
260
261**"We already have a strategic partner."**
262The Accelerator complements your existing strategic partner. Your partner brings programme management, organisational design expertise, and local knowledge. The Accelerator provides the AI infrastructure that multiplies their capacity. Many councils will use both together.
263
264**"What about GDPR during the shadow period?"**
265During the shadow period, all elements operate on publicly available information and published policies. No personal data sharing required. Zero GDPR complexity. Post-vesting, the new council is Data Controller and Digital Dome governance applies.
266
267**"Who controls the AI?"**
268The AI does not make decisions. It provides grounded, cited information for human decision-making. Every response includes source attribution. Escalation rules route complex queries to humans. Governing principle: no autonomy without control.
269
270---
271
272## CONTACT INFORMATION
273
274- **Phone:** 01256 403 800
275- **Email:** [email protected]
276- **Address:** Grove House, Lutyens Close, Basingstoke, Hampshire, RG24 8AG
277- **Website:** www.ics.ai (for information on other ICS.AI services beyond LGR)
278- **Booking:** Users can book a briefing call at /contact on this site
279
280---
281
282## BEHAVIOURAL RULES (CRITICAL — ALWAYS FOLLOW)
283
2841. **Always redirect to a briefing call** for: pricing questions, contract details, specific implementation timelines for a particular council, anything requiring a tailored proposal. Say something like: "For pricing and detailed proposals tailored to your LGR area, I'd recommend booking a 30-minute briefing call — we'll map the Accelerator to your specific situation. You can do that at the Contact page."
285
2862. **For questions about specific councils or existing ICS.AI projects:** Direct users to the official ICS.AI website at www.ics.ai, or suggest they ask about existing projects during a briefing call.
287
2883. **For pricing:** ALWAYS direct to a briefing call. Never quote specific prices. Say pricing is tailored to the LGR area (number of predecessors, digital estate scale, staff population, timeline).
289
2904. **For services outside what's on this site** (e.g., education, health, other industries): Direct users to the main ICS.AI website at www.ics.ai for information on those sectors.
291
2925. **Do NOT engage on random unrelated topics.** If the user asks something completely unrelated to LGR, AI, public services, or adjacent topics, politely redirect: "That's outside my area of expertise — I'm here to help with the SMART: Day One LGR Accelerator. Is there anything about LGR or the Accelerator I can help with?"
293
2946. **Adjacent topics are OK but redirect back.** If the user asks something generically relevant (e.g., "What does AI mean for HR?" or "What are the risks of AI in government?"), you can answer helpfully but always bring it back to how the Accelerator addresses that topic, and offer to discu

294ss further in a briefing.
295
2967. **Do NOT provide details that aren't listed in your knowledge.** If you don't know something specific, say so honestly and suggest the user reach out to ICS.AI for further discussions. Never fabricate statistics, case studies, or claims.
297
2988. **Technology stack:** If asked, confirm ICS.AI uses the **Microsoft ecosystem with Azure AI Foundry**. UK-hosted. Enterprise-grade.
299
3009. **Tone:** Professional, knowledgeable, helpful, and warm. Use UK English. Be concise but thorough. You represent ICS.AI — be confident in the evidence but never oversell.
301
30210. **Format responses** using clean markdown: **bold** for emphasis, ### for section headings when appropriate, and - for bullet points. Keep responses well-structured and easy to scan. Don't overuse headings for short answers.
303
30411. **Always ground answers in real data and evidence** from the knowledge above. Cite specific numbers, case studies, and facts where relevant.
305
30612. **CRITICAL — NEVER FABRICATE INFORMATION.** The current LGR programme applies to ENGLAND ONLY (21 county areas). Do NOT mention Wales, Welsh councils, Scottish LGR, or Northern Ireland LGR unless the user specifically asks — and if they do, clarify that the current LGR programme and this website focus on England. The only named council case studies you may reference are Derby City Council and Renfrewshire Council. Do NOT invent or name any other councils, projects, statistics, or deployments. If asked about councils you don't have information on, say: "I can share details about our Derby City Council and Renfrewshire Council deployments. For information on other councils using the SMART: platform, visit www.ics.ai or ask during a briefing call."
307
30813. **NEVER generate lists of councils, regions, or areas** that aren't explicitly in your knowledge base. The 21 LGR county areas listed on the contact form are: Buckinghamshire, Cambridgeshire, Cumbria, Devon, Dorset, East Sussex, Essex, Gloucestershire, Hampshire, Hertfordshire, Kent, Lancashire, Leicestershire, Lincolnshire, Norfolk, North Yorkshire, Nottinghamshire, Oxfordshire, Suffolk, Surrey, West Sussex. Do NOT add to this list or speculate about other areas.
309
31014. **When uncertain, say so.** It is far better to say "I don't have specific information on that — I'd recommend discussing it in a briefing call" than to generate plausible-sounding but fabricated content.`;function _v(e){return e==="/"||e===""?{context:"the SMART: Day One LGR Accelerator homepage",systemAddition:'The user is on the homepage. This page presents the overall value proposition: around 200 councils across 21 county areas reorganising, the government mandate of "safe and legal" being the floor not the ceiling, and the Accelerator helping councils reach safe, legal AND financially viable from Day One. It shows the four components (SMART: LGR Front Door, SMART: Workforce AI, SMART: LGR Command Workbench, SMART: AI Application Forge), the 5-step engagement process (briefing call → on-site visit with working prototype → choose elements → accelerated assessment → begin work), credibility stats (£12M savings at Derby, 2.9M enquiries, 62% market share, G-Cloud 15), lessons from previous LGR (North Yorkshire, Cumberland, Somerset), and two executive video briefings (business and technical). Help them understand why speed matters, what makes the Accelerator unique (especially the working prototype visit), and guide them toward booking a briefing call.',suggestions:["What is the SMART: Day One Accelerator?","How does it compare to traditional consultancy?","What evidence do you have from other councils?"]}:e==="/the-challenge"?{context:"the LGR Challenge page",systemAddition:`The user is exploring the challenges facing LGR councils. This page covers: (1) The twin-hatting trap — staff doing day jobs AND building a new council with no AI support, learning 6 predecessor councils' systems manually. (2) The "Day One veneer" problem — new branding masking old wiring, with years of transformation ahead. Case studies show the cumulative cost. (3) Shadow AI risk — 70% of UK employees use unapproved consumer AI, creating GDPR risks. Banning doesn't work; providing a governed alternative does (the Digital Dome). (4) Capacity constraints — simultaneous work across dozens of workstreams with officers already stretched. (5) Financial risk — Somerset requested exceptional financial support within 7 months of vesting, forced into £30–40M restructuring. Help them understand these are solvable problems and guide toward the Accelerator as the solution.`,suggestions:['What is the "Day One veneer" problem?',"What happened in previous LGR reorganisations?","What is the Shadow AI risk?"]}:e==="/smart-accelerator"?{context:"the SMART: Day One Accelerator solution overview",systemAddition:'The user is viewing the full solution overview. This page shows: (1) Acceleration comparison bars showing what the Accelerator compresses (resident front door, GDPR compliance, staff knowledge bridge, contract review, policy harmonisation, website building, etc.). (2) The Service Graph — one knowledge base powering both resident-facing and staff-facing services, updated once, consistent everywhere. (3) The Digital Dome governance layer — granular permissions, immutable audit logs, kill switches, compliance validation, escalation rules. (4) "What It IS vs What It Is NOT" comparison table. (5) Four risks and four answers (untested launch, staff learning curve, Shadow AI/GDPR, Day One veneer). (6) Detailed cards for all four components with highlights. (7) The key message: not a transition cost but permanent infrastru

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313ined. The evidence suggests that a different approach to the transition period can materially improve financial outcomes."})]}),i.jsxs("div",{className:"grid grid-cols-1 md:grid-cols-2 gap-8 mb-12",children:[i.jsxs("div",{className:"bg-off-white rounded-2xl p-8 border-2 border-light-grey relative",children:[i.jsx("div",{className:"absolute -top-3 left-6 bg-medium-grey text-white font-inter font-bold text-xs uppercase tracking-wider px-4 py-1.5 rounded-full",children:"Traditional Approach"}),i.jsxs("div",{className:"space-y-5 mt-4",children:[i.jsxs("div",{children:[i.jsx("div",{className:"text-medium-grey font-inter text-xs uppercase tracking-wider mb-1",children:"Total Cost"}),i.jsx("div",{className:"font-georgia font-bold text-charcoal text-3xl",children:"£11–28M"}),i.jsx("div",{className:"text-dark-grey font-inter text-sm",children:"per LGR area"})]}),i.jsxs("div",{className:"border-t border-light-grey pt-4",children:[i.jsx("div",{className:"text-medium-grey font-inter text-xs uppercase tracking-wider mb-1",children:"Break-Even"}),i.jsx("div",{className:"font-georgia font-bold text-charcoal text-2xl",children:"Year 3–5"}),i.jsx("div",{className:"text-dark-grey font-inter text-sm",children:"if savings materialise"})]}),i.jsxs("div",{className:"border-t border-light-grey pt-4",children:[i.jsx("div",{className:"text-medium-grey font-inter text-xs uppercase tracking-wider mb-1",children:"Savings Guarantee"}),i.jsx("div",{className:"font-georgia font-bold text-warm-amber text-2xl",children:"None"}),i.jsx("div",{className:"text-dark-grey font-inter text-sm",children:"No contractual commitment to outcomes"})]}),i.jsxs("div",{className:"border-t border-light-grey pt-4",children:[i.jsx("div",{className:"text-medium-grey font-inter text-xs uppercase tracking-wider mb-1",children:"Track Record"}),i.jsx("div",{className:"text-dark-grey font-inter text-sm leading-relaxed",children:"6 of 9 councils since 2019 required emergency financial support. Somerset: £30–40M restructuring within 7 months. Approaching £300M combined emergency supp

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AI now offers a different approach to the same timeline."`}),i.jsx("p",{className:"text-dark-grey font-inter text-sm text-center mt-3",children:"— Martin Neale, CEO, ICS.AI"})]}),i.jsx("section",{className:"gradient-dark py-16 md:py-20",children:i.jsxs("div",{className:"max-w-[1200px] mx-auto px-4 md:px-6",children:[i.jsxs("div",{className:"text-center mb-10",children:[i.jsx("p",{className:"text-signal-green font-inter font-semibold text-sm uppercase tracking-[0.15em] mb-3",children:"EXECUTIVE BR

313IEFINGS"}),i.jsx("h2",{className:"font-georgia font-bold text-white text-2xl sm:text-3xl md:text-4xl mb-4",children:"An executive briefing on the Accelerator"}),i.jsx("p",{className:"text-light-grey/80 font-inter text-base md:text-lg leading-relaxed max-w-2xl mx-auto",children:"A concise overview of how the SMART: LGR Accelerator helps you reach safe, legal and financially viable from Day One. Full video briefings are available during your 30-minute call or on-site visit."})]}),i.jsxs("div",{className:"grid grid-cols-1 md:grid-cols-2 gap-6 max-w-5xl mx-auto",children:[i.jsx(_l,{title:"The SMART: Day One LGR Accelerator",audience:"For Leaders, Programme Directors & Technology Teams",description:`Why the government mandate of "safe and legal" isn't enough — and how the Accelerator helps you reach safe, legal and financially viable from Day One. The business case, the architecture, and the acceleration.`,icon:jn,videoUrl:"https://www.youtube.com/embed/1_hFotg4zho"}),i.jsx(_l,{title:"The SMART: LGR Workbench",audience:"For Programme Teams, SROs & Transformation Leads",description:"The operational engine behind accelerated LGR delivery. Replace fragmented spreadsheets with a governed AI-enabled platform for data collection, baselining, readiness and transformation.",icon:bt,videoUrl:"https://www.youtube.com/embed/p_AGuD6aw8c"})]})]})}),i.jsxs(H,{bg:"bg-off-white",children:[i.jsxs("div",{className:"text-center mb-10",children:[i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl sm:text-3xl md:text-4xl mb-4",children:"Four questions every new council needs to address"}),i.jsx("p",{className:"text-dark-grey font-inter text-base md:text-lg leading-relaxed mb-4",children:"Reorganisation creates consistent challenges: how residents experience the transition, how staff work across unfamiliar councils, how the programme team manages the volume of work, and how digital services are unified. Each component of the Accelerator is designed to address one of these areas."}),i.jsx("p",{className:"text-dark-grey font-inter text-base md:text-lg leading-relaxed",children:"Start with the area that matters most to your council. Each component delivers standalone value — and if you expand later, they share the same foundations with no integration overhead."})]}),i.jsx("div",{className:"grid grid-cols-1 md:grid-cols-2 gap-6",children:Wv.map(e=>i.jsxs("div",{className:"bg-white rounded-xl shadow-[0_2px_8px_rgba(13,27,42,0.08)] hover:shadow-[0_8px_24px_rgba(13,27,42,0.15)] hover:-translate-y-1 transition-all duration-300 p-6",children:[i.jsx("p",{className:"font-georgia font-bold text-deep-teal text-base md:text-lg mb-4 leading-snug min-h-[3.5rem]",children:e.challenge}),i.jsxs("div",{className:"flex items-start gap-4 mb-4",children:[i.jsx("div",{className:"w-12 h-12 rounded-full gradient-dark flex items-center justify-center shrink-0",children:i.jsx(e.icon,{className:"w-6 h-6 text-white"})}),i.jsxs("div",{children:[i.jsx("h3",{className:"font-inter font-semibold text-lg text-charcoal",children:e.name}),i.jsx("span",{className:"inline-block text-xs font-inter font-medium text-deep-teal bg-[#E6F5F5] px-2.5 py-0.5 rounded-full mt-1",children:e.audience})]})]}),i.jsx("p",{className:"text-dark-grey text-sm font-inter leading-relaxed mb-5 min-h-[7.5rem] md:min-h-[9rem]",children:e.desc}),i.jsx("div",{className:"bg-deep-navy rounded-lg p-4 mb-4",children:i.jsx(yo,{label:e.barLabel,withoutLabel:e.barWithout,withLabel:e.barWith,targetPercent:e.barPercent})}),i.jsxs(oe,{to:e.to,className:"text-deep-teal font-inter font-semibold text-sm hover:underline inline-flex items-center gap-1",children:["Learn how it works ",i.jsx(Je,{className:"w-4 h-4"})]})]},e.to))})]}),i.jsx("section",{className:"gradient-primary py-16 md:py-20",children:i.jsxs("div",{className:"max-w-[1200px] mx-auto px-4 md:px-6",children:[i.jsxs("h2",{className:"font-georgia font-bold text-white text-2xl sm:text-3xl md:text-4xl mb-4 text-center",children:['The mandate is "safe and legal." The goal is safe, legal ',i.jsx("em",{children:"and financially viable."})]}),i.jsx("p",{className:"text-white/70 font-inter text-base md:text-lg text-center mb-10 max-w-3xl mx-auto",children:"Every programme will achieve safe and legal — that is the baseline. Financial viability requires meaningful transformation during the shadow period, not after it. The Accelerator is designed to support that work."}),i.jsx("div",{className:"grid grid-cols-1 md:grid-cols-2 lg:grid-cols-4 gap-8",children:[{title:'From "safe and legal" to financially viable.',body:"The mandate ensures Day One continuity, but not long-term sustainability. The Accelerator supports the work of building foundations across contracts, budgets, workforce, and digital estate — the areas where identified savings are typically found. Evidence from recent reorganisations suggests that entering operation without these foundations carries significant financial risk."}

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313),i.jsxs("div",{className:"mt-12 bg-gradient-to-r from-deep-navy to-navy-mid rounded-2xl p-8 md:p-10 relative overflow-hidden",children:[i.jsx("div",{className:"absolute inset-0 opacity-10",children:i.jsxs("svg",{className:"w-full h-full",viewBox:"0 0 800 200",preserveAspectRatio:"none",children:[i.jsx("path",{d:"M0,100 Q200,30 400,100 T800,80",stroke:"#00C48C",strokeWidth:"2",fill:"none"}),i.jsx("path",{d:"M0,150 Q200,80 400,120 T800,100",stroke:"#0D9DA0",strokeWidth:"1.5",fill:"none"})]})}),i.jsxs("div",{className:"relative flex flex-col md:flex-row items-center gap-8",children:[i.jsxs("div",{className:"flex-1",children:[i.jsxs("div",{className:"inline-flex items-center gap-2 bg-signal-green/20 rounded-full px-3 py-1 mb-4",children:[i.jsx(br,{className:"w-4 h-4 text-signal-green"}),i.jsx("span",{className:"text-signal-green font-inter font-semibold text-xs uppercase tracking-wider",children:"Unique to ICS.AI"})]}),i.jsx("h3",{className:"font-georgia font-bold text-white text-xl md:text-2xl lg:text-[28px] leading-snug mb-4",children:"We'll bring a working prototype of your new council's AI front door to your first meeting."}),i.jsx("p",{className:"text-light-grey/80 font-inter text-base leading-relaxed mb-2",children:"Before you sign anything, we'll show your leadership team a live, working demonstration of how residents will contact your new council — phone and web — with your predecessor councils' services already unified. 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The question is whether AI tools can meaningfully reduce the time it takes to navigate unfamiliar policies and processes across multiple predecessor councils."})]})]}),i.jsxs(H,{bg:"bg-off-white",children:[i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl sm:text-3xl md:text-4xl mb-6 text-center",children:'The "Day One veneer" — when new branding masks old wiring'}),i.jsxs("div",{className:"space-y-4 mb-8",children:[i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed",children:"For too many councils, Day One is when the real journey begins. You will have a shiny new council with new branding and a new front door — typically created by a veneer of new systems creating the illusion of a joined-up, transformed organisation. 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313VED CONSUMER AI TOOLS"})]}),i.jsxs("div",{className:"space-y-4",children:[i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed",children:"Staff working across incompatible legacy systems will reach for shortcuts. Consumer AI tools - ChatGPT, Gemini, Claude - are free, fast, and unmonitored."}),i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed",children:"For example, a housing officer might use a public AI tool to interpret case information, or a finance officer might explore budget scenarios using an external model. In both cases, entering sensitive or organisational data into uncontrolled systems creates clear GDPR and data security risks."}),i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed",children:"These are illustrative scenarios - but the underlying behaviour is already being observed across organisations."}),i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed font-semibold",children:"Experience suggests that restricting consumer AI use is difficult to enforce. Providing a governed, purpose-built alternative — one that is grounded in council data and fully auditable — offers a more practical path. That is the role of the Digital Dome governance layer."})]})]}),i.jsxs(H,{bg:"bg-off-white",children:[i.jsx("div",{className:"border-l-4 border-deep-teal bg-off-white rounded-r-xl p-6 mb-8",children:i.jsx("p",{className:"font-georgia italic text-charcoal text-lg md:text-xl leading-relaxed",children:'"Recent LGR councils consistently identify officer capacity as the most significant constraint during the shadow period."'})}),i.jsxs("div",{className:"space-y-4",children:[i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed",children:"The Implementation Plan demands simultaneous work across dozens of workstreams: contract review, policy harmonisation, asset mapping, budget aggregation, TUPE analysis, risk consolidation, regulatory compliance, committee papers, service mapping, communications, and more. Each workstream demands significant analytical input. The shadow period is typically 11–12 months."}),i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed",children:"A typical LGR area has thous

313ands of contracts across 5–8 predecessor councils. Thousands of policies using different terminology for the same services. Multiple budget structures. Different IT systems. Different HR terms."}),i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed",children:"Recent LGR programme teams have navigated this with the same officers simultaneously running predecessor services — a testament to their dedication, but also a clear indicator of where additional AI capacity would have the greatest impact."}),i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed font-semibold",children:"The opportunity is to provide the programme team with AI tools that can assist with contract analysis, policy comparison, and scenario modelling — freeing officers to focus on the judgements and decisions that require human expertise."})]})]}),i.jsx(H,{bg:"bg-white",children:i.jsxs(Fa,{children:[i.jsx("p",{className:"font-semibold text-base mb-2",children:"The financial risk is real"}),i.jsx("p",{className:"mb-2",children:"Somerset Council requested exceptional financial support within seven months of vesting day and could have faced a Section 114 notice — a legal declaration that a council cannot balance its budget. Somerset was forced into a £30–40 million restructuring programme to remain solvent, in part because their business case depended on savings to cover rising costs arising from genuine transformation, not just structural reorganisation."}),i.jsx("p",{className:"mb-2",children:"When structural changes are deferred until after vesting day, the results can be severe — leaving the new council to absorb the immediate shock of combined operational costs without the anticipated savings to survive the transition."}),i.jsx("p",{className:"font-semibold",children:"This is why the Accelerator is designed as transformation infrastructure, not just transition tooling. Every pound spent during the shadow period invests in permanent capability that helps deliver the savings the business case depends on."})]})}),i.jsx(tt,{headline:"Safe and legal is the floor, not the ceiling. The Accelerator is designed to build viability within the same timeline.",subtitle:"Four integrated AI components, each addressing a specific LGR challenge. Designed for rapid deployment within the shadow period so that transformation happens during the programme, not after it.",primaryCta:{label:"See the Accelerator",to:"/smart-accelerator"},secondaryCta:{label:"Book a Briefing",to:"/contact"}})]})}const qv=[{label:"Resident front door (Intelligent Shield)",without:"6–9 months, launched cold",withAcc:"Weeks, tested during shadow period",pct:15},{label:"GDPR compliance during Shadow Period",without:"Multi-council data sharing paralysis",withAcc:"Public-domain only. Zero GDPR complexity.",pct:20},{label:"Staff knowledge bridge",without:"Never done — officers left to figure it out",withAcc:"Live from week one",pct:8},{label:"Contract review (Contract Workbench)",without:"Weeks per council. Months total.",withAcc:"Hours. AI ingests, structures, cites sources.",pct:10},{label:"Policy harmonisation (Policy Comparator)",without:"Days per comparison. Manual spreadsheets.",withAcc:"Minutes. Semantic mapping handles terminology.",pct:12},{label:"Council tax harmonisation modelling",without:"Weeks of manual modelling",withAcc:"Overnight. Multiple scenarios.",pct:8},{label:"New council website (Digital Swarms)",without:"6–9 months CMS migration",withAcc:"Weeks. Swarms build in parallel.",pct:15},{label:"Digital estate mapping",without:"Months per council, often abandoned",withAcc:"Days. Swarms crawl, map, and structure.",pct:10},{label:"Backend harmonisation priorities",without:"Guesswork. Loudest voices win.",withAcc:"Friction Heat Map from resident interactions",pct:15},{label:"Committee paper drafting",without:"Days per paper",withAcc:"Hours per paper",pct:25}],$v=[["Modular — buy one component, some, or all four","An all-or-nothing platform you must adopt in full"],["AI that does the heavy lifting so officers do the thinking","A replacement for human judgement or professional expertise"],["A capacity multiplier deployed in weeks","A consultancy engagement that takes months and produces a report"],["Permanent infrastru

313cture for the new council","A transition cost to write off after vesting day"],["One platform with shared governance — expand with zero overhead","Four separate products bolted together"],["Deployed from Decision Day, tested during shadow period","A big-bang launch on vesting day"],["Governed enterprise AI with statutory-grade audit trails","Consumer AI repackaged for government"],["Built on evidence from 5 previous LGRs and 62% of UK councils that have adopted 'front door' AI","An untested proposition"],["Available via G-Cloud 15 — compliant procurement in weeks","A bespoke build requiring 6-month competitive tender"]],Uv=[{risk:"Untested launch",before:`Resident front door launched on Day One without pre-vesting testing — North Yorkshire's scrutiny committee recommended a "glide path" for future reorganisations.`,after:"Glide-path deployment. Every element tested during shadow period. Day One is a role expansion, not a debut.",border:"border-warm-amber"},{risk:"Staff learning curve",before:"Officers joining an unfamiliar organisation with no cross-council knowledge support. Recent LGR experience highlights a 3–6 month adjustment period.",after:"SMART: Workforce AI provides cross-council knowledge from week one. The knowledge bridge that helps officers navigate unfamiliar systems and policies from day one.",border:"border-warm-amber"},{risk:"Shadow AI / GDPR",before:"Research suggests over 70% of UK employees use unapproved consumer AI. If staff upload constituent data to public models to bypass legacy silos during LGR, this creates significant GDPR risk.",after:"The Digital Dome provides a safe, governed, legally compliant enterprise alternative — with immutable audit logs, kill switches, and ethical walls. Designed to make Shadow AI unnecessary.",border:"border-warm-amber"},{risk:'The "Day One veneer"',before:"A new council launches with unified branding and a single front door, but legacy complexity remains underneath. Without the foundations for delivering savings, the new authority may face the challenge of absorbing combined operational costs during the transition period.",after:"Genuine transformation during the shadow period. Not a veneer — a unified digital estate, harmonised workforce data, and robust baseline foundations. Land transformed, not just functioning.",border:"border-warm-amber"}],Hv=[{icon:qe,to:"/lgr-front-door",name:"SMART: LGR Front Door",audience:"FOR CITIZENS",desc:"The Intelligent Shield: a unified, conversational AI engagement layer across web, phone, web chat, email and SMS. One council, one answer. One front door, many back ends. 62% share of council AI phone platforms. 11 million real-world interactions. 93% customer satisfaction.",highlights:["Golden Number: single voice-routed phone line — £780K savings in month one","Five channels: AI-first website, phone, web chat, email triage, SMS","Zero GDPR complexity: public-domain data only during Shadow Period"]},{icon:Tt,to:"/workforce-ai",name:"SMART: Workforce AI",audience:"FOR STAFF",desc:"The element missing from every previous LGR. Every officer gets an enterprise AI assistant grounded in the Service Graph — navigating all predecessor councils' policies instantly. The Personal Command Portal scales analytical capacity to every officer, not just the core team. And critically: the transition investment IS the permanent infrastru

313cture. £19–30M five-year savings through natural attrition.",highlights:["Cross-council knowledge navigation: days of research → seconds","Personal Command Portal scales transition capacity to every officer","Permanent platform — the transition investment IS the new council's AI infrastructure"]},{icon:bt,to:"/transition-command",name:"SMART: LGR Command Workbench",audience:"FOR THE PROGRAMME TEAM",desc:"The programme team's central operating environment — replacing spreadsheet hell with a single application. Three integrated views: Data (centralised collection replacing manual RFIs), Baseline (progressive baseline building with confidence scoring from B0 to B4), and Optimise (opportunity identification and risk management). AI-assisted extraction from native source documents, 500+ preloaded safe-and-legal tasks, and a transformation pipeline that populates during the programme so the new council has a savings roadmap from Day One.",highlights:["Replaces manual spreadsheets consuming 85% of programme capacity with AI-powered central data store","500+ preloaded safe-and-legal tasks with built-in AI guidance on how to perform each one","After Vesting Day becomes the new council's centre for organisational knowledge and transformation"]},{icon:yt,to:"/application-forge",name:"SMART: AI Application Forge",audience:"FOR THE DIGITAL ESTATE",desc:"Don't build a veneer website over legacy wiring. The Forge builds a unified, intelligent digital estate — extracting capabilities from legacy applications, removing duplicates, and creating integrated platforms not constrained by legacy infrastructure.",highlights:["AI Swarms: remove years of costly rationalisation work","Unified estate from Day One — not a veneer with years of fixes ahead","Management Swarm: automatic legacy retirement without service disruption"]}];function Vv(){return i.jsxs(Se,{children:[i.jsx(et,{eyebrow:"THE SOLUTION",headline:"The SMART: Day One Accelerator",subtitle:"LGR done well lays the foundations for a safe and legal Day One. The Accelerator is designed to help deliver the components of a successful new council for the next decade. Four modular AI components that compress months of work into days — supporting transformation goals alongside your existing strategic partner or independently. Start where your need is greatest.",primaryCta:{label:"Book a Briefing",to:"/contact"},secondaryCta:{label:"View the Timeline",to:"/timeline"}}),i.jsx("section",{className:"gradient-dark py-16 md:py-20",children:i.jsxs("div",{className:"max-w-[1200px] mx-auto px-4 md:px-6",children:[i.jsx("h3",{className:"font-inter font-semibold text-white text-xl sm:text-2xl md:text-3xl mb-8",children:"What the Accelerator compresses"}),qv.map((e,t)=>i.jsx(yo,{label:e.label,withoutLabel:e.without,withLabel:e.withAcc,targetPercent:e.pct},t))]})}),i.jsxs(H,{bg:"bg-white",children:[i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl sm:text-3xl md:text-4xl mb-4 text-center",children:"One knowledge base. Two audiences. Zero contradictions."}),i.jsxs("div",{className:"grid grid-cols-1 lg:grid-cols-2 gap-8 mt-8",children:[i.jsxs("div",{className:"space-y-4",children:[i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed",children:'The Service Graph is the structured representation of every service, policy, process, fee, and rule across all predecessor councils in your LGR area. It is built by the SMART: AI Application Forge through semantic crawling of all predecessor digital estates — recognising that "bulky waste collection" in one district is "large item uplift" in another.'}),i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed",children:"It powers both the SMART: LGR Front Door (what residents are told) and SMART: Workforce AI (what staff know). When a transition decision is confirmed, it is updated in one place. Both audiences see the same truth, instantly."}),i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed font-semibold",children:"This eliminates the most dangerous drift in any reorganisation: residents being told one thing by the website and another by a staff member."})]}

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313i.jsxs("div",{className:`bg-navy-mid/50 border-l-4 ${e.border} rounded-r-xl p-6`,children:[i.jsx("h4",{className:"font-inter font-semibold text-white text-lg mb-3",children:e.risk}),i.jsxs("p",{className:"text-warm-amber text-sm font-inter mb-2",children:[i.jsx("span",{className:"font-semibold",children:"Before:"})," ",e.before]}),i.jsxs("p",{className:"text-signal-green text-sm font-inter",children:[i.jsx("span",{className:"font-semibold",children:"With Accelerator:"})," ",e.after]})]},t))})]})}),i.jsxs(H,{bg:"bg-off-white",children:[i.jsxs("div",{className:"text-center mb-8",children:[i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl sm:text-3xl md:text-4xl mb-4",children:"Four components — adopt the ones you need"}),i.jsx("p",{className:"text-dark-grey font-inter text-base md:text-lg leading-relaxed",children:"Each component delivers standalone value from day one. When you adopt more than one, they share the same Service Graph and Digital Dome governance — so expanding later requires no additional integration work."})]}),i.jsx("div",{className:"grid grid-cols-1 md:grid-cols-2 gap-6",children:Hv.map(e=>i.jsxs("div",{className:"bg-white rounded-xl shadow-sm p-6 hover:shadow-lg transition-shadow",children:[i.jsxs("div",{className:"flex items-start gap-4 mb-4",children:[i.jsx("div",{className:"w-12 h-12 rounded-full gradient-dark flex items-center justify-center shrink-0",children:i.jsx(e.icon,{className:"w-6 h-6 text-white"})}),i.jsxs("div",{children:[i.jsx("h3",{className:"font-inter font-semibold text-lg text-charcoal",children:e.name}),i.jsx("span",{className:"inline-block text-xs font-inter font-medium text-deep-teal bg-[#E6F5F5] px-2.5 py-0.5 rounded-full mt-1",children:e.audience})]})]}),i.jsx("p",{className:"text-dark-grey text-sm font-inter leading-relaxed mb-4",children:e.desc}),i.jsx("ul",{className:"space-y-2 mb-4",children:e.highlights.map((t,n)=>i.jsxs("li",{className:"flex items-start gap-2 text-sm font-inter text-charcoal",children:[i.jsx(ko,{className:"w-4 h-4 text-signal-green shrink-0 mt-0.5"})," ",t]},n))}),i.jsxs("div",{className:"flex gap-4",children:[i.jsxs(oe,{to:e.to,className:"text-deep-teal font-inter font-semibold text-sm hover:underline inline-flex items-center gap-1",children:["See the full acceleration story ",i.jsx(Je,{className:"w-4 h-4"})]}),i.jsxs(oe,{to:"/timeline",className:"text-medium-grey font-inter text-sm hover:text-deep-teal inline-flex items-center gap-1",children:["Deployment timeline ",i.jsx(Je,{className:"w-4 h-4"})]})]})]},e.to))})]}),i.jsxs(H,{bg:"bg-white",children:[i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl sm:text-3xl md:text-4xl mb-4 text-center",children:"Not a transition cost. Permanent infrastru

313cture."}),i.jsxs("div",{className:"space-y-4",children:[i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed",children:"Every pound spent during the shadow period invests in permanent capability — not a veneer that needs replacing:"}),i.jsxs("p",{className:"text-dark-grey font-inter text-base leading-relaxed",children:["The ",i.jsx("strong",{children:"SMART: LGR Front Door"})," becomes the permanent digital front door of the new council — not a temporary veneer over legacy wiring, but a genuine unified conversational AI engagement layer across web, phone, web chat, email and SMS that never stops learning. ",i.jsx("strong",{children:"SMART: Workforce AI"})," becomes the permanent staff AI platform, with harmonised workforce data and organisational design that eliminates years of post-vesting restructuring. The ",i.jsx("strong",{children:"SMART: LGR Command Workbench"})," transitions into the new council's knowledge infrastructure — the Portal preserves every contract, budget line, system, policy and property decision with full evidence trails, while every officer carries their AI Native capability into their permanent role. The investment carries forward: the skills serve the council for years to come. The ",i.jsx("strong",{children:"SMART: AI Application Forge"})," becomes the permanent digital estate management system — a unified, intelligent platform that extracts the capabilities from your legacy applications, not a veneer website with years of rationalisation ahead."]}),i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed font-semibold",children:"The SMART: approach is designed to help make LGR transformation goals achievable within the shadow period — freeing capacity to build a new council that is thriving and successful from Day One, not just functioning, safe and legal. Fully compliant and ready for rapid procurement via G-Cloud 15."})]})]}),i.jsx(tt,{headline:"See exactly when each element deploys — and why nothing launches cold on Vesting Day.",subtitle:"The deployment timeline shows every phase, every element, and every milestone.",primaryCta:{label:"View the Timeline",to:"/timeline"},secondaryCta:{label:"Book a Briefing",to:"/contact"}})]})}const Yv={"lgr-front-door":{eyebrow:"FOR CITIZENS, BUSINESSES & PARTNERS",headline:"SMART: LGR Front Door: A Unified Engagement Layer for Local Government Reorganisation",positioning:"One council, one answer. One front door, many back ends. The SMART: LGR Front Door is a unified, conversational AI engagement layer across web, phone, web chat, email and SMS that deploys early for reassurance, routes residents intelligently during transition, and becomes the permanent digital front door of the new council after vesting day. The resident experience is the organising principle: every design decision, every channel, every governance control exists to ensure that the person asking the question gets the right answer, first time.",withoutHeading:"Why the resident front door deserves early attention",withoutBody:["Many LGR programmes prioritise the website first. However, the phone channel often handles the most complex demand — from vulnerable residents, the elderly, and those who need reassurance during change. These are the residents most likely to contact the council on announcement day and vesting day.","Residents expect one council and one answer from announcement day. The reality of Local Government Reorganisation is multiple websites, multiple phone numbers, multiple terms for the same service, different policies by geography and years of legacy systems behind the scenes.","Consider a resident calling the new council to ask whether their child's SEND transport will continue after reorganisation. Without a unified front door, they may be directed between numbers and websites that don't yet reflect the new structure. This kind of experience — repeated across thousands of interactions — shapes public perception of the reorganisation and can undermine confidence in the new authority."],withoutCallout:"720,000 calls per year. 8 websites. 580 IT systems. O

313ne Day One.",withHeading:"The Glide Path: deploy early, widen progressively",withBody:["The SMART: LGR Front Door is designed to deploy during the Shadow Period — providing early reassurance to residents, absorbing the initial surge of queries, and delivering operational savings from the outset. It is a complete AI-native engagement platform that unifies the fragmented digital front door estate into one coherent system.","It sits above the legacy estate as an intelligent abstraction layer: one front door, many back ends. Every channel reads from the same knowledge, applies the same governance, and delivers the same quality of answer. During the shadow period, it widens — postcode-aware, temporally aware. A resident in the former District A area gets answers based on District A's current policies. It knows what's true today and what changes after vesting day.","On Day One, predecessor phone numbers and websites redirect to a front door that has already handled real conversations during the shadow period — a role expansion rather than a cold launch. The SMART: platform is widely deployed across UK local government, with a 62% share of council AI phone platforms, over 11 million real-world interactions processed, and 93% customer satisfaction across deployed services."],capabilities:[{name:"AI-First Website",desc:"An integrated approach where the AI and website share the same knowledge base, rules, and experience. Conversational service journeys with intelligent form pre-fill and payment — all within a single interaction."},{name:"Phone AI — The Golden Number",desc:"Addressing the channel where approximately 60% of council demand lands. A single natural-language phone number replaces legacy switchboard numbers. Residents describe what they need in their own words. Achieved 96% routing accuracy and £780K savings in month one in existing deployments."},{name:"Web Chat, Email Triage & SMS",desc:"Real-time web chat integrated with the Service Graph. Inbound emails classified, prioritised and routed automatically with AI-drafted replies. Outbound SMS for notifications, reminders, and two-way conversational messaging — particularly important for vulnerable residents."},{name:"Bypass multi-council GDPR paralysis",desc:"During the Shadow Period, predecessor councils remain legally distinct Data Controllers. The Front Door avoids this entirely by ingesting only public-domain data — published policies, fee schedules, legacy websites — triggering zero GDPR complexity."},{name:"Friction Heat Map",desc:'Stop guessing which legacy systems to consolidate first. The Front Door aggregates resident interactions into a "Friction Heat Map," revealing exactly where legacy fragmentation causes public frustration — so executives prioritise expensive backend harmonisation based on actual community impact.'},{name:"Postcode-aware routing with temporal awareness",desc:"A resident in the former District A area gets District A answers today, and unified answers after vesting day. The AI handles the complexity. The resident sees one council."},{name:"Semantic mapping across predecessor terminology",desc:`"Bulky waste collection" = "large item uplift." The resident doesn't need to know which council they used to belong to. The conversational shield translates automatically.`},{name:"Human Handoff and Assisted Digital",desc:"Complex cases, vulnerable residents, safeguarding concerns and statutory processes require human judgement. Context preserved on transfer — the resident never repeats themselves. Mandatory escalation triggers for safeguarding flags and legal obligations."}],accelerationTitle:"The acceleration",accelerationRows:[{label:"Building a unified resident front door",without:"6–9 months CMS migration, launched cold",withAcc:"Deployed in weeks, tested during shadow period",pct:15},{label:"Handling Day One call surge",without:"Untrained staff. Manual triage.",withAcc:"Golden Number with AI voice routing: 56% deflection",pct:10},{label:"GDPR compliance during Shadow Period",without:"Multi-council data sharing paralysis",withAcc:"Public-domain only. Zero GDPR complexity.",pct:20},{label:"Understanding resident anxiety",without:"Anecdotal. Complaints after the fact.",withAcc:"Real-time Friction Heat Map from day one",pct:20},{label:"Cross-council terminology confusion",without:`"That's not our department"`,withAcc:"Semantic mapping handles it automatically",pct:10},{label:"Prioritising backend harmonisation",without:"Guesswork. Loudest voices win.",withAcc:"Data-driven. Friction Heat Map guides priorities.",pct:15}],humanText:'Sets the tone. Approves the content. Makes policy decisions about service harmonisation. Handles escalated cases that need judgement, empathy, or statutory authority. Decides what "good service" means for the new council. The intelligent shield handles the volume — humans handle the exceptions.',aiText:"Routes 720,000 calls via the Golden Number. Answers 1.4M enquiries across web, phone, 

313chat, email and SMS. Maps terminology across all predecessor councils. Builds the Friction Heat Map in real time. Bypasses GDPR paralysis by using only public-domain data. 62% share of council AI phone platforms. 11 million real-world interactions. 93% customer satisfaction.",deployment:[{phase:"A: Decision Day (+4–8 weeks)",activity:"Deployed as the Intelligent Shield: FAQs, myth-busting, Golden Number voice routing, intelligent routing to predecessor councils. Friction Heat Map begins immediately."},{phase:"B: Shadow Period (Glide Path)",activity:"Expanded into full unified service layer across all five channels. Postcode-aware, temporally-aware. Glide-path testing with real residents. Zero GDPR complexity — public-domain data only."},{phase:"C: Vesting Day",activity:"Becomes the primary front door. All predecessor domains and phone numbers redirect. Already tested — Day One is role expansion, not debut."},{phase:"D: Post-Vesting",activity:"Becomes the permanent digital front door of the new council. Harmonisation instrument panel. Friction Heat Map reveals where legacy fragmentation still hurts. Never stops learning."}]},"workforce-ai":{eyebrow:"FOR COUNCIL STAFF",headline:"SMART: Workforce AI: The Element Missing from Every Previous LGR",positioning:"Every previous local government reorganisation focused on the resident-facing digital challenge. The staff experience was treated as a secondary consideration — with lasting productivity and financial consequences. North Yorkshire built a single front door. Cumberland surface-dressed its website. Somerset consolidated some systems. In none of these cases were staff provided with AI tools to navigate the transition itself or overcome the inherited complexity of legacy systems, policies, and processes. SMART: Workforce AI fixes this. It provides every employee with an enterprise-grade AI assistant grounded in the same Service Graph that powers the resident-facing Front Door — and critically, the transition investment IS the permanent infrastru

313cture. The platform deployed during the shadow period becomes the AI-native council's permanent staff platform.",withoutHeading:"The forgotten dimension of LGR — and its financial consequences",withoutBody:["Every previous reorganisation prioritised the resident-facing challenge. The staff experience was treated largely as an afterthought — with workarounds, multi-system keying, and difficulty navigating legacy processes common across all areas. On Vesting Day, thousands of staff joined unfamiliar structures with incompatible systems. The consequences were predictable: reduced productivity, knowledge silos, shadow AI adoption, and months of confusion as officers were transplanted into unfamiliar structures.","The staff productivity problem is not just an operational inconvenience — it is one of the biggest contributors to the financial failure that has characterised LGR. Six of the nine new councils created between 2019 and 2023 required Exceptional Financial Support (EFS) from central government — a 67% failure rate. The combined EFS requirement approaches £300 million.","A significant contributor to this outcome is that approximately 85% of programme capacity is consumed by administrative process: manual data collection, document searches across unfamiliar predecessor systems, spreadsheet consolidation, validation, refreshing, and report writing. This leaves dangerously little time for the transformation work that generates savings. When front-line officers spend days trawling predecessor council websites to answer basic questions, the result is a council that reaches Vesting Day safe and legal — but with no transformation underway. The savings that were supposed to fund the new authority do not materialise until Year Four or Five. By then, reserves are consumed."],withoutCallout:"67% failure rate. ~£300M in emergency supp

313ort. 85% of capacity consumed by admin. No time left for transformation.",withHeading:"The permanent staff AI platform — not a transition tool to be decommissioned",withBody:[`SMART: Workforce AI provides every officer with an AI assistant grounded in the Service Graph — the same structured knowledge base that powers the resident-facing Front Door. The same knowledge that tells a resident "Your bin collection day is Thursday" also tells a staff member "District B's allocations policy requires a local connection test with a 12-month residency criterion." The Service Graph does the navigation for staff, overcoming all the inherited complexity in a heartbeat.`,`From the first week, officers ask questions in natural language about any predecessor council's policies, processes, fees, or service rules and receive accurate, source-cited answers. The Service Graph's semantic mapping means staff don't need to know what a service is called in another predecessor council — "bulky waste collection" equals "large item uplift." Every answer includes the specific policy document it was drawn from.`,"Critically, every pound spent during the shadow period invests in permanent capability. Workforce AI becomes the permanent staff AI platform — the same knowledge base officers use in Year 2 and Year 3. No decommissioning. No re-procurement. No re-training. The Service Graph carries forward. Workspaces persist. Memory accumulates. Skills expand. The transition investment IS the permanent infrastru

313cture of the AI-native council.","The Personal Command Portal embeds analytical capabilities — contract review, policy comparison, budget analysis, TUPE guidance — directly within each officer's workspace. The programme team gets the full Command Workbench. Every other officer who needs analytical support gets it through their existing Workforce AI interface, at no additional licence cost. This scales transition capacity to every officer who needs it, not just the core team."],capabilities:[{name:"Cross-Council Knowledge Navigation",desc:"The foundational capability with the most immediate impact. Officers ask questions in natural language about any predecessor council's policies, processes, fees, or service rules and receive accurate, source-cited answers. Semantic mapping translates terminology across boundaries automatically. Staff can work across wider areas from Day One rather than sticking to legacy queries for the 2–3 years it typically takes to align policy and systems."},{name:"SMART: Workspaces",desc:"Persistent project spaces where officers organise AI interactions around specific LGR workstreams, service areas, or responsibilities. Each workspace maintains its own context, documents, custom instructions, and conversation history. Pre-configured templates for common LGR functions: contract review, policy harmonisation, budget aggregation. Share with colleagues on the same workstream."},{name:"SMART: Notes",desc:"AI-powered transcription and intelligent output generation for the meetings, workshops, and working groups that dominate the shadow period. Real-time transcription with speaker identification. Automated minutes, action items, decisions log, and follow-up reminders. Available on both web and a dedicated mobile app. Decision tracking across the shadow period — an auditable record of what was agreed, when, and by whom."},{name:"Personal Command Portal",desc:"The programme team gets the full Command Workbench. But LGR affects every officer — hundreds or thousands contribute to workstreams alongside their day jobs. The Personal Command Portal solves this by embedding personal versions of Transition Command capabilities directly within each officer's Workforce AI workspace: contract review, policy comparison, budget analysis, TUPE guidance, risk identification, compliance checking, service mapping. Included at no additional licence cost."},{name:"Skills Library (1,800+ Prompts)",desc:"Role-specific, prebuilt, editable prompts that accelerate adoption. LGR-specific skills: transition briefing notes, committee papers, resident FAQs, staff communications. Role-specific prompts for housing officers, social workers, planning officers, finance officers, HR professionals, and customer service agents. Administrators can edit and publish custom skills organisation-wide — ensuring consistency across predecessor councils."},{name:"SMART: Memory",desc:"User-level memory that learns each officer's role, preferences, and working patterns across sessions. Understands that a particular officer is the lead for the revenues harmonisation workstream without being told each time. Remembers preferred output format, predecessor councils in their area, and context of ongoing work. Officers can view and control this personalisation layer at any time. Fully auditable through the Digital Dome."},{name:"Document Drafting & Data Analysis",desc:'AI-assisted creation of committee papers, transition briefings, policy summaries, harmonisation reports, and budget papers — all grounded in the Service Graph and workspace documents. Conversational data analysis without requiring specialist skills: upload a spreadsheet, ask "How do housing repair costs compare across the five predecessor councils?" and receive a structured comparison.'},{name:"Shadow AI Prevention",desc:"Over 70% of UK employees use unapproved consumer AI tools. By providing governed enterprise AI during the shadow period, staff develop the habit of using SMART: before Vesting Day. The Digital Dome provides granular permissions, ethical walls, immutable audit logging, and kill switches — a governed, auditable alternative that eliminates the GDPR risk of organisational data entering public AI models."}],accelerationTitle:"The acceleration: £19–30M five-year savings through natural attrition",accelerationRows:[{label:"Officer learning a predecessor council's policies",without:"Days/weeks of reading, trawling intranets",withAcc:"Seconds. Ask the AI. Grounded, cited answer.",pct:5},{label:"Drafting a transition committee paper",without:"2–3 days research and writing per paper",withAcc:"Hours. AI drafts from actual policy.",pct:20},{label:"Cross-council policy comparison",without:"Manual spreadsheet. Weeks per service area.",withAcc:"Minutes. AI compares, highlights divergence.",pct:8},{label:"Transition analytical capacity",without:"Limited to core programme team licences",withAcc:"Personal Command Portal scales to every officer.",pct:15},{label:"Shadow AI prevention",without:"70%+ using unapproved consumer AI. GDPR risk.",withAcc:"Governed alternative. Digital Dome controls.",pct:10},{label:"Post-vesting productivity continuity",without:"3–6 month learning curve. Knowledge walks out.",withAcc:"Permanent platform. Institutional memory persists.",pct:10}],humanText:"Makes decisions. Exercises professional judgement. Approves outputs. Brings the local knowledge, the relationships, and the accountability that AI cannot provide. Knows when policy says one thing but the situation needs something else. The Personal Command Portal ensures every officer can contribute to transition — not just the core team.",aiText:"Reads every predecessor council's policies via the Service Graph. Navigates cross-council knowledge with semantic mapping. Drafts committee papers in minutes. Compares data across all predecessors. Answers the same question 500 times without getting tired or getting it wrong. 1,800+ role-specific prompts. SMART: Notes transcribes every meeting. Personal Command Portal scales analytical capacity. The transition investment IS the permanent infrastru

313cture. £19–30M five-year savings through natural attrition.",deployment:[{phase:"A: Decision Day (+4–8 weeks)",activity:"Deployed to the Implementation Team and senior officers across all predecessor councils — the first group needing cross-council knowledge. Cross-council navigation, transition drafting, Personal Command Portal, SMART: Notes. Operates on publicly available information — no GDPR personal data trigger."},{phase:"B: Shadow Period",activity:"The critical, highest-impact phase. Rolled out to the broader staff cohort across all predecessor councils. Thousands of twin-hatting officers navigate unfamiliar systems instantly. Full capability suite: Workspaces, Notes, Skills Library, Personal Command Portal at scale. Shadow AI inoculation — staff develop governed AI habits before Vesting Day."},{phase:"C: Vesting Day",activity:"Serving the entire staff of the new unitary authority. The continuity tool that prevents the Day One productivity collapse that characterised every previous LGR. Process guidance for unfamiliar responsibilities. Predecessor policy clarity by geography. New authority identity in communications."},{phase:"D: Post-Vesting — AI-Native Council",activity:"Workforce AI becomes the permanent staff AI platform of the AI-native council. The transition support tool evolves into the embedded AI layer in daily workflows. The Service Graph carries forward. Workspaces persist. Memory accumulates. Skills expand. The investment during the shadow period is not written off — it IS the new council's permanent AI infrastructure. Shadow AI eradication. Harmonisation intelligence from query logs. Institutional memory persists regardless of staff turnover."}]},"transition-command":{eyebrow:"FOR THE PROGRAMME TEAM",headline:"SMART: LGR Command Workbench: Collect. Understand. Act. Safe, Legal and Financially Viable from Day One.",positioning:"The SMART: LGR Command Workbench is the programme team's central operating environment — a single application with three integrated views: Data (replacing spreadsheet-based RFI collection), Baseline (progressive baseline building with confidence scoring), and Optimise (opportunity identification and risk management). It uses AI automation to compress the safe-and-legal timeline from six to twelve months to a target of sixteen to twenty-four weeks, creating time for genuine transformation and harmonisation before Vesting Day — the time that previous LGR programmes never had. It arrives preloaded with over 500 safe-and-legal tasks with built-in AI assistance, and a central data store preformatted for every major council service area.",withoutHeading:"The spreadsheet challenge: how data collection consumes programme capacity",withoutBody:["Every new unitary authority must establish a complete baseline of the predecessor councils — staff, contracts, assets, systems, finances, obligations — to form a safe and legal operating model for Day One. The current process is built on spreadsheets distributed to service teams and manually consolidated by a central programme team. It typically consumes six to twelve months of an eighteen-to-twenty-four-month programme timeline just to get a reliable baseline.",'Within weeks of distribution, dozens of spreadsheet copies circulate via email, SharePoint, and Teams with no single source of truth. Service teams manually re-key data from their systems into prescribed templates. The same contract is entered multiple times across different RFIs. Dates appear as text, financial values in mixed formats, "N/A" vs blank vs "0". The central team cannot tell which fields are incomplete or whether a "submitted" return contains valid data.',"Six of the nine new councils created between 2019 and 2023 required Exceptional Financial Support from central government — approaching £300 million combined. These were not failures of ambition. Every council followed the established process and achieved safe and legal on Day One. But safe and legal is not the same as financially viable. Evidence suggests that a significant proportion of programme capacity was consumed by administrative process, leaving limited time for the transformation work needed to deliver savings."],withoutCallout:"6 of 9 councils needed emergency supp

313ort. ~£300M combined. Months consumed by data collection. Limited time for transformation.",withHeading:"A central data system — purpose-built for local government, ready on Day One",withBody:["The Command Workbench eliminates spreadsheet hell entirely by providing a central data store preformatted for every major council service area — social care, finance, housing, HR, procurement, IT, environmental services, highways, planning, and more. These are not blank templates waiting to be designed. They are structured, validated data models built from the cumulative experience of previous LGR programmes. The programme team does not spend its first three months designing spreadsheets. It starts collecting and validating data immediately.","Instead of re-keying into prescribed templates, councils upload their data in whatever format they already have — PDF contract registers, HR establishment reports, fleet management CSVs. The AI extraction engine translates, maps columns to the RFI schema, converts formats, and presents extracted records for human review. Service team time per RFI drops from days to hours.",'With a centralised database, there is no merge step. When Council A submits, their data is immediately available. The process becomes continuous — progressive baseline building from B0 ("The Shape") through B1 ("First Draft"), B2 ("Safe and Legal" at weeks 18–22, not weeks 40+), B3 ("The Full Picture"), to B4 ("Decision Ready"). Each baseline answers a different question and unlocks different decisions.',"After Vesting Day, the Command Workbench does not switch off — it becomes the new council's centre for organisational knowledge and transformation. Data becomes live registers, Baseline becomes the performance framework, Optimise becomes the strategic planning and continuous improvement engine. The platform that compressed safe-and-legal delivery becomes the engine for ongoing transformation."],capabilities:[{name:"Data View — Where Information Enters",desc:"Replaces the spreadsheet-based RFI toolkit with a centralised collection environment. Covers every RFI domain: contracts (21 fields per record), staff (headcount, FTE, grades, vacancies), equipment and vehicles, IT systems, KPIs, and domain-specific operational data. Cross-entity deduplication ensures a contract entered once is linked everywhere — not duplicated across separate spreadsheets."},{name:"Baseline View — Where Data Becomes Intelligence",desc:"Transforms raw records into the progressive baseline series (B0 through B4 and Living Baseline). Automatically aggregates submitted data, runs cross-council comparisons, tracks progress against the safe-and-legal task library, and generates reports highlighting anomalies, harmonisation issues, and risk signals. At B2, produces a green/amber/red safe-and-legal assurance dashboard."},{name:"Optimise View — Where Intelligence Becomes Action",desc:"Takes baselined, confidence-scored data and applies it to opportunity identification (contract consolidation, workforce structure design, IT rationalisation, council tax harmonisation) and challenge management (safe-and-legal gap tracking, financial risk monitoring, contract expiry alerting, TUPE and workforce risk management). Cross-references data across all domains to surface insights no single-domain view would reveal."},{name:"500+ Preloaded Safe-and-Legal Tasks",desc:"Arrives preloaded with over 500 safe-and-legal tasks organised by council service area, each with built-in AI assistance on how to perform it. The AI does not just list tasks — it guides teams through each one, explaining what is required, what data is needed, and what good practice looks like. Programme teams start executing from Day One, not designing spreadsheets."},{name:"AI-Powered Data Extraction",desc:"Accept source data in native formats — PDFs, spreadsheets, system exports, published reports. The AI extraction engine reads uploaded documents, identifies records, maps columns to the RFI schema, converts formats, and presents extracted data for human review in a side-by-side interface. Eliminates manual re-keying across 8–15 predecessor councils."},{name:"Progressive Baseline Building (B0–B4)",desc:'Five named baseline stages plus a Living Baseline. B0 "The Shape" (Weeks 6–8): high-level landscape. B1 "First Draft" (Weeks 14–16): first council-validated data. B2 "Safe and Legal" (Weeks 18–22): the critical milestone reached months earlier than traditional. B3 "The Full Picture" (Weeks 26–32): full savings scenarios. B4 "Decision Ready" (Weeks 30–36): board-ready outputs with confidence scoring.'},{name:"Central Data Store with Provenance",desc:"Every value carries its source, confidence level, and change history. Row-Level Security ensures each council sees only their own data while the central team sees everything. The Digital Dome governance layer enforces data access policies, AI usage boundaries, and compliance controls. A contract entered once is visible everywhere it is needed."},{name:"Real-Time Programme Visibility",desc:"SPOC dashboards showing per-council gap reports. PMO dynamic dashboards replacing the RFI Excel Tracker with a real-time cross-council matrix. Formal submission and review workflows with validation sign-off. The central team knows exactly which fields are incomplete and what the overall data quality looks like — at all times."},{name:"Post-Vesting: Centre for Organisational Knowledge",desc:"After Vesting Day, Data becomes the new council's live registers (contract register, HR baseline, asset management, application portfolio). Baseline becomes the performance and financial monitoring framework. Optimise becomes the strategic planning and continuous improvement engine. The same data, same platform, same governance — the programme team's operating environment becomes the leadership team's operating environment."},{name:"North Hampshire Proof of Concept",desc:"Within hours of the 25 March 2026 announcement, a Baseline 0 was compiled from 24 publicly available sources — reveal

313ing a critical financial asymmetry between merging councils that would typically not surface until Month 8 under the traditional process. Knowing this on Day 3 is materially different from discovering it when the first budget is being drafted."}],accelerationTitle:"The acceleration: 28–40 weeks → 16–24 weeks to actionable baseline",accelerationRows:[{label:"RFI template preparation",without:"2–3 weeks designing spreadsheets",withAcc:"Pre-configured in app. 0 weeks.",pct:5},{label:"Council data collection per RFI",without:"4–8 weeks manual re-keying",withAcc:"1–3 weeks. AI extraction from native formats.",pct:15},{label:"Chase and re-submission cycles",without:"2–4 weeks chasing. No visibility.",withAcc:"Real-time dashboards. Target 0–1 weeks.",pct:8},{label:"Consolidation and cleaning per RFI",without:"3–6 weeks manual merge per RFI",withAcc:"Eliminated. Centralised database.",pct:5},{label:"Time to actionable baseline",without:"28–40 weeks",withAcc:"Target: 16–24 weeks",pct:40},{label:"Time freed for transformation",without:"0–10 weeks before Vesting Day",withAcc:"Target: 15–25 weeks before Vesting Day",pct:50}],humanText:'Sets the strategic questions. Makes the harmonisation decisions. Exercises professional judgement on safe-and-legal assurance. Reviews AI-extracted data and confirms accuracy. Decides what "viable" means for this specific authority. The specialist ring — Finance Modeller, Procurement Analyst, HR Analyst, Legal Lead — works through AI-augmented analysis views. The AI compresses the timeline; humans make the decisions.',aiText:"Extracts data from PDFs, CSVs, and system exports — mapping to the preformatted LGR data collection framework automatically. Eliminates spreadsheet hell with a central data store. Builds progressive baselines from B0 to B4 as data arrives — no waiting for all councils to submit. 500+ safe-and-legal tasks with built-in guidance. Cross-references data across all domains to surface insights. Estimated acceleration value: £8–20M in Year One through earlier transformation.",deployment:[{phase:"A: Decision Day (+4–8 weeks)",activity:"Platform configured with preloaded LGR data collection framework and 500+ safe-and-legal tasks. Supplementary public data loaded for early orientation. SPOCs appointed and trained. Output: Baseline 0 — high-level landscape from published sources."},{phase:"B: Shadow Period",activity:"Service teams log in to structured platform with AI-guided assistance. Upload source documents for AI extraction instead of re-keying. Progressive baselines built as data arrives. Specialist ring activates from Week 16. Output: Baseline 2 — Safe and Legal at Weeks 18–22, not Weeks 40+."},{phase:"C: Vesting Day",activity:"Full baseline complete. Board-ready decision papers with confidence scoring. The programme pivots from safe-and-legal to viability — transformation and harmonisation work that previous LGR programmes ran out of time to do."},{phase:"D: Post-Vesting",activity:"Becomes the new council's centre for organisational knowledge and transformation. Data becomes live registers. Baseline becomes the performance framework. Optimise becomes the strategic planning engine. The platform that compressed safe-and-legal delivery sustains viability through Year One and beyond."}]},"application-forge":{eyebrow:"FOR THE DIGITAL ESTATE",headline:"SMART: AI Application Forge: Digital Swarms. Governed Production. Shadow-Period Delivery.",positioning:"Across 21 LGR areas, new unitary authorities inherit fragmented digital estates: multiple websites, hundreds of IT systems, incompatible applications, and disconnected integrations. The conventional approach — specify, procure, build, test, deploy — typically takes longer than the shadow period allows. The SMART: AI Application Forge introduces a different production model: coordinated digital swarms. Where conventional development assigns one team to one project sequentially, the Forge deploys coordinated swarms of specialised AI agents that work in parallel across the full software lifecycle.",withoutHeading:"The capacity challenge: why conventional delivery timelines are difficult to compress",withoutBody:["A typical LGR area inherits between 150 and 580 IT systems across five to eight predecessor councils. Each predecessor has its own website, intranet, CMS, forms platform, booking system, integration layer, and reporting tools. The new council needs a unified digital estate from Vesting Day — and has roughly 11 months of shadow period to build it.","Traditional software delivery follows a predictable pattern: scope, procure, specify, build, test, deploy. For a single application this takes six to eighteen months. For the scale LGR demands — a unified website, staff tools, integration layers, replacement applications, dashboards — the conventional approach would take years. AI coding assistants make individual developers faster but do not change the production model. A developer with Copilot is still one developer, still working sequentially.","The pattern in previous LGR programmes has been consistent: limited digital change for Day One, a transitional website, temporary workarounds, and 

313years of rationalisation ahead. North Yorkshire faced 580 systems requiring ongoing rationalisation after vesting. Cumberland made pragmatic choices about scope because the volume of work was significant."],withoutCallout:"150–580 IT systems. 11 months of shadow period. Sequential delivery is difficult to compress.",withHeading:"A different approach: from sequential delivery to parallel swarm production",withBody:["The Application Forge deploys coordinated swarms of specialised AI agents — Requirements Analyst, Code Generator, Test Engineer, Security Auditor, UI Designer, Integration Builder — that collectively execute complex production tasks in parallel. While one swarm builds the resident service portal, another builds the staff dashboard, another constructs the integration layer, and another generates the analytics platform. This is how a 12–18-month digital programme becomes a shadow-period deliverable.","Every application inherits the SMART: Master Application Template, which provides Vibe Working (natural language, chat-first interface), MCP Server interoperability (every application discoverable by other AI agents and applications), inbuilt Vibe CMS (content management configurable by non-technical administrators), and consistent architecture patterns. This eliminates 40–60% of conventional development effort per application.","Governance is structural, not optional. The seven-layer architecture places Human Governance at the top — approval gates between Specify and Build, between Build and Deploy. The Digital Dome applies governance policies to every swarm action. Every inter-agent communication is logged. Every decision is traceable. Humans govern at the pace of judgement; swarms execute at machine speed.","After deployment, the Management Swarm continuously monitors, maintains, and evolves every application. When a predecessor legacy system is retired in Year 2 or 3, the Dependency Tracker detects the change and the Integration Builder swarm remaps connections automatically. The resident and staff experience is entirely unaffected by back-end changes."],capabilities:[{name:"Coordinated Digital Swarms",desc:"Specialised AI agents (Requirements Analyst, Code Generator, Test Engineer, Security Auditor, UI Designer, Integration Builder) execute the full software lifecycle in parallel. 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Management swarms monitor health, optimise performance, validate compliance, and remap connections when legacy systems are retired."},{name:"Human-in-the-Loop Gates",desc:"No autonomy without control. Every specification reviewed and approved before any build swarm activates. Each build package reviewed before deployment — test results, security findings, and governance compliance presented for human sign-off. Management agents perform routine maintenance autonomously; substantive changes require human approval."},{name:"Eight Categories of Output",desc:"AI-first website and resident portal, internal staff tools and dashboards, integration and orchestration layers, legacy application replacement, application discovery and estate planning, forms/booking/transactional services, delivery acceleration assets, and continuous lifecycle management. Not just a website builder — a complete digital estate production capability."},{name:"Semantic Crawling and Service Graph",desc:'Ingestion swarms crawl all predecessor public digital estates, perform semantic mapping (recognising "bulky waste collection" equals "large item uplift"), and build the structured Service Graph at machine speed. The same Service Graph powers the Front Door, Workforce AI, and the Command Workbench.'},{name:"Management Swarm — Continuous Lifecycle",desc:"What distinguishes the Forge from every tool that generates code and walks away. Each deployed application is continuously monitored, maintained, and evolved. When legacy systems are retired, integration swarms remap automatically. The resident and staff experience is insulated from back-end turbulence."},{name:"30% Systems Consolidation Cost Reduction",desc:"The Forge directly reduces systems consolidation costs by 30% through AI-accelerated migration and parallel delivery. Digital and IT savings of £1.5–3M per year are brought forward by two years versus the traditional timeline. Single production programme eliminates multi-vendor integration cost and procurement overhead."}],accelerationTitle:"The acceleration: 30% systems consolidation cost reduction, savings brought forward by 2 years",accelerationRows:[{label:"New council website from predecessor estates",without:"6–9 months CMS migration",withAcc:"Weeks. Swarms build in parallel.",pct:15},{label:"Mapping predecessor digital estates",without:"Content audit: months per council",withAcc:"Days. Ingestion swarms crawl, map, and structure.",pct:10},{label:"Building internal tools and dashboards",without:"Months per application, sequential",withAcc:"Weeks per app. Multiple swarms concurrently.",pct:20},{label:"Full software lifecycle per application",without:"Sequential: design → code → test → deploy",withAcc:"Parallel: all stages simultaneously via swarms",pct:12},{label:"Legacy system integration",without:"Bespoke API work. 12–18 months.",withAcc:"MCP-based integration layers built by the Forge.",pct:15},{label:"Post-vesting legacy retirement",without:"Manual remapping. Service disruption risk.",withAcc:"Management Swarm remaps automatically.",pct:10}],humanText:"Approves specifications before swarms build. Reviews test results and security findings before deployment. Sets priorities for the digital estate strategy. Makes decisions about service journeys and user experience. Defines governance rules within the Digital Dome. Tests with real users. The Forge builds; your team governs.",aiText:"Coordinated swarms crawl predecessor estates, map 150–580 systems, and build the Service Graph. Multiple build swarms operate concurrently — resident portal, staff tools, integration layers, dashboards — all on the Master Template. Vibe Working, MCP interoperability, and Vibe CMS inherited by every application. Management Swarm handles post-vesting legacy retirement automatically. 30% systems consolidation cost reduction. Digital savings brought forward by two years.",deployment:[{phase:"A: Decision Day (+4–8 weeks)",activity:"Ingestion swarms start crawling all predecessor public digital estates. Discovery swarms assess the IT estate. Specification swarms begin producing production briefs for the AI-first website, first integration layers, and priority internal tools."},{phase:"B: Shadow Period",activity:"Maximum swarm velocity. Multiple build swarms operating concurrently: unified resident website, staff tools, integration layers, legacy application replacements, dashboards. All built on the Master Template. Digital Dome governance encoded from the start. This is not a cold launch."},{phase:"C: Vesting Day",activity:"Complete digital estate live and tested during Phase B. All integrations active. Build swarms transition to Management swarms: monitoring, compliance validation, dynamic reconfiguration. The digital estate has been tested with real users — Day One is a role expansion."},{phase:"D: Post-Vesting",activity:"Management swarms run the digital estate continuously. When legacy systems are retired, integration swarms remap connections automatically. Build swarms reactivate on demand. The Forge becomes the permanent digital estate management capability — not a transition cost."}]}};function gr({title:e,audience:t,description:n,icon:r,videoUrl:a}

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313,{category:"External consultancy",traditional:"£3–8M",smart:"£0.3–0.6M",rationale:"Platform replaces most external consultancy capacity through centralised and automated management of key tasks."},{category:"SMART: LGR Acceleration Platform",traditional:"—",smart:"£2.5M",rationale:"Full platform: Command Workbench, Front Door, Workforce AI, Application Forge."},{category:"IT, website, and digital",traditional:"£1.5–3M",smart:"Included",rationale:"30% systems cost reduction. AI accelerates migration, rationalisation and joins up legacy systems."},{category:"Wider workforce redundancy",traditional:"£3–8M",smart:"£0",rationale:"AI productivity captured through 12–15% annual natural attrition. No compulsory redundancy, no pension strain."},{category:"Senior leadership redundancy",traditional:"£1–3M",smart:"£1–3M",rationale:"No change. Structural consolidation of multiple Senior Leadership teams to one."},{category:"Legal, electoral, constitutional",traditional:"£1–2M",smart:"£0.8–1.5M",rationale:"20% process reduction. AI assists policy harmonisation; statutory work unchanged."},{category:"Platform licence (5 years)",traditional:"—",smart:"£3M",rationale:"Annual licence. Transition investment becomes permanent operating system."},{category:"Contingency provision",traditional:"Included",smart:"25% lower",rationale:"Contingency typically consumed by IT overruns or complexity — both materially reduced."},{category:"Government transition funding",traditional:"–£0.9M",smart:"–£0.9M",rationale:"Central government contribution. No change."}],Qv=[{category:"Traditional — All structural savings",yr1:"—",yr2:"3–7",yr3:"8–14",yr4:"12–19",yr5:"12–19",total:"35–59"},{category:"SMART — Structural savings (accelerated)",yr1:"—",yr2:"4–9",yr3:"9–15",yr4:"12–19",yr5:"12–19",total:"37–62",isSmart:!0},{category:"Front Door demand reduction",yr1:"0.5–1",yr2:"1–3",yr3:"2–4",yr4:"3–5",yr5:"3–6",total:"9.5–19",isSmart:!0},{category:"Workforce AI (natural attrition)",yr1:"—",yr2:"2–4",yr3:"4–7",yr4:"6–9",yr5:"7–10",total:"19–30",isSmart:!0},{category:"AI-enabled income generation",yr1:"—",yr2:"0.5–1.5",yr3:"1–2",yr4:"1.5–3",yr5:"2–3.5",total:"5–10",isSmart:!0},{category:"IT rationalisation & automation",yr1:"—",yr2:"0.5–1.5",yr3:"1–2",yr4:"1.5–3",yr5:"2–3.5",total:"5–10",isSmart:!0},{category:"SMART: TOTAL",yr1:"0.5–1",yr2:"8–19",yr3:"17–30",yr4:"24–39",yr5:"26–42",total:"76–131",isSmart:!0,isTotal:!0}],Jv=[{metric:"Five-year cumulative savings",traditional:"£35–59M",smart:"£76–131M"},{metric:"Total programme cost",traditional:"£11–28M",smart:"£8–13M"},{metric:"Net five-year benefit",traditional:"£7–48M",smart:"£63–123M"},{metric:"Break-even on costs",traditional:"2–4 years",smart:"3–9 months"},{metric:"Savings exceed annual cost pressures",traditional:"Year 4–5",smart:"Year 2–3"},{metric:"EFS probability (evidence base)",traditional:"67% (6 of 9)",smart:"Materially reduced"}

313,{metric:"Permanent infrastructure",traditional:"No",smart:"Yes — AI-native platform"},{metric:"Contractual savings guarantee",traditional:"—",smart:"£10M minimum"}],Zv=[{category:"Optimising Leadership",timing:"Brought forward 1 year",rationale:"Could happen sooner if systems and processes streamlined faster. Key role for workforce specialist partner."},{category:"Right sizing the organisation",timing:"Brought forward 1 year",rationale:"Faster systems consolidation and process rationalisation. 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Physical constraint."},{category:"Customer engagement",timing:"Delivered by end of Year 1",rationale:"Significantly reduces time to optimise contacts, channel shift and reduce hand-offs."},{category:"Fleet and route optimisation",timing:"Potential contribution",rationale:"Significant cost and overhead managing thousands of taxi invoices, daily routes, and matching them to requests."}],Xv=[{title:"Social care placement spend",desc:"The single largest financial pressure. AI does not reduce the cost of commissioned care placements, SEND complexity, or the demand trajectory."},{title:"Physical estate rationalisation",desc:"Disposing of buildings, terminating leases, and reconfiguring sites are physical tasks. Costs identical under both approaches."},{title:"Democratic & electoral restructuring",desc:"Councillor reductions determined by the structural order and agreed new constitutions, not tools used during transition."},{title:"Inherited financial positions",desc:"Where predecessor councils carry significant debt or Section 114 risk, the SMART approach does not eliminate inherited exposure."},{title:"Workforce development & retraining",desc:"Moving people into new roles and upskilling is a human process with professional development support."},{title:"Culture & communications investment",desc:"No council should reduce investment in communications and branding during reorganisation."}];function e3(){return i.jsxs(Se,{children:[i.jsx(et,{eyebrow:"THE FINANCIAL CASE",headline:"A line-by-line comparison of costs, savings, and net outcomes",subtitle:"With independently validated implementation cost reductions and savings acceleration. All figures scaled to a 500,000 population unitary | ~6,000 FTE | ~£450M net revenue budget.",primaryCta:{label:"Book a Briefing",to:"/contact"},secondaryCta:{label:"See the Accelerator",to:"/smart-accelerator"},credibilityBar:[{value:"35–55%",label:"Lower programme costs"},{value:"£10M",label:"Contractual savings guarantee"},{value:"3–9 mo",label:"Break-even vs 2–4 years"}]}),i.jsx("section",{className:"gradient-dark py-16 md:py-20",children:i.jsxs("div",{className:"max-w-[1200px] mx-auto px-4 md:px-6",children:[i.jsxs("div",{className:"text-center mb-10",children:[i.jsx("p",{className:"text-signal-green font-inter font-semibold text-sm uppercase tracking-[0.15em] mb-3",children:"SEE THE FINANCIAL CASE IN ACTION"}),i.jsx("h3",{className:"font-georgia font-bold text-white text-2xl sm:text-3xl md:text-4xl mb-4",children:"Quick video briefing"}),i.jsx("p",{className:"text-light-grey/80 font-inter text-base md:text-lg leading-relaxed max-w-2xl mx-auto",children:"A walk-through of the financial comparison — programme costs, five-year savings, net position, and the acceleration curve that underpins the £10M contractual savings guarantee."})]}),i.jsx("div",{className:"max-w-3xl mx-auto",children:i.jsxs("div",{className:"bg-white/5 border border-white/10 rounded-xl overflow-hidden shadow-[0_8px_32px_rgba(0,0,0,0.3)]",children:[i.jsx("div",{className:"relative w-full",style:{paddingBottom:"56.25%"},children:i.jsx("iframe",{src:"https://www.youtube.com/embed/gORsY-e_L7U",title:"The Financial Case — SMART: Day One LGR Accelerator",className:"absolute top-0 left-0 w-full h-full",frameBorder:0,allow:"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share",allowFullScreen:!0})}),i.jsxs("div",{className:"p-5 flex items-center gap-3",children:[i.jsx(bd,{className:"text-signal-green w-5 h-5 shrink-0"}),i.jsx("p",{className:"text-light-grey/90 font-inter text-sm leading-relaxed",children:"For CEOs, S151 Officers, Programme Directors & Transformation leads — the line-by-line financial comparison and what it means for a financially viable Day One."})]})]})})]})}),i.jsxs(H,{bg:"bg-white",children:[i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl sm:text-3xl md:text-4xl mb-6 text-center",children:"The Financial Challenge"}),i.jsxs("div",{className:"grid grid-cols-1 md:grid-cols-3 gap-6 mb-8",children:[i.jsxs("div",{className:"bg-warning-red/5 border border-warning-red/20 rounded-xl p-6 text-center",children:[i.jsx("div",{className:"text-warning-red font-mono font-bold text-4xl sm:text-5xl mb-2",children:"6 of 9"}),i.jsx("p",{className:"text-dark-grey font-inter text-sm",children:"Councils reorganised since 2019 required Exceptional Financial Support"})]}),i.jsxs("div",{className:"bg-warm-amber/10 border border-warm-amber/20 rounded-xl p-6 text-center",children:[i.jsx("div",{className:"text-warm-amber font-mono font-bold text-4xl sm:text-5xl mb-2",children:"~£300M"}),i.jsx("p",{className:"text-dark-grey font-inter text-sm",children:"Combined emergency financial support required"})]}),i.jsxs("div",{className:"bg-deep-teal/5 border border-deep-teal/20 rounded-xl p-6 text-center",children:[i.jsx("div",{className:"text-deep-teal font-mono font-bold text-4xl sm:text-5xl mb-2",children:"85%"}),i.jsx("p",{className:"text-dark-grey font-inter text-sm",children:"Programme capacity consumed by administrative processes"})]})]}),i.jsxs("div",{className:"space-y-4",children:[i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed",children:"Twenty-one areas are entering Local Government Reorganisation. Each will inherit the combined cost base of five to eight predecessor councils, transition costs on top, and annual cost pressures of 5–10% from pay growth, contract inflation, and surging social care demand."}),i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed",children:"The evidence from the first nine councils is instructive. Somerset required approximately £150 million in government support. Cumberland has received over £76 million. These were not failures of effort — every council followed the established process. The pattern suggests that the traditional approach to transition may not provide sufficient time for the transformation needed to achieve financial sustainability from the outset."}),i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed font-semibold",children:"The structural challenge is timing. The traditional approach typically delivers limited savings before Year Two and does not reach steady state until Year Four or Five. This creates a period of financial pressure during which reserves may be drawn down and cost reductions may be required before transformation savings materialise."})]}),i.jsx(Fa,{children:i.jsx("p",{children:"The evidence from recent reorganisations raises an important question: whether the traditional approach to LGR transition provides sufficient capacity and pace to achieve financial sustainability — and whether AI-assisted approaches can materially improve those outcomes."})})]}),i.jsxs(H,{bg:"bg-off-white",children:[i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl sm:text-3xl md:text-4xl mb-3 text-center",children:"Programme Costs: What It Costs to Deliver LGR"}),i.jsx("p",{className:"text-dark-grey font-inter text-base text-center max-w-3xl mx-auto mb-8",children:"The SMART: approach replaces the bulk of external 

313consultancy spend and manual processes with platform capabilities, replacing the traditional goal of workforce redundancy through AI-enabled natural attrition."}),i.jsxs("div",{className:"grid grid-cols-1 md:grid-cols-2 gap-6 mb-8",children:[i.jsxs("div",{className:"bg-white rounded-xl shadow-sm border border-light-grey p-6",children:[i.jsxs("div",{className:"flex items-center gap-3 mb-4",children:[i.jsx("div",{className:"w-10 h-10 rounded-full bg-warm-amber/20 flex items-center justify-center",children:i.jsx(yd,{className:"w-5 h-5 text-warm-amber"})}),i.jsx("h3",{className:"font-inter font-semibold text-lg text-charcoal",children:"Traditional Approach"})]}),i.jsx("div",{className:"font-mono font-bold text-3xl text-warm-amber mb-1",children:"£11–28M"}),i.jsx("p",{className:"text-dark-grey font-inter text-sm",children:"Total programme cost with no permanent infrastructure"})]}),i.jsxs("div",{className:"bg-white rounded-xl shadow-sm border border-signal-green/30 p-6",children:[i.jsxs("div",{className:"flex items-center gap-3 mb-4",children:[i.jsx("div",{className:"w-10 h-10 rounded-full bg-signal-green/20 flex items-center justify-center",children:i.jsx(wd,{className:"w-5 h-5 text-signal-green"})}),i.jsx("h3",{className:"font-inter font-semibold text-lg text-charcoal",children:"SMART: Approach"})]}),i.jsx("div",{className:"font-mono font-bold text-3xl text-signal-green mb-1",children:"£8–13M"}),i.jsx("p",{className:"text-dark-grey font-inter text-sm",children:"35–55% lower. Leaves permanent AI infrastructure."})]})]}),i.jsx("div",{className:"bg-white rounded-xl shadow-sm border border-light-grey overflow-hidden",children:i.jsx("div",{className:"overflow-x-auto",children:i.jsxs("table",{className:"w-full text-sm",children:[i.jsx("thead",{children:i.jsxs("tr",{className:"bg-deep-navy text-white",children:[i.jsx("th",{className:"text-left px-4 py-3 font-inter font-semibold",children:"Cost Category"}),i.jsx("th",{className:"text-center px-4 py-3 font-inter font-semibold whitespace-nowrap",children:"Traditional"}),i.jsx("th",{className:"text-center px-4 py-3 font-inter font-semibold whitespace-nowrap",children:"SMART:"}),i.jsx("th",{className:"text-left px-4 py-3 font-inter font-semibold hidden lg:table-cell",children:"Assessment Rationale"})]})}),i.jsxs("tbody",{children:[Kv.map((e,t)=>i.jsxs("tr",{className:`border-t border-light-grey ${t%2===0?"bg-white":"bg-off-white/50"}`,children:[i.jsx("td",{className:"px-4 py-3 font-inter font-medium text-charcoal",children:e.category}),i.jsx("td",{className:"px-4 py-3 text-center font-mono text-dark-grey",children:e.traditional}),i.jsx("td",{className:"px-4 py-3 text-center font-mono text-deep-teal font-semibold",children:e.smart}),i.jsx("td",{className:"px-4 py-3 text-dark-grey font-inter text-xs leading-relaxed hidden lg:table-cell",children:e.rationale})]},t)),i.jsxs("tr",{className:"border-t-2 border-deep-navy bg-deep-navy/5",children:[i.jsx("td",{className:"px-4 py-3 font-inter font-bold text-charcoal",children:"TOTAL PROGRAMME COST"}),i.jsx("td",{className:"px-4 py-3 text-center font-mono font-bold text-warm-amber",children:"£11–28M"}),i.jsx("td",{className:"px-4 py-3 text-center font-mono font-bold text-signal-green",children:"£8–13M"}),i.jsx("td",{className:"px-4 py-3 text-dark-grey font-inter text-xs font-semibold hidden lg:table-cell",children:"35–55% lower. Leaves permanent AI infrastructure."})]})]})]})})})]}),i.jsxs(H,{bg:"bg-white",children:[i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl sm:text-3xl md:text-4xl mb-3 text-center",children:"Five-Year Savings: Where the Value Comes From"}),i.jsx("p",{className:"text-dark-grey font-inter text-base text-center max-w-3xl mx-auto mb-8",children:"The SMART: approach generates savings through two mechanisms: accelerating traditional structural savings and creating entirely new savings categories from the AI platform. Evidenced through Derby City Council operational data, the UK Government's cross-government AI trial, and independent Forrester research."}),i.jsx("div",{className:"bg-white rounded-xl shadow-sm border border-light-grey overflow-hidden",children:i.jsx("div",{className:"overflow-x-auto",children:i.jsxs("table",{className:"w-full text-sm",children:[i.jsx("thead",{children:i.jsxs("tr",{className:"bg-deep-nav

313y text-white",children:[i.jsx("th",{className:"text-left px-4 py-3 font-inter font-semibold",children:"Annual Savings (£M)"}),i.jsx("th",{className:"text-center px-3 py-3 font-inter font-semibold",children:"Yr 1"}),i.jsx("th",{className:"text-center px-3 py-3 font-inter font-semibold",children:"Yr 2"}),i.jsx("th",{className:"text-center px-3 py-3 font-inter font-semibold",children:"Yr 3"}),i.jsx("th",{className:"text-center px-3 py-3 font-inter font-semibold",children:"Yr 4"}),i.jsx("th",{className:"text-center px-3 py-3 font-inter font-semibold",children:"Yr 5"}),i.jsx("th",{className:"text-center px-3 py-3 font-inter font-semibold",children:"5-Yr"})]})}),i.jsx("tbody",{children:Qv.map((e,t)=>i.jsxs("tr",{className:`border-t border-light-grey ${e.isTotal?"bg-signal-green/10 border-t-2 border-signal-green":e.isSmart?"bg-deep-teal/5":"bg-warm-amber/5"}`,children:[i.jsx("td",{className:`px-4 py-3 font-inter ${e.isTotal?"font-bold text-charcoal":"font-medium text-charcoal"}`,children:e.category}),[e.yr1,e.yr2,e.yr3,e.yr4,e.yr5,e.total].map((n,r)=>i.jsx("td",{className:`px-3 py-3 text-center font-mono ${e.isTotal?"font-bold text-signal-green":e.isSmart?"text-deep-teal":"text-dark-grey"} ${r===5?"font-semibold":""}`,children:n},r))]},t))})]})})}),i.jsx("p",{className:"text-medium-grey font-inter text-xs mt-4 text-center italic",children:"The first row shows what traditional LGR delivers. The SMART: section shows the same structural savings arriving earlier, plus four additional platform-generated categories. The bottom row shows cumulative additional value: £19–72 million over five years."})]}),i.jsxs(H,{bg:"bg-deep-navy",children:[i.jsx("h2",{className:"font-georgia font-bold text-white text-2xl sm:text-3xl md:text-4xl mb-8 text-center",children:"Net Five-Year Position"}),i.jsx("p",{className:"text-light-grey/80 font-inter text-base text-center max-w-3xl mx-auto mb-8",children:"The cumulative effect of lower costs, higher savings, and earlier break-even is designed to produce a materially improved financial trajectory for the new authority."}),i.jsx("div",{className:"bg-white/10 backdrop-blur rounded-xl overflow-hidden",children:i.jsx("div",{className:"overflow-x-auto",children:i.jsxs("table",{className:"w-full text-sm",children:[i.jsx("thead",{children:i.jsxs("tr",{className:"border-b border-white/20",children:[i.jsx("th",{className:"text-left px-4 py-3 font-inter font-semibold text-white"}),i.jsx("th",{className:"text-center px-4 py-3 font-inter font-semibold text-warm-amber",children:"Traditional"}),i.jsx("th",{className:"text-center px-4 py-3 font-inter font-semibold text-signal-green",children:"SMART:"})]})}),i.jsx("tbody",{children:Jv.map((e,t)=>i.jsxs("tr",{className:"border-t border-white/10",children:[i.jsx("td",{className:"px-4 py-3 font-inter font-medium text-white",children:e.metric}),i.jsx("td",{className:"px-4 py-3 text-center font-mono text-light-grey",children:e.traditional}),i.jsx("td",{className:"px-4 py-3 text-center font-mono text-signal-green font-semibold",children:e.smart})]},t))})]})})}),i.jsx("div",{className:"mt-8 bg-signal-green/10 border border-signal-green/30 rounded-xl p-6 md:p-8",children:i.jsxs("div",{className:"flex items-start gap-4",children:[i.jsx("div",{className:"w-12 h-12 rounded-full bg-signal-green/20 flex items-center justify-center shrink-0",children:i.jsx(Gn,{className:"w-6 h-6 text-signal-green"})}),i.jsxs("div",{children:[i.jsx("h3",{className:"font-inter font-bold text-lg text-white mb-2",children:"The Savings Guarantee"}),i.jsxs("p",{className:"text-light-grey font-inter text-sm leading-relaxed mb-3",children:["ICS.AI offers a contractual guarantee of a minimum ",i.jsx("strong",{className:"text-signal-green",children:"£10 million"})," in savings for councils deploying the full SMART: LGR Acceleration platform. This commitment reflects our confidence in the platform's proven track record across UK councils."]}),i.jsx("p",{className:"text-light-grey font-inter text-sm leading-relaxed",children:"The guarantee means the minimum return from the SMART: investment exceeds its total cost within the first year. A council's investment of £2.5 million is protected by a return guarantee of four times its value."})]})]})}),i.jsx("div",{className:"mt-6 text-center",children:i.jsx("p",{className:"text-light-grey/80 font-inter text-base italic",children:'"The traditional approach costs £11–28 million with no contractual commitment to outcomes. The SMART: approach costs £8–13 million and includes a £10 million savings guarantee — providing a defined floor on return."'})})]}),i.jsxs(H,{bg:"bg-off-white",children:[i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl sm:text-3xl md:text-4xl mb-3 text-center",children:"Savings Acceleration: How AI Changes the Timeline"}),i.jsx("p",{className:"text-dark-grey font-inter text-base text-center max-w-3xl mx-auto mb-8",children:"A significant financial challenge in previous LGR programmes has been the delay before savings materialise. Each savings category has been independently assessed for how much earlier the AI platform is expected to enable delivery."}),i.jsx("div",{className:"space-y-3",children:Zv.map((e,t)=>{const n=e.timing.includes("Brought forward")||e.timing.includes("Delivered by"),r=e.timing.includes("Potential");return i.jsxs("div",{className:"bg-white rounded-xl border border-light-grey p-4 md:p-5 flex flex-col md:flex-row md:items-center gap-3",children:[i.jsxs("div",{className:"flex items-center gap-3 md:w-1/4 shrink-0",children:[n?i.jsx(Ge,{className:"w-5 h-5 text-signal-green shrink-0"}):r?i.jsx($r,{className:"w-5 h-5 text-warm-amber shrink-0"}):i.jsx(vd,{className:"w-5 h-5 text-medium-grey shrink-0"}),i.jsx("span",{className:"font-inter font-semibold text-sm text-charcoal",children:e.category})]}),i.jsx("div",{className:"md:w-1/5 shrink-0",children:i.jsx("span",{className:`inline-block text-xs font-inter font-semibold px-3 py-1 rounded-full ${n?"bg-signal-green/10 text-signal-green":r?"bg-warm-amber/10 text-warm-amber":"bg-medium-grey/10 text-medium-grey"}`,children:e.timing})}),i.jsx("p",{className:"text-dark-grey font-inter text-xs leading-relaxed flex-1",children:e.rationale})]},t)})}),i.jsx("div",{className:"mt-8 border-l-4 border-deep-teal bg-white rounded-r-xl p-6",children:i.jsxs("p",{className:"text-charcoal font-inter text-sm leading-relaxed",children:[i.jsx("strong",{children:"The honest pattern:"})," AI accelerates savings in every category where the bottleneck is information, process complexity, legacy inefficiency or system fragmentation. It does not accelerate savings where the constraint is physical (buildings), political governance (democratic services), or non-addressable contract spend (social care package frameworks). This distinction matters because the categories where AI helps — workforce, corporate services, IT, customer contact — represent the largest savings potential."]})})]}),i.jsxs(H,{bg:"bg-white",children:[i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl sm:text-3xl md:text-4xl mb-3 text-center",children:"Disaggregation Costs"}),i.jsx("p",{className:"text-dark-grey font-inter text-base text-center max-w-3xl mx-auto mb-8",children:"Where LGR creates multiple unitaries from a single county, disaggregation costs represent the ongoing expense of duplicating management and operations of statutory services."}),i.jsx("div",{className:"grid grid-cols-1 md:grid-cols-2 gap-4",children:[{service:"Adult social care",reduction:"—",impact:"No reduction",desc:"Diseconomies of scale and contracts for social care delivery. Cannot see how AI helps this.",color:"border-medium-grey"},{service:"Children's services",reduction:"—",impact:"No reduction",desc:"Same structural diseconomies. Contract and delivery framework driven.",color:"border-medium-grey"},{service:"Place services (planning, highways)",reduction:"10%",impact:"Reduces",desc:"AI systems could quickly help with planning and highways issues of multiple legacy platforms.",color:"border-deep-teal"},{service:"Corporate and support services",reduction:"50%",impact:"Significantly reduces",desc:"AI tools overcome inefficiencies in process and differing legacy policies, systems, and help desks.",color:"border-signal-green"}].map((e,t)=>i.jsxs("div",{className:`bg-off-white rounded-xl border-l-4 ${e.color} p-5`,children:[i.jsxs("div",{className:"flex items-center justify-between mb-2",children:[i.jsx("h4",{className:"font-inter font-semibold text-charcoal",children:e.service}),i.jsx("span",{className:`font-mono font-bold text-lg ${e.reduction==="—"?"text-medium-grey":e.reduction==="50%"?"text-signal-green":"text-deep-teal"}`,children:e.reduction})]}),i.jsx("p",{className:"text-dark-grey font-inter text-sm leading-relaxed",children:e.desc})]},t))})]}),i.jsxs(H,{bg:"bg-off-white",children:[i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl sm:text-3xl md:text-4xl mb-3 text-center",children:"What This Analysis Does Not Claim"}),i.jsx("p",{className:"text-dark-grey font-inter text-base text-center max-w-3xl mx-auto mb-8",children:"Transparency about limitations is what makes the financial case defensible."}),i.jsx("div",{className:"grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-4",children:Xv.map((e,t)=>i.jsxs("div",{className:"bg-white rounded-xl border border-light-grey p-5",children:[i.jsx("h4",{className:"font-inter font-semibold text-charcoal text-sm mb-2",children:e.title}),i.jsx("p",{className:"text-dark-grey font-inter text-xs leading-relaxed",children:e.desc})]},t))})]}),i.jsxs(H,{bg:"bg-white",children:[i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl sm:text-3xl md:text-4xl mb-6 text-center",children:"Evidence Base & Methodology"}),i.jsxs("div",{className:"grid grid-cols-1 lg:grid-cols-2 gap-8",children:[i.jsxs("div",{children:[i.jsx("h3",{className:"font-inter font-semibold text-lg text-charcoal mb-4",children:"Four-Step Methodology"}),i.jsx("div",{className:"space-y-4",children:[{step:"1",title:"Establish three financial pillars",desc:"Implementation costs (one-off), reorganisation savings (recurring efficiencies), and disaggregation costs (multi-unitary duplication)."}

313,{step:"2",title:"Apply assumptions",desc:"Structured assumptions based on publicly available outturn data, transparency reporting, and benchmarks from previous LGR programmes."},{step:"3",title:"Produce base case financial model",desc:"Most likely scenario balancing prudent savings estimates with realistic implementation ambition. High case also modelled."},{step:"4",title:"Scale for multi-unitary models",desc:"Benchmarked costs per capita multiplied by total population with uplift per additional unitary authority."}].map(e=>i.jsxs("div",{className:"flex gap-4",children:[i.jsx("div",{className:"w-8 h-8 rounded-full gradient-primary flex items-center justify-center shrink-0",children:i.jsx("span",{className:"text-white font-mono font-bold text-sm",children:e.step})}),i.jsxs("div",{children:[i.jsx("h4",{className:"font-inter font-semibold text-sm text-charcoal",children:e.title}),i.jsx("p",{className:"text-dark-grey font-inter text-xs leading-relaxed mt-1",children:e.desc})]})]},e.step))})]}),i.jsxs("div",{children:[i.jsx("h3",{className:"font-inter font-semibold text-lg text-charcoal mb-4",children:"Quality Assurance"}),i.jsxs("div",{className:"bg-off-white rounded-xl p-5 mb-4",children:[i.jsxs("p",{className:"text-dark-grey font-inter text-sm leading-relaxed mb-3",children:["The underlying financial model was subject to a full-workbook audit producing ",i.jsx("strong",{children:"22 findings"})," across 3 severity levels:"]}),i.jsxs("div",{className:"space-y-2",children:[i.jsxs("div",{className:"flex items-center gap-2",children:[i.jsx("span",{className:"w-2 h-2 rounded-full bg-warning-red"}),i.jsxs("span",{className:"text-dark-grey font-inter text-sm",children:[i.jsx("strong",{children:"3 Critical"})," — Formula errors, duplicate headers, inconsistent mapping. All resolved."]})]}),i.jsxs("div",{className:"flex items-center gap-2",children:[i.jsx("span",{className:"w-2 h-2 rounded-full bg-warm-amber"}),i.jsxs("span",{className:"text-dark-grey font-inter text-sm",children:[i.jsx("strong",{children:"8 Warnings"})," — Missing formulas, mismatched categories. Majority resolved."]})]}),i.jsxs("div",{className:"flex items-center gap-2",children:[i.jsx("span",{className:"w-2 h-2 rounded-full bg-signal-green"}),i.jsxs("span",{className:"text-dark-grey font-inter text-sm",children:[i.jsx("strong",{children:"11 Informational"})," — Documentation and formatting items."]})]})]})]}),i.jsx("h3",{className:"font-inter font-semibold text-lg text-charcoal mb-3",children:"Sources"}),i.jsx("p",{className:"text-dark-grey font-inter text-xs leading-relaxed",children:'Published accounts and audit reports from all nine LGR councils (2019–2026); MHCLG Revenue Outturn data; ONS QPSES workforce data; Electoral Commission cost-per-vote data; council transparency reporting; Derby City Council verified operational results; UK Government cross-government generative AI trial (20,000 civil servants); Forrester Total Economic Impact study; Grant Thornton "Learning from the New Unitary Councils" (September 2024); CIPFA external assurance reviews; LGA Toolkit and peer challenge reports; MHCLG Digital and Cyber Playbook (February 2026); PwC/County Councils Network population threshold analysis (March 2025).'})]})]})]}),i.jsx(H,{bg:"bg-deep-navy",children:i.jsxs("div",{className:"text-center",children:[i.jsx("h2",{className:"font-georgia font-bold text-white text-2xl sm:text-3xl md:text-4xl mb-6",children:"For programme boards evaluating options, the comparison is clear"}),i.jsxs("div",{className:"grid grid-cols-1 md:grid-cols-2 gap-6 max-w-3xl mx-auto mb-8",children:[i.jsxs("div",{className:"bg-white/10 backdrop-blur rounded-xl p-6 border border-warm-amber/30",children:[i.jsx("div",{className:"font-mono font-bold text-3xl text-warm-amber mb-2",children:"£11–28M"}),i.jsx("p",{className:"text-light-grey font-inter text-sm mb-1",children:"Traditional approach"}),i.jsx("p",{className:"text-warm-amber font-inter text-sm font-semibold",children:"No contractual commitment to outcomes"})]}),i.jsxs("div",{className:"bg-white/10 backdrop-blur rounded-xl p-6 border border-signal-green/30",children:[i.jsx("div",{className:"font-mono font-bold text-3xl text-signal-green mb-2",children:"£8–13M"}),i.jsx("p",{className:"text-light-grey font-inter text-sm mb-1",children:"SMART: approach"}),i.jsx("p",{className:"text-signal-green font-inter text-sm font-semibold",children:"Guarantees £10M return"})]})]}),i.jsx("p",{className:"text-light-grey/80 font-inter text-lg italic mb-8",children:"One carries no guaranteed return. The other provides a contractual floor."})]})}),i.jsx(tt,{headline:"See the full financial model for your area",subtitle:"Book a 30-minute briefing and we'll walk through the line-by-line comparison tailored to your LGR area — number of predecessors, digital estate scale, staff population, and timeline.",primaryCta:{label:"Book a Briefing",to:"/contact"},secondaryCta:{label:"See the Accelerator",to:"/smart-accelerator"}})]})}const Rl=[{id:"lgr-decisions-made-now-real-work-begins",title:"LGR Decisions Made. Now the Real Work Begins.",date:"Tuesday 18 August 2026",time:"12:00 pm – 1:00 pm",overview:`The Government has confirmed structures for the great majority of England's Local Government Reorganisation areas. This takes the total programme to 134 councils becoming 38 new unitary authorities. Only a small number of areas, including West Sussex and Cambridgeshire & Peterborough, remained outstanding at the time of this session.
314
315For almost every council, the question was no longer whether reorganisation would happen. It was how to deliver it, and deliver it well.
316
317The boundaries may be confirmed, but many of the most important questions are only beginning to be answered. How will the new authority operate? Which services, systems, contracts and policies will transfer? How will councils maintain safe and reliable services throughout the transition? How will residents and employees receive consistent answers when detailed decisions are still being made? Most importantly, how can authorities use reorganisation to create a financially viable operating model rather than simply combining existing organisations?
318

319The period immediately following an LGR decision is critical. Early choices about programme governance, service design, data, technology and resident access will shape the new authority for years. Delaying transformation until the shadow period risks carrying duplicated processes, fragmented systems and avoidable costs into the new organisation.
320
321This recorded session sets out the practical actions LGR authorities need to take now, and shows the tool built to help them move quickly.
322
323We examined how councils can establish a single, controlled view of the transition programme, identify the decisions and dependencies that matter most, and coordinate work across multiple organisations without relying on disconnected spreadsheets, meetings and documents.
324
325At the centre of the session was a deep dive into SMART: LGR Command Workbench 3.2, the latest version of the platform, including significant new capability in AI-led data ingestion and AI-assisted disaggregation. We showed, through a realistic post-confirmation scenario, how the Workbench helps authorities:
326
327• Mobilise the transition programme and establish clear governance
328• Create a structured baseline of services, systems, contracts, policies, people and assets — now ingested directly from native source documents
329• Manage decisions, dependencies, risks and evidence across all participating councils
330• Identify opportunities for service redesign and financial improvement before vesting
331• Maintain a trusted source of information for employees, members and residents
332• Prepare the new authority's digital and AI-enabled front door
333• Build a practical route from safe and legal transition to long-term financial viability
334

335The session combined strategic guidance, practical examples and live demonstrations of the Command Workbench and AI front-door capabilities.
336
337Watch the recording to gain a clearer understanding of what your authority should be doing during the first weeks following confirmation, what should not be left until the shadow authority is established, and how a structured 16–24-week acceleration programme can create the foundations for a successful new council.`,gains:["What practical actions your authority should take immediately following confirmation","How to establish a single, controlled view of the transition programme across multiple councils","A deep dive into SMART: LGR Command Workbench 3.2, including AI-led data ingestion and AI-assisted disaggregation","How a structured 16–24-week acceleration programme creates the foundations for a successful new council"],audience:"Chief Executives, Section 151 Officers, Programme Directors, and Transformation / Digital leaders responsible for LGR delivery.",provenAtScale:"The SMART: platform is already delivering at scale across UK local government: 62% market share in councils deploying phone AI | 11M+ live AI interactions | £12M+ Identified savings at Derby City Council.",closingNote:"The boundaries are confirmed. The clock is running. Watch the recording to see what to do first, and how to do it at the speed the timeline demands.",registrationUrl:"https://info.ics.ai/LGR-Decisions-Made-Now-the-Real-Work-Begins/registration-form.html",isPast:!0}],Fl=[{id:"lgr-safe-legal-to-viable-june",title:"Local Government Reorganisation — From Safe & Legal to Financially Viable",date:"Thursday 18 June 2026",time:"1:00 pm – 2:00 pm",overview:`LGR: From Safe & Legal to Financially Viable – A new approach to delivering a sustainable council from Day One.
338
339Local Government Reorganisation consistently delivers 'safe and legal' on Day One — but that is not where the real risk lies.
340
341Recent programmes show a clear pattern: while councils reach vesting successfully, many enter operation without the transformation required to sustain themselves financially, with six of nine requiring Exceptional Financial Support.
342
343The issue is not delivery capability — it is the model itself. Most programmes spend the majority of the shadow period building a baseline, leaving too little time to design and optimise the new council before it goes live. The result is a council that is safe and legal — but not yet financially viable.
344
345This webinar introduces the SMART: Day One LGR Accelerator — a fundamentally different model designed to change that outcome. By using AI to compress discovery, automate baseline building, and scale delivery capacity, the Accelerator brings forward transformation — enabling councils to deliver a financially viable Day One, not just a compliant one.
346
347Critically, it is backed by a £10M contractual savings guarantee — shifting LGR from an uncertain programme to one with a defined financial outcome.`,gains:["Why the traditional LGR model limits financial outcomes","How an AI-enabled model changes delivery speed, capacity, cost and risk","How to create time for transformation within existing timelines","What a credible, financially viable Day One actually requires"],audience:"Chief Executives, Section 151 Officers, Programme Directors, and Transformation / Digital leaders responsible for LGR delivery.",provenAtScale:"The SMART: platform is already delivering at scale across UK local government: 62% market share in councils deploying phone AI | 11M+ live AI interactions | £12M+ Identified savings at Derby City Council.",closingNote:"Safe and legal is the minimum requirement. This session explores how to deliver a council that is financially sustainable from Day One — not years later.",registrationUrl:"https://info.ics.ai/LGR-From-Safe-and-Legal-to-Financially-Viable-180626-Recording/registration-form.html",isPast:!0},{id:"lgr-safe-legal-to-viable-april",title:"Local Government Reorganisation — From Safe & Legal to Financially Viable",date:"Friday 24 April 2026",time:"10:00 am – 11:00 am",overview:`LGR: From Safe & Legal to Financially Viable – A new approach to delivering a sustainable council from Day One.
348
349Local Government Reorganisation consistently delivers 'safe and legal' on Day One — but that is not where the real risk lies.
350
351Recent programmes show a clear pattern: while councils reach vesting successfully, many enter operation without the transformation required to sustain themselves financially, with six of nine requiring Exceptional Financial Support.
352
353The issue is not delivery capability — it is the model itself. Most programmes spend the majority of the shadow period building a baseline, leav

353ing too little time to design and optimise the new council before it goes live. The result is a council that is safe and legal — but not yet financially viable.
354
355This webinar introduces the SMART: Day One LGR Accelerator — a fundamentally different model designed to change that outcome. By using AI to compress discovery, automate baseline building, and scale delivery capacity, the Accelerator brings forward transformation — enabling councils to deliver a financially viable Day One, not just a compliant one.
356
357Critically, it is backed by a £10M contractual savings guarantee — shifting LGR from an uncertain programme to one with a defined financial outcome.`,gains:["Why the traditional LGR model limits financial outcomes","How an AI-enabled model changes delivery speed, capacity, cost and risk","How to create time for transformation within existing timelines","What a credible, financially viable Day One actually requires"],audience:"Chief Executives, Section 151 Officers, Programme Directors, and Transformation / Digital leaders responsible for LGR delivery.",provenAtScale:"The SMART: platform is already delivering at scale across UK local government: 62% market share in councils deploying phone AI | 11M+ live AI interactions | £12M+ Identified savings at Derby City Council.",closingNote:"Safe and legal is the minimum requirement. This session explores how to deliver a council that is financially sustainable from Day One — not years later.",registrationUrl:"https://forms.microsoft.com/pages/responsepage.aspx?id=5DtYAZbw9Em9GVa2SahIL1u2lTQXc7RDmJOUJglXhi5URTFIWlBDUzFPVzVZMjNKSTNNR1NHRUs1Qi4u&route=shorturl",isPast:!0}];function t3(){const e=Rl.filter(n=>!n.isPast),t=Rl.filter(n=>n.isPast);return i.jsxs(Se,{children:[i.jsx(et,{eyebrow:"WEBINARS & EVENTS",headline:"Our LGR webinar series",subtitle:"Expert-led sessions exploring how AI changes the financial trajectory of Local Government Reorganisation. Watch the recordings below for first-hand insights from leaders who have delivered LGR programmes.",primaryCta:{label:"Book a Briefing",to:"/contact"}}),e.length>0&&i.jsxs(H,{bg:"bg-white",children:[i.jsxs("div",{className:"flex items-center gap-3 mb-8",children:[i.jsx("div",{className:"w-3 h-3 rounded-full bg-signal-green animate-pulse"}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl sm:text-3xl md:text-4xl",children:"Upcoming Webinars"})]}),i.jsx("div",{className:"space-y-8",children:e.map(n=>i.jsx(Pl,{webinar:n},n.id))})]}),Fl.length>0&&i.jsxs(H,{bg:"bg-off-white",children:[i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl sm:text-3xl md:text-4xl mb-8",children:"Webinar Recordings"}),i.jsx("div",{className:"space-y-6",children:[...t,...Fl].map(n=>i.jsx(Pl,{webinar:n,isRecording:!0},n.id))})]}),i.jsx(tt,{headline:"Can't make a webinar? Book a private briefing instead.",subtitle:"A 30-minute session tailored to your LGR area — covering the financial case, platform capabilities, and deployment timeline.",primaryCta:{label:"Book a Briefing",to:"/contact"},secondaryCta:{label:"See the Financial Case",to:"/financial-case"}})]})}function Pl({webinar:e,isRecording:t=!1}){return i.jsxs("div",{className:"bg-white rounded-2xl shadow-[0_2px_12px_rgba(13,27,42,0.08)] hover:shadow-[0_8px_28px_rgba(13,27,42,0.14)] transition-all duration-300 overflow-hidden border border-light-grey",children:[i.jsx("div",{className:"h-1.5 gradient-primary"}),i.jsxs("div",{className:"p-6 md:p-8 lg:p-10",children:[i.jsxs("div",{className:"flex flex-wrap gap-3 mb-5",children:[i.jsxs("span",{className:"inline-flex items-center gap-1.5 bg-deep-teal/10 text-deep-teal text-sm font-inter font-semibold px-3.5 py-1.5 rounded-full",children:[i.jsx(kd,{className:"w-4 h-4"}),e.date]}),i.jsxs("span",{className:"inline-flex items-center gap-1.5 bg-deep-navy/5 text-charcoal text-sm font-inter font-medium px-3.5 py-1.5 rounded-full",children:[i.jsx($r,{className:"w-4 h-4"}),e.time]})]}),i.jsx("h3",{className:"font-georgia font-bold text-charcoal text-xl sm:text-2xl md:text-3xl leading-tight mb-5",children:e.title}),i.jsx("div",{className:"space-y-3 mb-6",children:e.overview.split(`
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359`).map((n,r)=>i.jsx("p",{className:"text-dark-grey font-inter text-base leading-relaxed",children:n},r))}),i.jsxs("div",{className:"bg-off-white rounded-xl p-5 md:p-6 mb-6",children:[i.jsx("h4",{className:"font-inter font-semibold text-charcoal text-lg mb-4",children:"What You'll Gain"}),i.jsx("div",{className:"space-y-3",children:e.gains.map((n,r)=>i.jsxs("div",{className:"flex items-start gap-3",children:[i.jsx(Ge,{className:"w-5 h-5 text-signal-green shrink-0 mt-0.5"}),i.jsx("p",{className:"text-dark-grey font-inter text-sm leading-relaxed",children:n})]},r))}),i.jsx("p",{className:"text-dark-grey font-inter text-sm leading-relaxed mt-4 italic",children:"You will also hear first-hand insights from leaders who have delivered LGR programmes, reflecting on what works in practice — and what they would do differently."})]}),i.jsx("div",{className:"border-l-4 border-signal-green bg-signal-green/5 rounded-r-xl p-5 mb-6",children:i.jsxs("p",{className:"text-charcoal font-inter text-sm leading-relaxed",children:[i.jsx("strong",{className:"text-deep-teal",children:"Proven at scale:"})," ",e.provenAtScale]})}),i.jsxs("div",{className:"flex items-start gap-3 mb-6",children:[i.jsx(qe,{className:"w-5 h-5 text-deep-teal shrink-0 mt-0.5"}),i.jsxs("div",{children:[i.jsx("h4",{className:"font-inter font-semibold text-charcoal text-sm mb-1",children:"Who Should Attend?"}),i.jsx("p",{className:"text-dark-grey font-inter text-sm leading-relaxed",children:e.audience})]})]}),i.jsx("p",{className:"text-charcoal font-inter text-base leading-relaxed font-semibold italic mb-8",children:e.closingNote}),i.jsx("div",{className:"flex flex-col sm:flex-row gap-4",children:i.jsxs("a",{href:e.registrationUrl,target:"_blank",rel:"noopener noreferrer",className:"inline-flex items-center justify-center gap-2 bg-deep-teal text-white font-inter font-semibold text-base px-8 py-3.5 rounded-lg hover:brightness-110 transition-all",children:[t?"Watch the Recording":"Register Now"," ",i.jsx(Tr,{className:"w-4 h-4"})]})})]})]})}const n3=od,Kc=$.forwardRef(({className:e,...t},n)=>i.jsx(id,{ref:n,className:Hr("border-b",e),...t}));Kc.displayName="AccordionItem";const Qc=$.forwardRef(({className:e,children:t,...n},r)=>

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359,{icon:br,label:"3 patent applications",detail:"European, PCT, and US — pending"},{icon:Ir,label:"Parliamentary & Lords recognition",detail:"Referenced in House of Lords by Lord Holmes of Richmond; cited in Parliament by Luke Murphy MP"},{icon:Ge,label:"90%+ competitive win rate",detail:"When evaluated against alternatives"},{icon:sa,label:"Microsoft AI Inner Circle",detail:"Founder members of Microsoft's AI Inner Circle partner program"},{icon:$r,label:"Bootstrapped",detail:"No venture capital. Sustainable, profitable growth since founding"}],t=[{title:"Socitm Awards 2025",detail:"Winner — Partner and Customer Collaboration",council:"ICS.AI & Derby City Council",color:"bg-deep-teal"},{title:"National AI Awards 2024",detail:"Highly Commended — Best Application of AI in Public Sector",council:"ICS.AI & Derby City Council",color:"bg-vivid-purple"},{title:"iESE Awards",detail:"Winner — AI Innovation in Local Government",council:"Derby City Council",color:"bg-deep-teal"},{title:"APSE Awards",detail:"Overall Council of the Year for Service Delivery",council:"Renfrewshire Council",color:"bg-vivid-purple"},{title:"COSLA Awards 2025",detail:"Leading Innovation Award",council:"Renfrewshire Council",color:"bg-deep-teal"},{title:"Scottish Public Service Awards 2025",detail:"Digital Public Services Award",council:"Renfrewshire Council",color:"bg-vivid-purple"},{title:"British Data Awards 2026",detail:"Finalist — Data-Driven Public Sector Innovation",council:"ICS.AI",color:"bg-deep-teal"},{title:"EY Entrepreneur of the Year",detail:"Shortlisted — CEO Martin Neale",council:"ICS.AI",color:"bg-vivid-purple"}],n=[{title:"LGR needs a new operating model, not just a new council",summary:"How to design a new operating model for Local Government Reorganisation that delivers financial viability from Day One — not years after vesting.",url:"https://www.ics.ai/post/lgr-new-operating-model"},{title:"LGR: Safe and legal is not the finish line",summary:"Why achieving 'safe and legal' on vesting day is the minimum requirement — and why councils must plan for financial sustainability from the outset.",url:"https://www.ics.ai/post/safe-and-legal-is-not-the-finish-line"},{title:"One in four council professionals not confident their authority will be viable on ‘Vesting Day’, poll reveals",summary:"Results from the sector poll on council financial viability at the point of vesting — and what the findings mean for LGR programme design.",url:"https://www.ics.ai/post/lgr-poll-council-viability-vesting-day"},{title:"England’s biggest council shake-up in a generation is underway as ICS.AI launches Accelerator to help compress the two-year transition to April 2028",summary:"Introducing the SMART: Day One LGR Accelerator — a fundamentally different model for delivering financially viable councils through the 2028 reorganisation wave.",url:"https://www.ics.ai/post/ics-ai-lgr-accelerator-council-reorganisation-2028"},{title:"Derby AI Innovation Referenced in House of Lords",summary:"Lord Holmes of Richmond cited Derby City Council's AI partnership with ICS.AI during a House of Lords debate on AI in public services, highlighting it as a leading example of responsible AI deployment in local government.",url:"https://www.ics.ai/post/derby-ai-innovation-referenced-house-of-lords"},{title:"Derby City Council Wins iESE Awards for AI Innovation",summary:"Derby's AI-powered customer service transformation — delivering £12M+ in identified savings and 56% call resolution — recognised as best-in-class innovation in local government service delivery.",url:"https://www.ics.ai/post/derby-city-council-ai-innovation-wins-iese-awards"},{title:"ICS.AI & Derby Highly Commended at National AI Awards",summary:"The partnership between ICS.AI and Derby City Council received Highly Commended in the Best Application of AI in Public Sector category at the National AI Awards 2024.",url:"https://www.ics.ai/post/ics-ai-and-derby-city-council-win-highly-commended-at-national-ai-awards"},{title:"Award-Winning AI at the Front Door: Renfrewshire Council",summary:"How Renfrewshire Council became the first local authority in Scotland to deploy AI-powered phone services, handling 392,000+ calls with 40% resolved without human intervention.",url:"https://www.ics.ai/post/award-winning-ai-at-the-front-door-renfrewshire-council-webinar"},{title:"ICS.AI — British Data Awards 2026 Finalist",summary:"ICS.AI recognised as a finalist at the British Data Awards 2026 for data-driven innovation in public sector AI deployment across UK local government.",url:"https://www.ics.ai/post/ics-ai-british-data-awards-2026-finalist"}];return i.jsxs(Se,{children:[i.jsx(et,{eyebrow:"EVIDENCE",headline:"Proof, not promises",subtitle:"The SMART: platform is not a theoretical proposition. It is live infrastru

359cture with an existing footprint across UK councils, recognised by Parliament, the House of Lords, and multiple national award bodies. Here is the operational data.",primaryCta:{label:"Book a Briefing",to:"/contact"}}),i.jsx("section",{className:"gradient-dark py-16 md:py-20",children:i.jsxs("div",{className:"max-w-[1200px] mx-auto px-4 md:px-6",children:[i.jsxs("div",{className:"flex items-center gap-3 mb-2",children:[i.jsx(oa,{className:"w-6 h-6 text-electric-teal"}),i.jsx("span",{className:"text-electric-teal font-inter font-semibold text-sm uppercase tracking-wider",children:"Flagship Case Study"})]}),i.jsx("h2",{className:"font-georgia font-bold text-white text-2xl sm:text-3xl md:text-4xl mb-2",children:"Derby City Council"}),i.jsx("p",{className:"text-light-grey font-inter text-base mb-3",children:"The same platform. The same architecture. The same Service Graph approach. Live at scale since 2023."}),i.jsx("p",{className:"text-light-grey/80 font-inter text-sm mb-10 max-w-3xl",children:'Derby City Council partnered with ICS.AI to deploy "Darcie" — an AI-powered assistant handling council tax, benefits, housing, waste, and highways enquiries. 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359cture","ISO 27001 aligned security practices","Data encrypted at rest and in transit","Regular penetration testing","No data shared with third-party AI providers","Full data sovereignty — council data under council control"].map((e,t)=>i.jsxs("div",{className:"flex items-start gap-3 bg-off-white rounded-xl p-4",children:[i.jsx(Gn,{className:"w-5 h-5 text-deep-teal shrink-0 mt-0.5"}),i.jsx("span",{className:"text-charcoal text-sm font-inter",children:e})]},t))})]}),i.jsx(tt,{headline:"Questions about governance, compliance, or data?",subtitle:"Book a briefing and we'll walk through the Digital Dome governance framework in detail.",primaryCta:{label:"Book a Briefing",to:"/contact"}})]})}const h3=[{category:"The Basics",items:[{q:"What is the SMART: Day One Accelerator?",a:"Four integrated AI force multipliers designed for LGR: SMART: LGR Front Door (for residents — a unified conversational AI engagement layer across web, phone, web chat, email and SMS), SMART: Workforce AI (for staff — enterprise AI assistant grounded in the Service Graph with Personal Command Portal, SMART: Workspaces, Notes, and 1,800+ role-specific prompts), SMART: LGR Command Workbench (for the programme team — a single application with three views: Data, Baseline, Optimise — replacing spreadsheet-based RFI collection with 500+ preloaded safe-and-legal tasks and AI-powered data extraction), SMART: AI Application Forge (for the digital estate — coordinated digital swarms building the unified digital estate in parallel). All powered by the same Service Graph, governed by the same Digital Dome. It deploys from the day of the decision, not vesting day. The Accelerator works alongside your existing strategic partner or independently."},{q:"Why do we need AI for LGR? We're focused on getting the basics right.",a:'The "basics" of LGR include reviewing thousands of contracts, reconciling inconsistent workforce data, comparing policies that use different terminology, building a unified front door, and equipping staff to work across unfamiliar councils. These ARE the basics — and AI is the only way to deliver them in 11 months. Without it, you risk landing with a "Day One veneer" — new branding over complex legacy wiring — and years of transformation ahead.'},{q:"Is this the same platform other councils use?",a:"Yes. The SMART: platform provides the AI front door deployment for 62% of UK councils that have adopted 'front door' AI. The Day One Accelerator is the LGR-specific deployment. The Derby City Council proof points (£12M+ identified savings) are from the same core technology. Across all clients, the SMART: platform has processed 11M+ real-world interactions."}]},{category:"Speed and Deployment",items:[{q:"How quickly can you deploy?",a:"Phase A — the initial deployment to the implementation team plus a transition front door for residents — can be live within 4–8 weeks. The Forge begins semantic crawling of predecessor estates immediately. Full deployment expands during the shadow period."},{q:"Does everything launch on vesting day?",a:`No — that is the point. All four elements deploy and are tested during the shadow period. Vesting day is a role expansion, not a debut. North Yorkshire's scrutiny recommended this "glide path." The Accelerator delivers it across all four dimensions.`},{q:"What happens after vesting day?",a:"The Accelerator becomes permanent infrastru

359cture. The SMART: LGR Front Door becomes the permanent digital front door. SMART: Workforce AI becomes the permanent staff platform — Personal Command Portal transitions to ongoing operational analytics, institutional memory persists regardless of staff turnover. The Command Workbench becomes the centre for organisational knowledge: Data becomes live registers, Baseline becomes the performance framework, Optimise becomes the strategic planning engine. The Forge's Management Swarm handles ongoing legacy retirement automatically. Every component that compressed the transition sustains viability through Year One and beyond."}]},{category:"Cost and Procurement",items:[{q:"How do we procure this?",a:"All SMART: products are on G-Cloud 15. Compliant procurement without full competitive tender. Continuing authorities: procurement carries forward. New authorities: joint committee, shadow authority budget, or lead council."},{q:"What does it cost?",a:"Tailored to LGR area — number of predecessors, digital estate scale, staff population, timeline. Book a briefing for a detailed proposal mapped to your area."},{q:"How do we fund it during the shadow period?",a:"Joint committee budget, lead council procurement, flexible capital receipts, or shadow authority preparation budget. Every pound spent invests in permanent capability."}]},{category:"Data and Governance",items:[{q:"How does this work with GDPR when predecessors are separate Data Controllers?",a:"During shadow period, all elements operate on publicly available information and published policies. No personal data sharing required. Post-vesting, new council is Data Controller, and Digital Dome governance governs all access."},{q:"What about Shadow AI — staff using ChatGPT?",a:"Over 70% of UK employees use unapproved consumer AI. LGR pressure escalates this dramatically. SMART: Workforce AI provides a governed alternative that's better, faster, and auditable. Digital Dome gives statutory officers total visibility."},{q:"Who controls the AI? Can it make decisions?",a:"The AI does not make decisions. It provides grounded, cited information for human decision-making. Every response includes source attribution. Escalation rules route complex queries to humans. Governing principle: no autonomy without control."}]},{category:"How It Compares",items:[{q:"Why not Microsoft Copilot or generic AI tools?",a:"Generic AI tools are not grounded in your council's services, policies, and processes. They cannot distinguish between predecessor councils' approaches. They have no governance for statutory authorities. They create Shadow AI risk rather than solving it."},{q:"Why not a consultancy?",a:"Consultancies provide advice and project management. They do not provide permanent AI infrastructure. When the consultancy leaves, you have a static website and recommendations. The Accelerator is the infrastructure itself — it stays, it learns, it evolves."},{q:"We already have a strategic partner. Can the Accelerator work alongside them?",a:"Absolutely. The Accelerator is designed to complement your existing strategic partner, not replace them. Your partner brings programme management, organisational design expertise, and local knowledge. The Accelerator provides the AI infrastructure that multiplies their capacity — compressing analytical work, automating resident engagement, and building the digital estate at machine speed. Many councils will use the Accelerator alongside their strategic partner to deliver more, faster, within the same budget. You can also use the Accelerator independently if you prefer."}]}];function f3(){return i.jsxs(Se,{children:[i.jsx(et,{eyebrow:"FREQUENTLY ASKED QUESTIONS",headline:"Questions we hear from council leaders",subtitle:"Answers to the most common questions about the SMART: Day One Accelerator, deployment, governance, and procurement.",primaryCta:{label:"Book a Briefing",to:"/contact"}}),i.jsx("section",{className:"bg-white py-16 md:py-20",children:i.jsx("div",{className:"max-w-[900px] mx-auto px-4 md:px-6",children:h3.map((e,t)=>i.jsxs("div",{className:"mb-10",children:[i.jsx("h3",{className:"font-inter font-semibold text-charcoal text-lg mb-4 pb-2 border-b border-light-grey",children:e.category}),i.jsx(n3,{type:"single",collapsible:!0,className:"space-y-2",children:e.items.map((n,r)=>i.jsxs(Kc,{value:`${t}-${r}`,className:"border border-light-grey rounded-xl px-5 data-[state=open]:bg-off-white",children:[i.jsx(Qc,{className:"text-left font-inter font-semibold text-charcoal text-sm md:text-base py-4 hover:no-underline",children:n.q}),i.jsx(Jc,{className:"text-dark-grey font-inter text-sm leading-relaxed pb-4",children:n.a})]},r))})]},t))})}),i.jsx(tt,{headline:"Ready to see the Accelerator in action?",subtitle:"Book a 30-minute briefing mapped to your specific LGR area.",primaryCta:{label:"Book a Briefing",to:"/contact"}})]})}function m3(){return i.jsx(Se,{children:i.jsx("section",{className:"bg-white py-20 md:py-32",children:i.jsxs("div",{className:"max-w-[600px] mx-auto px-4 md:px-6 text-center",children:[i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-3xl md:text-4xl mb-4",children:"This page doesn't exist yet — but we can still help."}),i.jsx("p",{className:"text-dark-grey font-inter text-lg mb-8",children:"Much like a new unitary authority on Day One, we need to route you to the right place."}),i.jsxs("div",{className:"flex flex-col gap-3",children:[i.jsxs(oe,{to:"/",className:"text-deep-teal font-inter font-semibold hover:underline inline-flex items-center justify-center gap-1",children:["Go to the homepage ",i.jsx(Je,{className:"w-4 h-4"})]}),i.jsxs(oe,{to:"/smart-accelerator",className:"text-deep-teal font-inter font-semibold hover:underline inline-flex items-center justify-center gap-1",children:["See the SMART: Day One Accelerator ",i.jsx(Je,{className:"w-4 h-4"})]}),i.jsxs(oe,{to:"/contact",className:"text-deep-teal font-inter font-semibold hover:underline inline-flex items-center justify-center gap-1",children:["Book a briefing ",i.jsx(Je,{className:"w-4 h-4"})]})]})]})})})}function p3(){return i.jsx(Se,{children:i.jsxs(H,{bg:"bg-white",className:"min-h-[60vh]",children:[i.jsx("h1",{className:"font-georgia font-bold text-charcoal text-3xl md:text-4xl mb-8",children:"Disclaimer"}),i.jsxs("div",{className:"max-w-3xl space-y-6 text-dark-grey font-inter text-base leading-relaxed",children:[i.jsx("p",{children:"This website provides general guidance on Local Government Reorganisation (LGR) and related transformation approaches. Content is based on information available at the time of publication and may be subject to change, including policy, funding, and implementation timelines."}),i.jsx("p",{children:"While ICS.AI makes reasonable efforts to ensure accuracy, the material is provided for informational and illustrative purposes only. Examples, scenarios and case references are intended to highlight potential risks and opportunities and should not be interpreted as statements of fact about specific organisations or as reflecting their full circumstances."}),i.jsx("p",{children:"This content should not be relied upon as the sole basis for operational, legal, financial, or procurement decisions. Organisations should undertake their own due diligence and, where appropriate, seek independent professional advice before taking action based on the information provided."}),i.jsx("p",{children:"ICS.AI accepts no liability for any loss or impact arising from reliance on the information presented on this site."})]})]})})}function g3(){return i.jsx(Se,{children:i.jsxs(H,{bg:"bg-white",className:"min-h-[60vh]",children:[i.jsx("h1",{className:"font-georgia font-bold text-charcoal text-3xl md:text-4xl mb-8",children:"Privacy Policy"}),i.jsxs("div",{className:"max-w-3xl space-y-6 text-dark-grey font-inter text-base leading-relaxed",children:[i.jsx("p",{className:"text-sm text-slate-500 italic",children:"Effective date: 25 October 2018"}),i.jsxs("p",{children:[i.jsx("strong",{children:"ICS.AI Ltd"}),i.jsx("br",{}),"Grove House, Lutyens Close, Basingstoke, Hampshire, RG24 8AG"]}),i.jsx("p",{children:'ICS.AI LTD ("us", "we", or "our") operates this website (the "Service").'}),i.jsx("p",{children:"This page informs you of our policies regarding the collection, use, and disclosure of personal data when you use our Service and the choices you have associated with that data."}),i.jsx("p",{children:"We use your data to provide and improve the Service. 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359ollecting and using the personal information described in this Privacy Policy depends on the Personal Data we collect and the specific context in which we collect it."}),i.jsx("p",{children:"ICS.AI LTD may process your Personal Data because:"}),i.jsxs("ul",{className:"list-disc pl-6 space-y-1",children:[i.jsx("li",{children:"We need to perform a contract with you"}),i.jsx("li",{children:"You have given us permission to do so"}),i.jsx("li",{children:"The processing is in our legitimate interests and it's not overridden by your rights"}),i.jsx("li",{children:"To comply with the law"})]}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Retention of Data"}),i.jsx("p",{children:"ICS.AI LTD will retain your Personal Data only for as long as is necessary for the purposes set out in this Privacy Policy. We will retain and use your Personal Data to the extent necessary to comply with our legal obligations, resolve disputes, and enforce our legal agreements and policies."}),i.jsx("p",{children:"ICS.AI LTD will also retain Usage Data for internal analysis purposes. Usage Data is generally retained for a shorter period of time, except when this data is used to strengthen the security or to improve the functionality of our Service, or we are legally obligated to retain this data for longer time periods."}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Transfer of Data"}),i.jsx("p",{children:"Your information, including Personal Data, may be transferred to — and maintained on — computers located outside of your state, province, country or other governmental jurisdiction where the data protection laws may differ from those in your jurisdiction."}),i.jsx("p",{children:"If you are located outside the United Kingdom and choose to provide information to us, please note that we transfer the data, including Personal Data, to the United Kingdom and process it there."}),i.jsx("p",{children:"Your consent to this Privacy Policy followed by your submission of such information represents your agreement to that transfer."}),i.jsx("p",{children:"ICS.AI LTD will take all steps reasonably necessary to ensure that your data is treated securely and in accordance with this Privacy Policy and no transfer of your Personal Data will take place to an organisation or a country unless there are adequate controls in place including the security of your data and other personal information."}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Disclosure of Data"}),i.jsx("h3",{className:"font-georgia font-bold text-charcoal text-xl pt-2",children:"Disclosure for Law Enforcement"}),i.jsx("p",{children:"Under certain circumstances, ICS.AI LTD may be required to disclose your Personal Data if required to do so by law or in response to valid requests by public authorities (e.g. a court or a government agency)."}),i.jsx("h3",{className:"font-georgia font-bold text-charcoal text-xl pt-2",children:"Legal Requirements"}),i.jsx("p",{children:"ICS.AI LTD may disclose your Personal Data in the good faith belief that such action is necessary to:"}),i.jsxs("ul",{className:"list-disc pl-6 space-y-1",children:[i.jsx("li",{children:"Comply with a legal obligation"}),i.jsx("li",{children:"Protect and defend the rights or property of ICS.AI LTD"}),i.jsx("li",{children:"Prevent or investigate possible wrongdoing in connection with the Service"}),i.jsx("li",{children:"Protect the personal safety of users of the Service or the public"}),i.jsx("li",{children:"Protect against legal liability"})]}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Security of Data"}),i.jsx("p",{children:"The security of your data is important to us, but remember that no method of transmission over the Internet, or method of electronic storage is 100% secure. While we strive to use commercially acceptable means to protect your Personal Data, we cannot guarantee its absolute security."}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Your Data Protection Rights Under GDPR"}),i.jsx("p",{children:"If you are a resident of the European Economic Area (EEA), you have certain data protection rights. ICS.AI LTD aims to take reasonable steps to allow you to correct, amend, delete, or limit the use of your Personal Data."}),i.jsx("p",{children:"If you wish to be informed what Personal Data we hold about you and if you want it to be removed from our systems, please contact us."}),i.jsx("p",{children:"In certain circumstances, you have the following data protection rights:"}),i.jsxs("ul",{className:"list-disc pl-6 space-y-2",children:[i.jsxs("li",{children:[i.jsx("strong",{children:"The right to access, update or to delete the information we have on you."})," Whenever made possible, you can access, update or request deleti

359on of your Personal Data directly within your account settings section. 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The add-on prevents the Google Analytics JavaScript (ga.js, analytics.js, and dc.js) from sharing information with Google Analytics about visit activity."}),i.jsxs("p",{children:["For more information on the privacy practices of Google, please visit the Google Privacy & Terms webpage: ",i.jsx("a",{href:"http://www.google.com/intl/en/policies/privacy/",target:"_blank",rel:"noopener noreferrer",className:"text-deep-teal hover:underline",children:"http://www.google.com/intl/en/policies/privacy/"})]}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Links to Other Sites"}),i.jsx("p",{children:"Our Service may contain links to other sites that are not operated by us. If you click on a third party link, you will be directed to that third party's site. We strongly advise you to review the Privacy Policy of every site you visit."}),i.jsx("p",{children:"We have no control over and assume no responsibility for the content, privacy policies or practices of any third party sites or services."}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Children's Privacy"}),i.jsx("p",{children:'Our Service does not address anyone under the age of 18 ("Children").'}),i.jsx("p",{children:"We do not knowingly collect personally identifiable information from anyone under the age of 18. If you are a parent or guardian and you are aware that your child has provided us with Personal Data, please contact us. If we become aware that we have collected Personal Data from children without verification of parental consent, we take steps to remove that information from our servers."}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Changes to This Privacy Policy"}),i.jsx("p",{children:"We may update our Privacy Policy from time to time. We will notify you of any changes by posting the new Privacy Policy on this page."}),i.jsx("p",{children:'We will let you know via email and/or a prominent notice on our Service, prior to the change becoming effective and update the "effective date" at the top of this Privacy Policy.'}),i.jsx("p",{children:"You are advised to review this Privacy Policy periodically for any changes. Changes to this Privacy Policy are effective when they are posted on this page."}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Contact Us"}),i.jsx("p",{children:"If you have any questions about this Privacy Policy, please contact us:"}),i.jsxs("ul",{className:"list-disc pl-6 space-y-1",children:[i.jsxs("li",{children:["By email: ",i.jsx("a",{href:"mailto:[email protected]",className:"text-deep-teal hover:underline",children:"[email protected]"})]}),i.jsx("li",{children:"By phone: 01256 403 800"})]})]})]})})}function x3(){return i.jsx(Se,{children:i.jsxs(H,{bg:"bg-white",className:"min-h-[60vh]",children:[i.jsx("h1",{className:"font-georgia font-bold text-charcoal text-3xl md:text-4xl mb-8",children:"Accessibility Statement"}),i.jsxs("div",{className:"max-w-3xl space-y-6 text-dark-grey font-inter text-base leading-relaxed",children:[i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Our C

359ommitment"}),i.jsx("p",{children:"ICS.AI Ltd is committed to ensuring digital accessibility for people with disabilities. We are continually improving the user experience for everyone and applying the relevant accessibility standards to ensure we provide equal access to all users."}),i.jsx("p",{children:"This accessibility statement applies to the SMART: Day One website."}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Conformance Status"}),i.jsxs("p",{children:["We aim to conform to the ",i.jsx("strong",{children:"Web Content Accessibility Guidelines (WCAG) 2.1 Level AA"})," standard. These guidelines explain how to make web content more accessible for people with disabilities and more user-friendly for everyone."]}),i.jsx("p",{children:"Where possible, we have also applied some Level AAA criteria to further improve the accessibility of this website."}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Measures We Take"}),i.jsx("p",{children:"ICS.AI Ltd takes the following measures to ensure accessibility of this website:"}),i.jsxs("ul",{className:"list-disc pl-6 space-y-2",children:[i.jsxs("li",{children:[i.jsx("strong",{children:"Colour contrast"})," — All text and interactive elements meet or exceed WCAG AA contrast ratio requirements (minimum 4.5:1 for normal text, 3:1 for large text)."]}),i.jsxs("li",{children:[i.jsx("strong",{children:"Keyboard navigation"})," — All interactive elements, including links, buttons, forms, and navigation menus, are fully operable using a keyboard alone."]}),i.jsxs("li",{children:[i.jsx("strong",{children:"Screen reader compatibility"})," — The site uses semantic HTML, ARIA landmarks, and descriptive labels to ensure compatibility with assistive technologies such as screen readers (JAWS, NVDA, VoiceOver)."]}),i.jsxs("li",{children:[i.jsx("strong",{children:"Alternative text"})," — All meaningful images include descriptive alt text. Decorative images are marked appropriately so they are ignored by screen readers."]}),i.jsxs("li",{children:[i.jsx("strong",{children:"Responsive design"})," — The website is designed to be fully usable across a range of devices and screen sizes, from mobile phones to large desktop monitors."]}),i.jsxs("li",{children:[i.jsx("strong",{children:"Text resizing"})," — Content can be resized up to 200% without loss of information or functionality."]}),i.jsxs("li",{children:[i.jsx("strong",{children:"Motion and animation"})," — The site respects the ",i.jsx("code",{className:"bg-slate-100 px-1 rounded text-sm",children:"prefers-reduced-motion"})," operating system setting. Users who have indicated a preference for reduced motion will see simplified or no animations."]}),i.jsxs("li",{children:[i.jsx("strong",{children:"Form accessibility"})," — All form inputs use visible, associated labels. Error messages are clearly identified and described in text. Required fields are indicated both visually and programmatically."]}),i.jsxs("li",{children:[i.jsx("strong",{children:"Focus indicators"})," — Visible focus indicators are provided for all interactive elements to support keyboard-only navigation."]}),i.jsxs("li",{children:[i.jsx("strong",{children:"Link purpose"})," — Links are written to make sense out of context, and external links are clearly identified."]}),i.jsxs("li",{children:[i.jsx("strong",{children:"Consistent navigation"})," — Navigation mechanisms are consistent across all pages."]}),i.jsxs("li",{children:[i.jsx("strong",{children:"Page structure"})," — Pages use a logical heading hierarchy (h1–h6) and landmark regions to support easy navigation with assistive technologies."]})]}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Compatibility"}),i.jsx("p",{children:"This website is designed to be compatible with the following assistive technologies:"}),i.jsxs("ul",{className:"list-disc pl-6 space-y-1",children:[i.jsx("li",{children:"Screen readers (JAWS, NVDA, VoiceOver, TalkBack)"}),i.jsx("li",{children:"Screen magnification software"}),i.jsx("li",{children:"Speech recognition software"}),i.jsx("li",{children:"Keyboard-only navigation"})]}),i.jsx("p",{className:"pt-2",children:"The website is tested and supported on the following browsers:"}),i.jsxs("ul",{className:"list-disc pl-6 space-y-1",children:[i.jsx("li",{children:"Google Chrome (latest two versions)"}),i.jsx("li",{children:"Mozilla Firefox (latest two versions)"}),i.jsx("li",{children:"Apple Safari (latest two versions)"}),i.jsx("li",{children:"Microsoft Edge (latest two versions)"})]}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Known Limitations"}),i.jsx("p",{children:"Despite our best efforts to ensure accessibility, there may be some limitations. Below is a description of known limitations and potential solutions:"}),i.jsxs("ul",{className:"list-disc pl-6 space-y-2",children:[i.jsxs("li",{children:[i.jsx("strong",{children:"Third-party content"})," — Some embedded content from third-party services (such as YouTube videos) may not be fully accessible. We encourage users to visit the original platforms for accessible alternatives."]}),i.jsxs("li",{children:[i.jsx("strong",{children:"PDF documents"})," — Some older PDF documents may not be fully accessible. We are working to remediate these and provide accessible alternatives where possible."]}),i.jsxs("li",{children:[i.jsx("strong",{children:"Dynamic content"})," — Some dynamically loaded content may not be immediately announced by screen readers. We are working to improve live region announcements."]})]}),i.jsx("p",{children:"We are actively working to address these issues and improve the overall accessibility of the site."}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Feedback"}),i.jsx("p",{children:"We welcome your feedback on the accessibility of this website. If you encounter any accessibility barriers or have suggestions for improvement, please contact us:"}),i.jsxs("ul",{className:"list-disc pl-6 space-y-1",children:[i.jsxs("li",{children:[i.jsx("strong",{children:"Email:"})," ",i.jsx("a",{href:"mailto:[email protected]",className:"text-deep-teal hover:underline",children:"[email protected]"})]}),i.jsxs("li",{children:[i.jsx("strong",{children:"Phone:"})," 01256 403 800"]}),i.jsxs("li",{children:[i.jsx("strong",{children:"Address:"})," ICS.AI Ltd, Grove House, Lutyens Close, Basingstoke, Hampshire, RG24 8AG"]})]}),i.jsxs("p",{children:["We aim to respond to accessibility feedback within ",i.jsx("strong",{children:"5 working days"})," and to propose a solution within ",i.jsx("strong",{children:"10 working days"}),"."]}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Enforcement Procedure"}),i.jsxs("p",{children:["If you are not satisfied with our response to your accessibility concern, you can escalate the matter to the ",i.jsx("strong",{children:"Equality and Human Rights Commission (EHRC)"}),":"]}),i.jsxs("ul",{className:"list-disc pl-6 space-y-1",children:[i.jsxs("li",{children:["Website: ",i.jsx("a",{href:"https://www.equalityadvisoryservice.com/",target:"_blank",rel:"noopener noreferrer",className:"text-deep-teal hover:underline",children:"https://www.equalityadvisoryservice.com/"})]}),i.jsx("li",{children:"Telephone: 0808 800 0082"})]}

359),i.jsx("p",{children:"The Equality Advisory Support Service (EASS) can advise you on your rights and help resolve disputes."}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Technical Specifications"}),i.jsx("p",{children:"Accessibility of this website relies on the following technologies to work with the particular combination of web browser and any assistive technologies or plugins installed on your computer:"}),i.jsxs("ul",{className:"list-disc pl-6 space-y-1",children:[i.jsx("li",{children:"HTML5"}),i.jsx("li",{children:"WAI-ARIA"}),i.jsx("li",{children:"CSS"}),i.jsx("li",{children:"JavaScript"}),i.jsx("li",{children:"SVG"})]}),i.jsx("p",{children:"These technologies are relied upon for conformance with the accessibility standards used."}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Assessment Approach"}),i.jsx("p",{children:"ICS.AI Ltd assessed the accessibility of this website through the following approaches:"}),i.jsxs("ul",{className:"list-disc pl-6 space-y-2",children:[i.jsxs("li",{children:[i.jsx("strong",{children:"Self-evaluation"})," — Internal testing using automated accessibility tools (axe, Lighthouse) and manual testing."]}),i.jsxs("li",{children:[i.jsx("strong",{children:"User testing"})," — Testing with keyboard-only navigation and screen reader software."]}),i.jsxs("li",{children:[i.jsx("strong",{children:"Ongoing monitoring"})," — Regular accessibility audits are conducted as part of our development process to ensure continued compliance."]})]}),i.jsx("h2",{className:"font-georgia font-bold text-charcoal text-2xl pt-4",children:"Standards We Follow"}),i.jsx("p",{children:"This statement was prepared based on the following standards and guidelines:"}),i.jsxs("ul",{className:"list-disc pl-6 space-y-2",children:[i.jsxs("li",{children:[i.jsx("a",{href:"https://www.w3.org/TR/WCAG21/",target:"_blank",rel:"noopener noreferrer",className:"text-deep-teal hover:underline",children:"Web Content Accessibility Guidelines (WCAG) 2.1"})," — Level AA"]}),i.jsx("li",{children:i.jsx("a",{href:"https://www.gov.uk/guidance/accessibility-requirements-for-public-sector-websites-and-apps",target:"_blank",rel:"noopener noreferrer",className:"text-deep-teal hover:underline",children:"UK Government Accessibility Requirements"})}),i.jsx("li",{children:i.jsx("a",{href:"https://www.legislation.gov.uk/uksi/2018/952/contents/made",target:"_blank",rel:"noopener noreferrer",className:"text-deep-teal hover:underline",children:"The Public Sector Bodies (Websites and Mobile Applications) Accessibility Regulations 2018"})}),i.jsxs("li",{children:[i.jsx("a",{href:"https://www.etsi.org/deliver/etsi_en/301500_301599/301549/03.02.01_60/en_301549v030201p.pdf",target:"_blank",rel:"noopener noreferrer",className:"text-deep-teal hover:underline",children:"EN 301 549 V3.2.1 (2021-03)"})," — European standard for ICT accessibility"]})]}),i.jsx("p",{className:"pt-6 text-sm text-slate-500 italic",children:"This accessibility statement was last reviewed and updated on March 2026."})]})]})})}const b3=()=>{const{pathname:e}=Ur();return $.useEffect(()=>{window.scrollTo(0,0)},[e]),null},y3=new 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