https://nimbleseo.ai/_next/static/immutable/chunks/0nfj9f-f-zcb3.js

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You write and optimize content, audit pages, track rankings, and monitor whether AI engines like ChatGPT, Perplexity, and Google AI Overviews cite your brand — all on a single engine that powers both the search lane and the AI lane.",lane:"both",links:[{label:"View the labeled sample demo",href:"/demo"},{label:"Browse the glossary",href:"/glossary"}],surfaces:["public","app"],updated:"2026-07-10"},{slug:"do-i-need-to-connect-anything",category:"getting-started",question:"Do I need to connect anything before I can start?",answer:"You can write, score an article, audit a URL, or improve a draft without connecting anything. For dashboards and recommendations based on your business, connect two performance sources: Google Search Console, Google Analytics 4, Ahrefs, or Semrush. Examples stay clearly labelled until then. Add publishing tools such as a CMS only when you need them.",lane:"both",links:[{label:"Connect data sources",href:"/integrations#measurement-sources",appOnly:!0},{label:"Run a technical audit",href:"/technical",appOnly:!0}],surfaces:["public","app"],updated:"2026-07-23"},{slug:"connect-a-source",category:"getting-started",question:"How do I connect enough data to use my own evidence?",answer:"Open Integrations and connect two performance sources: Google Search Console, Google Analytics 4, Ahrefs, or Semrush. After the first source, setup guides you to add a second so recommendations can cross-check results. Add a crawler, CMS, alerts, or automation only when a workflow asks for it. Every connection stays within the active workspace.",lane:"both",links:[{label:"Open Integrations",href:"/integrations",appOnly:!0}],surfaces:["public","app"],updated:"2026-06-30"},{slug:"run-find-fix-loop",category:"getting-started",question:"How does the find → fix loop work, and can I undo a change?",answer:"In the Technical surface, the platform finds on-page issues, lets you preview the exact change, applies it, and — crucially — lets you undo it. Every fix is reversible: you can revert any applied change, so you can experiment without risk. This reversible find → fix loop is the core of the on-page engine.",lane:"seo",links:[{label:"Open Technical",href:"/technical",appOnly:!0}],surfaces:["public","app"],updated:"2026-06-30"},{slug:"how-do-i-contact-support",category:"getting-started",question:"How do I contact support or send feedback?",answer:"Existing customers can use the Feedback button in the app shell or sign in and open Support to file and track an account-linked ticket. If you cannot sign in or are still evaluating NimbleSEO, email support directly.",lane:"both",links:[{label:"Email support",href:"mailto:[email protected]?subject=NimbleSEO%20support"}],surfaces:["public","app"],updated:"2026-07-10"},{slug:"read-ai-visibility",category:"getting-started",question:"How do I read AI-visibility results?",answer:"AI Visibility samples a set of prompts across multiple AI engines and extracts whether — and how — your brand is cited. Each result shows the engine, the prompt, and the citation evidence, with a confidence band. It is a sample across prompts and engines, not a complete census of every AI answer, and it is labelled that way.",lane:"geo",links:[{label:"Open AI Visibility",href:"/ai-visibility",appOnly:!0},{label:"How AI visibility is measured",href:"/methodology/ai-visibility"}],surfaces:["public","app"],updated:"2026-06-30"},{slug:"humanize-a-draft",category:"getting-started",question:"How do I humanize an AI-generated draft?",answer:"Paste or open a draft in the Humanizer and choose a mode (Standard, Creative, Academic, or Casual) with adjustable intensity to match your brand voice. It rewrites the text to read more naturally. It does not promise to defeat any specific AI detector — it improves the writing, and you review the result before publishing.",lane:"both",links:[{label:"Open the Humanizer",href:"/humanizer",appOnly:!0}],surfaces:["public","app"],updated:"2026-06-30"},{slug:"set-up-rank-tracking",category:"getting-started",question:"How do I set up rank tracking?",answer:"Add the keywords you want to track in the Rankings surface and the platform records their positions over time so you can see rank history and movement. Position data comes from the configured SERP source; until a run completes, new keywords show as pending rather than a fabricated position.",lane:"seo",links:[{label:"Open Rankings",href:"/rankings",appOnly:!0}],surfaces:["public","app"],updated:"2026-06-30"},{slug:"observe-act-verify-report",category:"workflows-features",question:"How does 

2NimbleSEO turn findings into measurable results?",answer:"NimbleSEO starts with your goal, records source evidence, identifies the most valuable opportunity, recommends the next action, and tracks the work through completion. It then repeats the same measurement, compares before and after, and reports the impact with an attribution-confidence label. What the product finds appears as “What we found,” the prioritized recommendation appears as “What to do next,” active work appears as “Work in progress,” and measured change appears as “Results.”",lane:"both",links:[{label:"See the product methodology",href:"/methodology"},{label:"View the labeled sample demo",href:"/demo"}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"how-actions-are-prioritized",category:"workflows-features",question:"How does NimbleSEO decide what I should do next?",answer:"The command deck ranks concrete moves using the evidence available in your workspace: AI-answer presence and share of voice, ranking signals, technical findings, and content readiness. Inputs can be measured, sampled, or estimated, so every recommendation keeps its provenance and uncertainty instead of hiding them inside one magic score. You remain the decision-maker.",lane:"both",links:[{label:"Open the command deck",href:"/",appOnly:!0},{label:"How metrics are labelled",href:"/methodology"}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"content-workflow",category:"workflows-features",question:"Can NimbleSEO research, write, optimize, and refresh content?",answer:"Yes. The content workflow covers research and briefs, drafting, brand-voice and originality checks, SEO/GEO optimization, internal-link opportunities, decay detection, and refresh planning. Generated work is a draft for human review; factual claims and citations still need editorial verification before publication.",lane:"both",links:[{label:"Open Studio",href:"/studio",appOnly:!0},{label:"Browse content tools",href:"/help",appOnly:!0}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"publishing-and-cms-safety",category:"workflows-features",question:"Can it publish changes to my CMS?",answer:"Supported CMS connections can stage or publish approved content and on-page changes, but the safe path is preview → approve → deploy → read back → recheck. A database-only suggestion is not presented as a live CMS change, and an integration failure is shown as partial or failed rather than silently marked complete. CMS availability depends on the connected provider and plan.",lane:"both",links:[{label:"Open Integrations",href:"/integrations",appOnly:!0},{label:"Review the find → fix workflow",href:"/technical",appOnly:!0}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"agencies-and-client-reporting",category:"workflows-features",question:"Is NimbleSEO built for agencies and multi-brand teams?",answer:"Yes. Workspaces keep client data separate, portfolios roll up multiple workspaces, roles control access, and agency workflows include client-ready evidence reports and white-label delivery. Limits for seats, workspaces, prompt checks, crawl pages, and credits vary by plan, so the pricing page is the source of truth for capacity.",lane:"both",links:[{label:"Compare plan capacity",href:"/pricing"},{label:"Open Reports",href:"/reports",appOnly:!0}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"technical-links-and-local",category:"workflows-features",question:"Does it cover technical SEO, internal links, backlinks, and local SEO?",answer:"The product includes live crawling and technical findings, reversible on-page fixes, internal-link and topic-architecture analysis, provider-backed backlink analysis, and local-search workflows. Coverage is not identical in every area: backlink and local metrics depend on configured external providers, and a feature visible in the wider product may be plan-gated or outside the default launch workflow. The UI states when a connection or entitlement is required.",lane:"seo",links:[{label:"Open Technical",href:"/technical",appOnly:!0},{label:"Browse all help topics",href:"/help",appOnly:!0}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"experiments-and-proof",category:"workflows-features",question:"Can I prove that a change caused a ranking or citation lift?",answer:"You can retain before-and-after evidence, re-run the relevant checks, and compare changed pages with a matched control set. That supports a directional or matched-control conclusion, not proof of causation. NimbleSEO never upgrades an observational comparison into a randomized-experiment claim.",lane:"both",links:[{label:"Read the methodology",href:"/methodology"}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"supported-languages",category:"workflows-features",question:"Which languages does NimbleSEO support?",answer:"The interface ships in 18 languages, while research and content generation support 36 language and market variants. Interface language and content language are separate: for example, you can use the product in Dutch while researching and writing for Japan. Search locale, script direction, and generation instructions follow the selected content market.",lane:"both",links:[{label:"Open account settings",href:"/settings/account",appOnly:!0}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"what-is-geo",category:"seo-vs-geo",question:"What is GEO (Generative Engine Optimization)?",answer:"GEO is the practice of optimizing content so AI engines — ChatGPT, Perplexity, Google AI Overviews, Gemini — cite it in their generated answers. Where classic SEO competes for a blue link on a results page, GEO competes to be the source an AI quotes. Techniques include clear BLUF answers, data density, structured formats, and source attribution.",lane:"geo",links:[{label:"GEO in the glossary",href:"/glossary"},{label:"Open AI Visibility",href:"/ai-visibility",appOnly:!0}],surfaces:["public","app"],updated:"2026-06-30"},{slug:"geo-vs-seo-difference",category:"seo-vs-geo",question:"How is GEO different from classic SEO?",answer:"Classic SEO optimizes for ranking in a list of links; GEO optimizes for being cited inside an AI-generated answer. SEO success is a position on a SERP; GEO success is a citation in ChatGPT or an AI Overview. They overlap — good structure and authority help both — but they are measured differently, which is why this platform gives every surface an SEO lane and a GEO lane.",lane:"both",links:[{label:"Browse the glossary",href:"/glossary"}],surfaces:["public","app"],updated:"2026-06-30"},{slug:"do-i-need-both",category:"seo-vs-geo",question:"Why isn't standard SEO enough anymore?",answer:"Standard SEO is still foundational, but it cannot tell you whether an AI answer mentions your brand, cites your page, or sends the source opportunity to a competitor. GEO adds that evidence layer across tracked prompts and engines; NimbleSEO keeps both lanes together so one technical or content improvement can be evaluated in search and in AI answers without maintaining two toolchains.",lane:"both",links:[{label:"Run a technical audit",href:"/technical",appOnly:!0},{label:"Open AI Visibility",href:"/ai-visibility",appOnly:!0}],surfaces:["public","app","pricing"],updated:"2026-07-17"},{slug:"ai-share-of-voice",category:"seo-vs-geo",question:"How is AI share of voice calculated?",answer:"AI share of voice is your weighted share of brand mentions and citations across the tracked non-branded prompts, engines, and selected time window. The result is shown with the run count, engine mix, capture dates, and confidence state; branded prompts are reported separately so asking an engine about your own name cannot inflate the headline number.",lane:"geo",links:[{label:"Read the measurement standard",href:"/methodology/ai-visibility"}],surfaces:["public","app","pricing"],updated:"2026-07-17"},{slug:"ai-source-refresh",category:"seo-vs-geo",question:"How often do LLMs update their sources?",answer:"There is no universal refresh schedule: source selection can change with the provider, model, interface, region, account state, and time. NimbleSEO does not claim to control that cadence. It reruns prompts on the schedule included in your plan, timestamps every capture, records the capture method, and labels unstable results so you can distinguish a durable change from normal answer variance.",lane:"geo",links:[{label:"See capture methodology",href:"/capture"}],surfaces:["public","app","pricing"],updated:"2026-07-17"},{slug:"competitor-tracking",category:"seo-vs-geo",question:"Can I track competitors in AI answers?",answer:"Yes. Add the rivals you care about and NimbleSEO compares mentions, citations, answer position, engine coverage, and the third-party sources that influence the same prompts. It uses public or connected evidence rather than private competitor data, and every sample result remains explicitly labelled until your own captures are connected.",lane:"geo",links:[{label:"Open Competitors",href:"/competitors",appOnly:!0}],surfaces:["public","app","pricing"],updated:"2026-07-17"},{slug:"actionable-content-suggestions",category:"seo-vs-geo",question:"Will I get actionable content suggestions, not just charts?",answer:"Yes. Prompt gaps, cited-source evidence, page findings, and competitor patterns feed a ranked list of next steps and content briefs with the reason and evidence attached. You review every recommendation before publishing, applied technical fixes are reversible, and a follow-up run can check whether the observed visibility changed without claiming that the action caused it.",lane:"both",links:[{label:"View the labeled demo",href:"/demo"}],surfaces:["public","app","pricing"],updated:"2026-07-17"},{slug:"no-black-hat",category:"accuracy-honesty",question:"Does NimbleSEO use black-hat tactics to influence AI answers?",answer:"No. NimbleSEO does not cloak pages, fabricate citations, create fake reviews, or recommend spam. It helps teams improve inspectable content, technical accessibility, source qual

2ity, and entity clarity; recommendations remain human-reviewed and outcomes are never guaranteed.",lane:"both",links:[{label:"Read the trust centre",href:"/trust"}],surfaces:["public","app","pricing"],updated:"2026-07-17"},{slug:"which-ai-engines-tracked",category:"seo-vs-geo",question:"Which AI engines do you track?",answer:"We track brand mentions and citations across ChatGPT, Claude, Gemini, Perplexity, Grok, Microsoft Copilot, DeepSeek, Meta AI, You.com, and Phind. Google AI Overviews and AI Mode presence is tracked separately in the search-results lane, not as an answer-engine adapter. Each engine’s capture method (bare API model, search-grounded API, or manually seeded) is disclosed rather than hidden behind one platform count, and coverage is a sample of prompts per engine, not a census of every possible AI answer — the methodology page documents exactly how the sampling works.",lane:"geo",links:[{label:"How AI visibility is measured",href:"/methodology/ai-visibility"},{label:"Capture fidelity per engine",href:"/capture"}],surfaces:["public","app"],updated:"2026-07-10"},{slug:"what-is-a-citation",category:"seo-vs-geo",question:'What is a "citation" and how do you count it?',answer:"A citation is an instance where an AI engine references your brand or domain in its generated answer to a sampled prompt. We extract the engine, the prompt, and the matched evidence so each counted citation is traceable to a real result. We do not infer citations you cannot inspect — if we cannot show the evidence, we do not count it.",lane:"geo",links:[{label:"Open AI Visibility",href:"/ai-visibility",appOnly:!0},{label:"Citation terms in the glossary",href:"/glossary"}],surfaces:["public","app"],updated:"2026-06-30"},{slug:"capture-modes-differ",category:"seo-vs-geo",question:"Are all AI-engine checks captured in the same way?",answer:"No. A bare provider API model, a search-grounded API, and a real consumer browser session can return different answers to the same prompt. NimbleSEO keeps those populations separate and publishes the capture mode for each engine rather than hiding the difference behind one platform count. Google AI Overviews and AI Mode are measured in the search-results lane.",lane:"geo",links:[{label:"See the capture-fidelity matrix",href:"/capture"},{label:"Read the AI-visibility methodology",href:"/methodology/ai-visibility"}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"prompt-universe-selection",category:"seo-vs-geo",question:"How do I choose which prompts to track?",answer:"Start with the decisions and questions that matter to your customers, then expand each topic into realistic phrasings, intents, and follow-ups. That set is your prompt universe. Keep branded prompts separate from non-branded discovery prompts, preserve the set over time for comparability, and add new prompts as a new cohort rather than silently rewriting history.",lane:"geo",links:[{label:"Prompt-universe definition",href:"/glossary#prompt-universe"},{label:"Open AI Visibility",href:"/ai-visibility",appOnly:!0}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"why-repeat-ai-checks",category:"seo-vs-geo",question:"Why do AI-visibility checks need repeated runs?",answer:"AI answers vary between runs, so one response is evidence of one response — not a stable rate. Repeats let the platform estimate stability, effective sample size, and a Wilson confidence interval. Correlated repeats are down-weighted, and a result stays inconclusive when there is not enough defensible evidence.",lane:"geo",links:[{label:"How uncertainty is calculated",href:"/methodology/ai-visibility"},{label:"Wilson interval in the glossary",href:"/glossary#wilson-ci"}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"ai-traffic-and-revenue",category:"seo-vs-geo",question:"Can NimbleSEO measure traffic or revenue from AI answers?",answer:"It can connect retained citation evidence with first-party analytics and reporting signals when those sources are available, but attribution is not automatically proof of cause and effect. A cited answer, a later visit, and a conversion can support a traceable evidence chain; they do not prove the citation caused the conversion. Missing analytics data is shown as unavailable rather than estimated into a customer result.",lane:"geo",links:[{label:"Open Reports",href:"/reports",appOnly:!0},{label:"Read the methodology",href:"/methodology"}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"where-does-data-come-from",category:"data-byok",question:"Where does your data come from?",answer:"Search and ke

2yword data come from third-party SERP/keyword providers (such as DataForSEO); your own performance data comes from Google Search Console and GA4 once you connect them; technical findings come from a live crawl of your pages; and AI-visibility data comes from sampled prompts run against AI engines. Each surface tells you which of these it is using.",lane:"both",links:[{label:"Open Integrations",href:"/integrations",appOnly:!0}],surfaces:["public","app"],updated:"2026-06-30"},{slug:"can-i-bring-my-own-keys",category:"data-byok",question:"Can I bring my own API keys (BYOK)?",answer:"Workspaces can save their own AI provider keys (such as Anthropic or OpenAI) for generation, so those model calls run on your provider quota and you pay the provider directly. Automatic scheduled routing of monitoring checks through customer keys is still being proven end to end, so we do not sell it yet.",lane:"both",links:[{label:"Open Integrations",href:"/integrations",appOnly:!0}],surfaces:["app"],updated:"2026-07-10"},{slug:"byok-shared-cache",category:"data-byok",question:"If I bring my own keys, does my data touch the shared cache?",answer:"No. A workspace using its own provider keys runs against your provider quota and is isolated to your tenant — your BYOK requests do not read from or write to the shared keyless cache. Row-level security keeps every workspace’s data separated regardless of which keys it uses.",lane:"both",links:[{label:"Open Integrations",href:"/integrations",appOnly:!0}],surfaces:["app"],updated:"2026-07-10"},{slug:"data-labels-explained",category:"data-byok",question:'What do the "Sample", "Works keyless", "Connect to run" and "Measured" labels mean?',answer:'These four labels tell you exactly how real a number is. "Sample" is illustrative data shown before you connect a source. "Works keyless" runs live on your own input without any connection. "Connect to run" means the feature needs a connected source (e.g. GSC) before it returns results. "Measured" is your real connected data. We never show sample data without the Sample label.',lane:"both",links:[{label:"Open Integrations",href:"/integrations",appOnly:!0}],surfaces:["public","app"],updated:"2026-06-30"},{slug:"proprietary-search-index",category:"data-byok",question:"Does NimbleSEO own a web-scale keyword or backlink index?",answer:"No. NimbleSEO does not claim an Ahrefs- or Semrush-scale proprietary web index. Keyword, SERP, backlink, and local-search coverage uses configured third-party providers; your first-party performance comes from connected sources such as GSC and GA4; and technical findings come from the product crawler. Provider-backed metrics inherit the provider’s coverage and refresh limits.",lane:"seo",links:[{label:"Open Integrations",href:"/integrations",appOnly:!0},{label:"Read data-source labels",href:"/methodology"}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"data-refresh-cadence",category:"data-byok",question:"How fresh is the data?",answer:"Freshness depends on the source and the run you schedule. Live crawls and explicit checks record their run time; connected analytics follow the source’s reporting delay; provider metrics follow that provider’s refresh cadence; and AI-answer observations are tied to a prompt, engine, capture mode, locale, and timestamp. The interface should show the observation window rather than implying everything is real time.",lane:"both",links:[{label:"Read the methodology",href:"/methodology"}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"export-and-api-access",category:"data-byok",question:"Can I export my data or use an API?",answer:"Reports and supported result tables can be exported for analysis and client delivery. API, webhook, and warehouse automation are available only on eligible plans or configured workspaces; their presence in the codebase does not make them part of every plan. Check the current plan contract or contact sales for the exact endpoint, retention, and volume requirements you need.",lane:"both",links:[{label:"Compare plans",href:"/pricing"},{label:"Open Reports",href:"/reports",appOnly:!0}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"how-accurate",category:"accuracy-honesty",question:"How accurate are your numbers?",answer:"As accurate as their source, and we label that source so you can judge it. Measured numbers come from your connected GSC/GA4 or a live crawl. Sampled numbers (like AI visibility) come from a defined prompt sample with a confidence band. Modelled numbers (like a bill projection or a forecast) are estimates from a documented model. We do not present any of these as more certain than they are.",lane:"both",links:[{label:"Read the methodology",href:"/methodology"}],surfaces:["public","app"],updated:"2026-06-30"},{slug:"measured-vs-sampled-vs-modelled",category:"accuracy-honesty",question:"What is the difference between measured, sampled, and modelled data?",answer:"Measured is real data read from a source you connected. Sampled is computed from a representative subset 

2(for example, AI visibility samples prompts across engines) and carries a confidence band. Modelled is an estimate produced by a documented formula (for example, the bill projection from your usage). Each surface states which kind it is showing rather than blending them into one figure.",lane:"both",links:[{label:"Read the methodology",href:"/methodology"}],surfaces:["public","app"],updated:"2026-06-30"},{slug:"do-you-invent-rankings",category:"accuracy-honesty",question:"Do you ever invent rankings or citations?",answer:"No. If a ranking has not been fetched yet, the keyword shows as pending — not a placeholder position. If an AI citation cannot be backed by inspectable evidence, it is not counted. Our first rule is that sample, heuristic, or computed output is never presented as measured or live; where we cannot show the real thing, we say so.",lane:"both",links:[{label:"Open Rankings",href:"/rankings",appOnly:!0},{label:"Open AI Visibility",href:"/ai-visibility",appOnly:!0}],surfaces:["public","app"],updated:"2026-06-30"},{slug:"why-sample-or-connect",category:"accuracy-honesty",question:'Why does a metric say "Sample" or "Connect to run"?',answer:'Because that surface needs your data to produce a real result and you have not connected it yet. "Sample" lets you preview the layout with illustrative figures; "Connect to run" means the feature stays inert until you wire up the source it depends on. Connecting GSC, GA4, or a crawl replaces the sample with your measured data.',lane:"both",links:[{label:"Connect a source",href:"/integrations",appOnly:!0}],surfaces:["public","app"],updated:"2026-06-30"},{slug:"how-is-lift-labelled",category:"accuracy-honesty",question:"How do you label AI-visibility lift?",answer:"As matched-control lift, never as proof of cause. When we report a change after an action, we compare against a matched control set and label the result that way. A matched-control comparison is evidence of association, not proof that the action caused the change — so we report the association and stop there.",lane:"geo",links:[{label:"Read the methodology",href:"/methodology"}],surfaces:["public","app"],updated:"2026-06-30"},{slug:"recommendations-not-autopilot",category:"accuracy-honesty",question:"Does the platform make decisions or publish changes automatically?",answer:"Not by default. NimbleSEO can prioritize actions, draft changes, and dispatch supported workflows, but consequential changes should pass through the visible preview and approval path. The AI companion is advisory, and a generated recommendation is not treated as an applied, published, or verified result.",lane:"both",links:[{label:"Review the find → fix workflow",href:"/technical",appOnly:!0},{label:"Open the command deck",href:"/",appOnly:!0}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"current-product-limits",category:"accuracy-honesty",question:"What are the important product limitations?",answer:"AI visibility is a sampled observation, not a census of every personalized answer; third-party search and link metrics depend on provider coverage; browser capture can be policy- and spend-gated; and not every additional tool in the wider application is part of the default launch workflow. NimbleSEO does not own a web-scale index, does not prove causation from an observational lift, and does not promise rankings or citations.",lane:"both",links:[{label:"Capture-fidelity matrix",href:"/capture"},{label:"Current product facts",href:"/facts"},{label:"Read the methodology",href:"/methodology"}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"what-ai-assistant-can-answer",category:"ai-assistant",question:"What can the NimbleSEO AI assistant answer?",answer:"The signed-in companion can explain product concepts, the current surface, measurement labels, supported workflows, billing rules, and practical next steps. Its product answers are grounded in the same FAQ, page-help, glossary, facts, methodology, and plan sources used by the interface. Workspace-specific analysis still depends on the context and evidence the current surface provides.",lane:"both",links:[{label:"Open the in-app help center",href:"/help",appOnly:!0},{label:"Read canonical product facts",href:"/facts"}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"ai-assistant-cost",category:"ai-assistant",question:"Does asking the AI assistant cost credits?",answer:"FAQ and help searches are deterministic retrieval and cost 0 credits. Local navigation and supported visible page actions in the companion also cost 0 companion credits. A free-form model answer costs 1 managed credit, or 0 managed credits when an eligible workspace uses its connected Anthropic key. The interface disclose

2s the charge before the answer path is used.",lane:"both",links:[{label:"See credit costs",href:"/pricing"},{label:"Search the help center for free",href:"/help",appOnly:!0}],surfaces:["public","app","pricing"],updated:"2026-07-17"},{slug:"ai-assistant-sources",category:"ai-assistant",question:"How do you stop the AI assistant from inventing product answers?",answer:"The assistant retrieves a small set of approved product sources before it calls a model, treats page and customer content as untrusted context, and is instructed to say what is missing when the sources are insufficient. It must not invent routes, buttons, plan rules, actions, or evidence. Important billing, legal, security, and measurement answers link back to their canonical source so you can verify them.",lane:"both",links:[{label:"Canonical product facts",href:"/facts"},{label:"Trust centre",href:"/trust"},{label:"Methodology",href:"/methodology"}],surfaces:["public","app"],updated:"2026-07-17"},{slug:"ai-assistant-all-questions",category:"ai-assistant",question:"Can the AI answer every question a customer might ask?",answer:"It can cover questions documented by the approved product knowledge base, but no responsible assistant can promise every possible answer. When the evidence is missing, account-specific, legal, or security-sensitive, it should say so and route the user to the correct support, privacy, security, or sales channel. 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