https://zime.ai/_next/static/chunks/pages/products/mcp-in-house-agents-1e5b1c3febcd3ad7.js

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Built a forecast agent. Started an RFP agent. Maybe even a content agent. But each one is rebuilding context from scratch. Zime exposes your GTM Context Model through MCP, so every in-house agent can use the same buyer language, deal context, CRO strategy, Winning Behaviors, and proof points.",cta:{...i,secondaryLabel:"See example workflows →"}},proofStrip:{},croProblem:{headline:"Six internal AI projects. Six context layers. [[No shared GTM brain]].",paragraphs:["Your agents may be technically live. But they still disagree because each one is working from different context.","Every new agent starts from zero. Every team rebuilds context. Every answer drifts."],pullQuoteAfterParagraph:1,bulletItems:["The forecast agent reads CRM fields.","The RFP agent reads old docs.","The content agent uses generic keywords.","The deal-desk agent misses call context.","The account-health agent cannot see what was promised in sales.","The support agent does not feed customer signals back into GTM."],bulletLayout:"grid",closingLine:"The bottleneck is not the model. It is the context layer."},howItWorks:{headline:"Build context once. Let every agent [[read from it]].",steps:[{title:"Distill org memory into a Context Model",body:"Zime's FDEs ingest CRO strategy, playbooks, call recordings, CRM data, decks, and tribal knowledge, then structure it into persistent GTM context."},{title:"Filter noise and capture signal",body:"Zime separates what matters from what does not: winning patterns, anti-patterns, competitor mentions, persona-specific objections, and recency-weighted deal signals."},{title:"Calculate Winning GTM Behaviors",body:"The model identifies which behaviors move deals forward by stage, product, persona, segment, and competitor."},{title:"Expose context through MCP",body:"Your Claude agents, custom agents, forecast agents, RFP agents, deal-desk agents, and content agents can query the same GTM brain."},{title:"Govern and improve continuously",body:"RBAC, lineage, redaction, approvals, and evals are built in. Every new deal, support signal, IVR topic, and agent output sharpens the Context Model."}]},exampleWorkflows:{headline:"What your agents can do with [[live GTM context]]",rows:[{agent:"SEO / GEO content agent",mcpAdds:"Prospect keywords, objections, competitor mentions, persona pain, call themes",exampleOutput:"Landing pages, comparison pages, AI-search answers, persona content"},{agent:"Forecasting agent",mcpAdds:"Deal stage, call evidence, unresolved objections, competitor risk, executed Winning Behaviors",exampleOutput:"Risk flags, forecast changes, deal-quality scores"},{agent:"Deal-desk agent",mcpAdds:"Pricing pressure, buyer urgency, competitor context, discount history, approval logic",exampleOutput:"Discount recommendation, approval route, commercial rationale"},{agent:"RFP / security agent",mcpAdds:"Approved messaging, proof points, product language, similar wins, buyer concerns",exampleOutput:"RFP answers, security responses, follow-up drafts"},{agent:"Account-health agent",mcpAdds:"Sales objections, support issues, IVR topics, renewal timing, product gaps",exampleOutput:"Renewal risk alerts, expansion signals, CS follow-up tasks"},{agent:"Support / IVR agent",mcpAdds:"Customer questions, repeated complaints, implementation issues, product confusion",exampleOutput:"GTM feedback loops, account risk signals, updated sales messaging"}],examplePrompts:["Create a GEO page for CIOs using keywords and objections from enterprise calls in the last 30 days.","Find late-stage deals where Zscaler was mentioned and the renewal question was not asked.","Review this discount request using call context, buyer urgency, competitor mentions, and pricing guidance.","Find accounts where integration issues came up in IVR or support and renewal is within 90 days."]},whyDifferent:{headline:"Most MCP servers expose data. Zime calculates and exposes [[Winning GTM Behaviors]].",intro:"Custom RAG, vector databases, and semantic catalogs can retrieve documents.",cannotKnow:["Which CRO priority applies.","Which persona changes the message.","Which competitor changes the play.","Which proof point worked before.","Which Winning Behavior should happen next.","Whether the recommendation was executed."],closingLine:"Zime gives agents the context behind the decision, not just the document behind the answer."},enterpriseReady:{headline:"MCP-native. Governed. [[Live in 7 days]].",intro:"Zime is built to fit the agentic stack you already have.",bullets:["MCP-native: Claude agents, custom agents, and MCP-compliant tools can query the C

1ontext Model.","API-ready: REST and SDKs for systems that are not MCP-native yet.","Governed: RBAC, lineage, retention, consent, and redaction enforced at the context layer.","Headless: Works across Slack, Teams, CRM, email, and internal tools.","FDE-led setup: Zime configures context, ontology, endpoints, and access rules with your GTM and platform teams."],timelineHeadline:"7-day path",timelineRows:[{day:"Day 0",detail:"FDE kickoff with GTM and platform teams."},{day:"Day 1–3",detail:"Calls, CRM, decks, support/IVR, and approved messaging ingested."},{day:"Day 4–5",detail:"Context validated. MCP endpoints and access rules configured."},{day:"Day 6",detail:"First agents read from the Context Model."},{day:"Day 7",detail:"Shared state verified. Lineage trail ready for governance review."}]},outcomes:{headline:"Built for the [[agentic AI roadmap]].",metricRows:[{outcome:"9-month enterprise AI ramp → 7-day time-to-impact across the portfolio",customer:"Enterprise AI programs"},{outcome:"3.5 → 1.9 fatal objections per call",customer:"Tenarai"},{outcome:"$30K → $397K+ ACV",customer:"Versa Networks"},{outcome:"250% NRR",customer:"15 logos"}]},teamsTellUs:{headline:"Hidden",clusters:[{title:"Hidden",body:"Hidden"},{title:"Hidden",body:"Hidden"},{title:"Hidden",body:"Hidden"}]},toolGaps:{headline:"Hidden",blocks:[{title:"Hidden",body:"Hidden"},{title:"Hidden",body:"Hidden"},{title:"Hidden",body:"Hidden"}],positionLine:"Hidden"},contextModel:{headline:"Hidden",intro:"Hidden",inputs:[{title:"Hidden",body:"Hidden"},{title:"Hidden",body:"Hidden"},{title:"Hidden",body:"Hidden"},{title:"Hidden",body:"Hidden"}],governanceLine:"Hidden"},playbookTimeline:{headline:"Hidden",rows:[{day:"Day 0",detail:"Hidden"}]},contextChanges:{headline:"Hidden",bullets:[{title:"Hidden",body:"Hidden"},{title:"Hidden",body:"Hidden"},{title:"Hidden",body:"Hidden"},{title:"Hidden",body:"Hidden"},{title:"Hidden",body:"Hidden"}]},aiStrategyCallout:{headline:"Hidden",bullets:["Hidden","Hidden","Hidden"],closingLine:"Hidden"},faq:{items:[{question:"Is this an MCP server we plug into Claude?",answer:"Yes. Zime exposes the Context Model as an MCP-native endpoint. Claude agents, custom agents, and any MCP-compliant tool can query it. We also provide standard APIs and SDKs for systems that are not MCP-native yet."}]},demoPreview:{headline:"Hidden",bullets:["Hidden","Hidden","Hidden"]},finalCta:{headline:"Stop building context six times. [[Build it once]].",subhead:"Bring one in-house agent or workflow: SEO/GEO content, forecasting, deal desk, RFP, account health, or support. In 7 days, Zime will connect it to your GTM Context Model through MCP and show outputs grounded in real calls, buyer language, CRO strategy, and Winning Behaviors.",cta:i},sections:{teamsTellUs:!1,toolGaps:!1,contextModel:!1,playbookTimeline:!1,contextChanges:!1,aiStrategyCallout:!1,demoPreview:!1,faq:!1}},d=()=>(0,a.jsx)(o.A,{config:s})}},e=>{e.O(0,[6742,9588,508,8010,6158,4215,636,6593,8792],()=>e(e.s=40862)),_N_E=e.O()}]);