The AI Brain behind every GTM agent
Part of Grow revenue with AIEvery GTM agent (outbound, expansion, marketing-to-sales, collateral) was re-discovering the world on each run. Account research re-scraped sites it scraped last week. The expansion-signal agent had no idea the prospect-research agent already noted the CEO change. Salesforce, HubSpot, Pendo, conversation transcripts, platform usage, health scores: each in its own silo. Duplicated cost, stale context, contradictory answers, zero institutional memory across agents.
Designed and shipped a central AI Brain: Graphiti on Neo4j 5, entities and facts stored with time validity so the graph answers what was true on date X and what changed. Event-driven ingest via Pub/Sub from Salesforce, HubSpot, Pendo, customer conversations, platform usage, and health scores. Query API every agent calls before and during its work; write-back contract so every agent commits what it learned. Freshness and confidence layer flags stale facts for re-fetch.
A single shared brain underneath every GTM agent: outbound, expansion, marketing↔sales, collateral. Agents start each run grounded in the latest truth across the business instead of re-scraping. The substrate that surfaces the invisible patterns (account changes, signal correlations, history) no single source could see on its own.
A shared context layer that several agents depend on is a full-system build with a Fractional AI lead tail to keep the schema and ingest contracts coherent as new agents come online. Start with an AI Transformation Sprint to pick the ontology and ship the first ingest slice before committing to the full build.
Others solving this in the wild
A small investment firm dropped Salesforce for a CRM it built with AI, and cut about $100K a year.
A four-person VC firm handed most of its work to AI agents, and now runs like a shop of 100.
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