Endgame

Endgame is a platform that constructs a structured context graph for go-to-market (GTM) teams, enabling both human agents and AI agents to access and act on organized knowledge derived from their daily operations. The system ingests raw data from multiple sources—including sales calls, deal records, playbooks, customer interactions, and internal documentation—and transforms it into a unified, queryable knowledge base. This context graph captures relationships among people, accounts, stages, signals, and actions, allowing teams to surface relevant insights without manual effort. One of its core functions is processing every sales call into structured knowledge: it extracts key topics, objections, buyer personas, decision criteria, and sentiment, then links them to specific deals, accounts, and playbook stages. The same pipeline handles deal records—such as pricing decks, renewal runbooks, strategic saves, and stage rules—and converts them into actionable signals. For example, when a call transcript reveals a new competitor mention or a change in budget, Endgame updates the graph automatically, making that information available to the relevant sales, marketing, or success agents. The context graph also models account hierarchies, buying groups, and individual roles. It can tag contacts with profiles (e.g., champion, economic buyer, detractor, new lead) and map their relationship to the deal lifecycle. Meddic and median frameworks are supported: users can define ICP (ideal customer profile) criteria for enterprise or mid-market segments, apply stage rules, and track progression through discovery, demo, pricing, and close. The system learns from historical data to suggest next-best actions—like when to send a pricing deck or schedule a strategic save meeting—without relying