Your AI doesn't know
who to route to. what to approve or dismiss. who's the right alternative. when to assign or escalate.

BehaviorGraph is the behavioral context layer for enterprise AI. It turns collaboration patterns, relevance signals, pulse surveys, and workflow data into a queryable layer that enterprise search, AI agents, and governance platforms can use at runtime to find the right person, route decisions correctly, and escalate with full context.

Enterprise AI reads documents and org charts, but doesn't know how the organization actually works. Who do people rely on? How do decisions route in practice? Where do bottlenecks form? This missing behavioral layer causes AI to misroute work, miss the right person, and stall on escalation.

Tacit knowledge is what people know but don't write down: who actually handles APAC contracts, which team boundary always stalls handoffs, who to go to when the usual person is overloaded. Today's AI reads documents and org charts but is blind to how work actually flows. BehaviorGraph captures tacit knowledge at scale using a research-backed framework grounded in behavioral science and organizational network analysis, tested in real enterprise environments. The result: organizational intelligence your AI can query at runtime, from six data sources you already have, privacy by design.

BehaviorGraph plugs into your existing stack via REST API, MCP (Model Context Protocol), or RAG enrichment. It adds people context to every result: who actually owns a topic, who is available, and who to escalate to. Users find the right person, not just the right file.

No. BehaviorGraph operates on metadata only: collaboration patterns, calendar signals, presence data, and pulse survey responses. It never reads message content, emails, or documents. Privacy by design.

BehaviorGraph makes governance behavioral, not just rule-based. It knows when to escalate, who can approve, and when a human must decide. It routes within your approval structure, never around it. Every decision is auditable.

Collaboration patterns (calendars, meetings, presence), relevance and expertise signals (who peers rely on), lightweight pulse surveys (team health, readiness), workflow events (approvals, escalations, handoffs), and cross-team communication patterns. All metadata-only, connected via API.

No. BehaviorGraph works in three ways: (1) As an overlay on top of your existing enterprise search, enriching results with people context. (2) As a standalone context layer that your AI agents query directly via API or MCP. (3) As a full behavioral intelligence platform with its own routing, escalation, and governance capabilities. If you already have enterprise search, BehaviorGraph makes it better. If you don't, BehaviorGraph still provides the organizational context that search alone can't.

Your agents call our API or MCP tools before taking action. BehaviorGraph tells them who to route to (based on org chart authority combined with behavioral relevance), who's available as backup (when the primary is overloaded, with qualified alternatives suggested and a human in the loop for confirmation), and when to escalate (with the full decision path and approval chain). You can use this alongside agent platforms like LangChain or CrewAI, or directly through our API without any other platform. We cover the part others don't: the organizational context that makes routing decisions accurate.

Yes. Most companies start with one of three entry points: (1) Search enrichment for teams already using enterprise search. (2) Agent routing for teams deploying AI agents. (3) Bottleneck detection for operations or engineering leads who want to find where work stalls. You can also add our AI agent directly to Slack or other platforms so your team can ask questions like "who owns APAC vendor contracts?" right where they work. Or you can build BehaviorGraph into your own workflows through our API. Each connects to the same behavioral graph, so expanding to other use cases later requires no additional data setup.