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Unify docs, chats, tickets, CRM records, and system state into a queryable graph. Agents traverse relationships to answer questions humans ask in whole sentences — not keyword queries.
Most enterprise knowledge is locked inside a dozen disconnected tools. A knowledge graph unifies them into a typed semantic model — entities, relationships, temporal facts — so agents can reason over what's true, not just what's indexed.
Connectors for Confluence, Notion, Slack, Drive, SharePoint, Salesforce, ServiceNow, Jira, and your product databases. All content is entity-resolved and linked.
People, projects, accounts, and artifacts are merged across sources. Aliases collapse, ownership is attributed, and timestamps track when each fact became true.
Agents translate natural language into graph traversals and SQL, combining structured and unstructured context to answer questions no single system could.
'Who owns the service that handles GDPR exports for our EU customers?' — one query, three hops, cited answer.
Every fact is time-stamped. Ask 'what was X's status last quarter?' and get a point-in-time answer, not today's view.
The graph respects source-system permissions. Agents never surface content a user wouldn't be allowed to see in the underlying tool.
Your domain ontology guides extraction from unstructured text — 'contract', 'SOW', and 'MSA' converge on the same entity instead of three noisy clusters.