Accurate, contextual, explainable search over everything your organization holds: structured and unstructured together, permissions respected by construction.
The graph expands the question before retrieval. That is where the accuracy comes from.
Enterprise search fails when it treats every document as an island. The graph makes the islands a map: a query about a project pulls its documents, owners, decisions, and dependencies because they are connected. Each result can show why it ranked, and never shows what the searcher isn't allowed to see.
A search for a project surfaces its documents, owners, decisions, and dependencies, because they are connected, not because they share keywords.
Results respect the searcher’s rights at query time. No leaking through the search index.
Why did this result rank first? Because of these connections, shown, not asserted.
Database rows, wiki pages, tickets, and contracts in one result set, linked by the entities they share.
How it's built, and the reproducible numbers behind it.
SDKs, query examples, and local setup: what's live and what's coming.
Five phases, honestly labelled: shipped, live, in development.
8 questions, free gap analysis against EU AI Act and SR 11-7.
Book a session and we’ll walk this use case end to end on real data: architecture, queries, and what a 90-day path looks like for your team.