We built an enterprise knowledge platform that indexes an organization's entire knowledge estate — wikis, drives, chat tools, legacy systems — and surfaces answers through a single AI-powered search bar, with permissions enforced at the retrieval layer.
Employees ask a question in plain language and get an answer, not a list of documents to open.
The average knowledge worker lost a quarter of their working week searching across disconnected systems — switching between wikis, intranet drives, chat tools, email and legacy systems to find information that should have been a single query away.
Existing enterprise search tools returned documents, not answers. And none of them enforced existing access permissions at the retrieval layer — meaning sensitive documents could surface for users who shouldn't see them.
Indexes every internal system the organization uses — wikis, drives, chat platforms, email and legacy tools — into a single, unified knowledge graph.
Every document's existing access permissions are enforced at the retrieval layer, not bolted on afterward — a user only ever sees what they already have access to.
Employees ask questions in plain language and receive answers — not ranked lists of links — with the assistant citing which systems and documents it drew from.
Beyond answering questions, the assistant can trigger actions — creating tickets, drafting documents, updating records — directly from the search interface.
Unified Knowledge Layer
One interface spanning every internal system — no switching, no separate search tools per platform.
Existing Permissions Enforced
Every access control already set in the source systems is respected at retrieval — no new permission layer to manage.
Time Lost to Searching
The average knowledge worker's quarter-week of search time, eliminated by a single natural-language interface.