Omni is a self-hosted workplace search and agent layer that indexes tools like Google Workspace, Slack, Jira, Confluence, HubSpot, and local files with Postgres, ParadeDB, and pgvector. Omni is a useful find for teams that want Glean-style workplace search without sending every knowledge source into a closed SaaS stack. The project connects to common work tools, builds a shared context layer, and gives agents search, citation, and tool-use paths over company data. Best fit: technical teams that can self-host Docker services, already run Postgres, and want to test hybrid BM25 plus vector search before buying an enterprise search platform. What to check before using it: Confirm the connectors you need are production-ready, especially Microsoft 365, Notion, GitHub, or custom internal systems. Review permission inheritance against your own identity model before indexing private content. Decide whether your LLM provider keeps data inside your boundary; self-hosting the index does not automatically make hosted model calls private. Test Postgres, ParadeDB, and pgvector performance on a realistic document count. Treat the project as beta unless your own deployment test proves it can handle your security and uptime requirements. Area Omni angle Verification check --- --- --- Search BM25 plus vector search in Postgres Test recall against your real docs Agents Chat and tool use over indexed company data Review sandbox and permissions Hosting Self-hosted deployment path Validate backups, auth, and updates Lock-in Apache-2.0 repository Confirm license and active maintenance This is a tool to trial, not a blanket recommendation. Start with a small workspace, index non-sensitive sources first, and compare answer quality, latency, and review burden against your current internal search or RAG setup.

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