Over the past few months, I've been working on building Omni - a workplace search and chat platform that connects to apps like Google Drive/Gmail, Slack, Confluence, etc. Essentially an open-source alternative to Glean, fully self-hosted.
I noticed that some orgs find Glean to be expensive and not very extensible. I wanted to build something that small to mid-size teams could run themselves, so I decided to build it all on Postgres (ParadeDB to be precise) and pgvector. No Elasticsearch, or dedicated vector databases. I figured Postgres is more than capable of handling the level of scale required.
To bring up Omni on your own infra, all it takes is a single `docker compose up`, and some basic configuration to connect your apps and LLMs.
What it does:
- Syncs data from all connected apps and builds a BM25 index (ParadeDB) and HNSW vector index (pgvector)
- Hybrid search combines results from both
- Chat UI where the LLM has tools to search the index - not just basic RAG
- Traditional search UI
- Users bring their own LLM provider (OpenAI/Anthropic/Gemini)
- Connectors for Google Workspace, Slack, Confluence, Jira, HubSpot, and more
- Connector SDK to build your own custom connectors
Omni is in beta right now, and I'd love your feedback, especially on the following:
- Has anyone tried self-hosting workplace search and/or AI tools, and what was your experience like?
- Any concerns with the Postgres-only approach at larger scales?
Happy to answer any questions!
The code: https://github.com/getomnico/omni (Apache 2.0 licensed)