Problem
Knowledge workers lose context after meetings and chats. Most assistants summarize one call, then forget it. Teams that need continuity across screen activity, voice notes, and follow-up tasks usually stitch together several paid tools. This creates context gaps, duplicate notes, and new privacy risk.
Solution
Omi records conversations and screen context, transcribes them in real time, and keeps a searchable memory timeline. It is MIT licensed and open source, so teams can inspect code and extend workflows. The platform includes desktop, mobile, and wearable clients, plus APIs and SDKs for custom automations. Instead of isolated summaries, Omi links notes, action items, and chat history into one system.
Self-Hosting
You can run Omi in your own environment for development and controlled deployments. The project documents a local stack with backend setup, environment variables, and app builds. This path needs engineering support, especially for keys, storage choices, and ongoing updates. If you want zero setup, the quick start also supports a cloud-backed mode.
Who It's For
Omi is best for technical teams, operators, and founders who need long-term memory across meetings and daily work. It also fits builders who want to create custom assistants on top of a shared context layer. It is less ideal for teams that want a closed, fully managed SaaS with no setup decisions.
Comparison
Compared with ChatGPT voice mode or Otter.ai, Omi gives deeper control over data flow, model choice, and integration logic. Compared with meeting-only tools like Fireflies, Omi combines conversation capture, screen context, and persistent AI chat in one open platform. The tradeoff is setup effort, since self-hosted deployments need technical ownership.
