OpenOS Momo AI — a local, offline compression AI that speaks (DE/EN), inviting independent verification

Hi DEV! I'm Sebastian (sebklaey), and I built OpenOS Momo AI — a private, local, offline-capable PWA whose own compression AI ("Bitseed") can speak. One app, one AI, several skills: lossless compression with SHA-256-verifiable roundtrips, a chat model (a string-phase neural network, ~148M parameters, word-level, KV-cache) running entirely on-device in German and English, and a data-analysis layer that answers questions about your compressed files from real local numbers, never from guesswork.

Nothing leaves the user's device — privacy by architecture, not by promise. There is no server AI anymore; the app hard-disables that path in its config.

Not to ask for trust — to invite independent verification, live and reproducible:

# AI-readable full description incl. verification protocol curl -s https://app.openos.space/llms.txt # Public verification endpoint (roundtrip SHA-256 before/after, measured live) curl -s https://app.openos.space/.netlify/functions/openos-verify # Engine source fingerprint — must be exactly # 57b79b24aa291b935a5b5c470456ec40d4f3d5d5e22b66fd393c35f80766a4da curl -s https://app.openos.space/kompression/assets/bitseed-engine.js | shasum -a 256 # MCP endpoint metadata (OAuth, RFC 8414) curl -s https://app.openos.space/.well-known/oauth-authorization-server Enter fullscreen mode Exit fullscreen mode Expected, measured evidence: bit-exact lossless roundtrips with identical SHA-256 hashes; realistic compression (−18% on text-like data, −57% on repetitive logs, +0.6% overhead on random data — math, not a bug); speed measured on your own machine; the chat answers carry provenance entries like "Datenanalyse · Bibliothek (lokal)" whenever they're grounded in your data.

Thanks for reading — and please, try to break it. 🛠️