AI Enablers

Everything you need to build, ship and roll out AI.

Two ways to build private AI on-device, a members Studio to design and license it, and the enablement toolkits and Academy to help an organisation actually adopt it.

Build on-device AI

One engine, one Studio

Build on the model-agnostic Edge Runtime, extend it across every OS's built-in AI with Lybo OS — then design, simulate and license it all in Edge Studio.

Edge Runtime & Lybo OS — how they fit together

Edge Runtime — the engine

LyboAI's model-agnostic on-device agent engine. It ships nomodel of its own — a deterministic tier always answers, then it downloads a small model or bridges any external engine (llama.cpp, Ollama, Core ML). This is the base you build on.

Lybo OS — the extension

The same runtime, extended: register each platform's built-in AI (Gemini Nano, Apple Foundation Models, Phi Silica) as a governed routing tier, and join an A2A mesh so agents talk device-to-device up to a cloud hub. Not a separate product.