LYBO OS Live Demo

One agent, written once · runs on every device's own AI
← lyboai.app/developers

1Pick a device

Imagine this same agent app installed on each. Which one are you holding?

2Pick a task

A real job you'd give the agent. LYBO OS runs the very same one on any device above.
Same signed skill pack — LYBO OS just picks the runtime.
OS providesLYBO OS adds
Every phone and PC now ships its own built-in AI — but each one is different, and none of them is safe to ship a real product on by itself. LYBO OS is one agent you write once: it uses whatever AI the device already has, fills in what that OS is missing, and keeps everything governed. Pick a device and a task on the left, then press Run and watch the same job play out.
1Device chosen
2Task chosen
3Press Run
4Read the result

What just happened

Model router — the live decision

LYBO OS looks at your device and the task, then picks the best "brain" available. Orange = the one it chose.

Capability map — leverage vs augment

Grey = features the OS already gives us (we lean on them). Orange = the governance and skills LYBO OS adds on top.

Agent session — the actual run

Your task goes in; a validated, structured answer comes back — on-device.
Press Run on this device to start the agent…

Guardrails — why it can't hallucinate into trouble

The safety rails that run on every request, so the agent is trustworthy in production.
Schema-first: outputs validated + repaired against a declared JSON schema Confidence gate: low-confidence → deterministic floor, never a guess Grounded: answers constrained to signed pack knowledge, not open web HITL consent: side-effecting tools (payments, messages) held for approval Glass-box trace: every route, skip, tool call and token logged with an id Eval gate: packs must pass an eval suite before signing/publish
Run a task to see the guardrail trace…

Central nervous system — three tiers, one mesh

The bigger picture: devices stay private and light; heavier reasoning rolls up only when needed.
this device · Tier 1 Edge (TLM/OS-AI)──▶ vehicle-node-3 · Tier 2 Node (SLM + local RAG)──▶ @cloud.hub · Tier 3 Core (LLM) field-tablet-02 kiosk-07
Tier 1 handhelds structure inputs locally (no raw audio upstream) → Tier 2 vehicle/site nodes aggregate, dedupe and answer from regional RAG → Tier 3 core consolidates high-signal summaries into business memory. Heavy compute only when deep reasoning is required — and the hub can never bypass on-device consent.