Skip to main content

EdgeEmbed · Physical AI

Models predict. EdgeEmbed decides what machines are allowed to do.

EdgeEmbed is the AI-to-control bridge for physical AI — the deterministic layer between your AI model's intent and the controller that moves the machine. Every intent is gated against authorable safety policy, executed with real-time discipline, and recorded for bit-exact replay. The model can be uncertain. The gate is deterministic. The recorder remembers everything.

Explore the RuntimeExplore HIL
How it fits togetherDecide on the machine · Prove on the bench
On the machine — in production
AI model intentEdgeEmbed RuntimeThe gate decides. The recorder proves.PLC · controller · actuators
same deterministic behavior — proven before it ships
On the bench — in development
AI agent · CI · engineerEdgeEmbed HILHands and eyes on hardware — open sourceSimulator · real board

The bridge

Two worlds that don't speak the same language

The AI world speaks in probabilities — model intents, confidence scores, per-frame guesses. The control world demands determinism — a machine either stops or it doesn't, and someone must be able to prove why. Today's safety controllers decide deterministically, but only from hard-wired, classical inputs; none of them accept a model's confidence-weighted intent as an input class. That intake is the bridge EdgeEmbed builds: probabilistic AI intents in, policy-governed deterministic decisions out, with a record of why. EdgeEmbed does not replace AI stacks, PLCs, safety controllers, or robot controllers. It connects them.

What EdgeEmbed is

  • The AI-to-control bridge — the deterministic layer between the model and the machine
  • A Model Gate: every AI intent is checked against authorable safety policy before it can act
  • A flight recorder: every decision journaled for bit-exact replay and evidence
  • Driven by declarative config — safety behavior as data, on an ordinary core, no NPU

What EdgeEmbed does not replace — it connects

  • Not a model team or an inference runtime — model outputs enter as events; we never run inference
  • Not a PLC and not a safety PLC — vetted decisions leave toward the controllers you already trust
  • Not a robot controller or a motion planner
  • Not a certified safety system today — evidence-ready by design; the certification is yours, we co-develop the evidence

Products

Two products, one bridge

The runtime decides on the machine; HIL proves the behavior on real hardware. Each stands on its own — together they close the loop from AI intent to validated machine action.

EdgeEmbed Runtime

The gate decides. The recorder proves.

The deterministic engine at the heart of the bridge: AI intents and machine events in, one policy-governed, control-ready action out — every decision recorded and replayable.

Explore the Runtime

EdgeEmbed HIL · Open source

Hands and eyes for AI agents on hardware

The open hardware-in-the-loop protocol: discover a board, drive its pins, watch its logs, run bounded commands — with a local simulator so the first ten minutes need no hardware.

Explore HIL

Get in touch

Talk to us about your machine

Our mission is a trustworthy Decide stage in every machine that runs AI. Putting a model on a real machine, or bridging AI outputs into a PLC or robot controller? We would love to hear from you.

EdgeEmbed teamOnline — typically replies within a day
Hi — this is the EdgeEmbed team. Tell us about your machine, the AI you are putting on it, and what you need the bridge to do.