VISION & PROTOCOL

Building the semantic infrastructure for physical AI.

THE PROBLEM

Robots fail not because they can't see or grasp — they fail because they don't know what success looks like.

Current systems lack explicit knowledge of:

  • • What states matter
  • • When a task is complete
  • • What can go wrong
  • • How to recover

This knowledge exists in manuals. But it's locked in PDFs, inaccessible to machines.

OUR SOLUTION

We extract procedural knowledge into machine-readable task graphs. States. Constraints. Failure modes. Recovery paths.

The result: robots that know what they're trying to achieve, not just what motions to make.

WHY NOW

Humanoid deployments accelerating in 2026-2027

Foundation models need structured grounding, not just video

Regulators demanding explainable robot behavior

Teleop doesn't scale — procedural knowledge does

WORK WITH US

We partner with robotics labs, foundation model teams, and simulation engineers.

PILOT ACCESS

Evaluate our data in your stack. Single category, 30 procedures.

RESEARCH

Academic partnerships, benchmarks, co-authorship.

ENTERPRISE

Full corpus, custom extractions, priority support.

Built with precision by the Syngraph Team. 2026.