The independent safety & certification layer for embodied AI.
Model alignment made language models trustworthy. Murphy does the equivalent for the physical world. We surface how an embodiment fails before it ships, and turn that into the proof it takes to clear safety, certification, and insurance.
Find what breaks. Map the standards. Turn it into proof.
Find what breaks, before it ships.
We build the scenarios that break an embodiment, in simulation and on real hardware, and surface the edge cases and failures long before it reaches your floor.
Failures become training data.
Every failure we surface becomes training data, and we hold the growing library to train from. A small dose of the right edge cases changes deployment outcomes dramatically.
A standards brain that keeps up.
Standards and regulations never stop changing. We hold a deep bank of failure data and heuristics, and backsolve compliance and certification from the rules as they evolve.
Training on a small dose of the right edge cases lifted real-world task success from 5% to 75% in published results. That library is the asset we build.
The end result: proof that the exact system you’re deploying is safe, certifiable, and insurable.
Robot makers
Clear the safety, certification and procurement gate, with proof, before go-live.
Operators & 3PLs
Put learned robots near your people with evidence.
Certifiers, insurers & regulators
The independent evidence the emerging bar requires.
Built by engineers from Princeton
Alignment you can prove — not hope for.
We’re working with a small number of warehouse-robotics teams. If you build or deploy learned manipulation policies, let’s talk.
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