Alignment made language models safe enough to deploy. Murphy does the equivalent for the physical world. We find how a robot’s AI fails before it ships, then turn those failures into the evidence it takes to clear safety, certification, and insurance.
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.
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.
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.
Proof that the exact system you’re deploying is safe, certifiable, and insurable.
Clear the safety, certification and procurement gate, with proof, before go-live.
Put learned robots next to your people — with the evidence to back it.
The independent evidence regulators and insurers now expect.
We’re working with a small number of warehouse-robotics teams. If you build or deploy learned manipulation policies, let’s talk.
Get in touch →