Algorithmic safety validation tools for autonomy.
As autonomy moves into complex safety-critical domains (e.g., aviation), failures become more costly and companies must devote significant in-house effort to validate their system before real-world deployment. Valgo accelerates autonomous systems development and certification by providing tooling to perform algorithmic safety validation at scale. We are building a platform to efficiently find rare and realistic failure events in simulation at a fraction of the compute cost required by existing approaches. Our tools are agnostic to models/simulators (i.e., black box) and can be applied across industries such as autonomous vehicles, aviation, robotics, space, defense, energy, and finance.
Valgo was founded by Stanford PhDs who wrote the textbook and taught the course at Stanford on algorithmic safety validation. We also have significant industry experience working on an FAA-certified collision avoidance system at MIT Lincoln Laboratory, validating autonomous aircraft at Xwing, and collaborating with industry sponsors across transportation, aviation, and energy.