Valgo
Winter 2026Algorithmic safety validation tools for autonomy.
About Company
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.
Active Founders
Stanford CS PhD with thesis on algorithms to validate safety-critical systems. Former research staff at MIT Lincoln Laboratory on the core team that designed and validated the aircraft collision avoidance system (ACAS X), now a worldwide standard. Other relevant experience working at Xwing (an autonomous aircraft startup now part of Joby Aviation), and NASA Ames Research Center.
Stanford Aero/Astro PhD with thesis on safe machine learning. Author of "Algorithms for Validation" textbook. Lecturer for "Validation of Safety-Critical Systems" course at Stanford. Industry experience at Reliable Robotics, MIT Lincoln Laboratory, Johns Hopkins Applied Physics Laboratory, and NASA.