Polymath

AI agents are expected to perform useful work over long horizons with little or no human supervision, but achieving this requires training in environments that closely reflect the real world. Model labs pushing the frontier of agent capabilities need realistic simulation environments, data, tasks, and verifiers to improve agent reliability and autonomy. Without such environments, agents cannot be properly trained or evaluated for the kind of extended, independent operation that future applications will demand.

Polymath is a data lab that builds simulation environments where agents can practice and learn through experience, mirroring real-world conditions. Its offerings span applications and services, data, tasks, verifiers, and agents, forming a pipeline to train and evaluate autonomous AI systems. Polymath works directly with leading model labs to advance agent capabilities, positioning itself as an infrastructure and data partner for frontier AI development.