Bespoke Labs builds the infrastructure and realistic, company-scale reinforcement learning environments needed to train AI agents for long-running, real-world tasks. Its platform combines an environment engine, a high-throughput sandboxing layer, and an agent-optimization layer that uses the GEPA evolutionary algorithm to tune prompts and policies, enabling agents to learn from and be evaluated on multi-step workflows. It differentiates itself by delivering end-to-end production-grade training infrastructure for frontier AI labs and enterprises, while contributing open benchmarks like Terminal-Bench and datasets like OpenThoughts to the broader community. The goal is to reduce AI agent unreliability in real-world settings and become a key partner for companies building agentic AI at scale.
Company Size
51-200
Company Stage
Series A
Total Funding
$40M
Headquarters
Mountain View, California
Founded
2024
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