Bespoke Labs

Founded by Mahesh Sathiamoorthy in 2023

Train and evaluate production AI agents using simulated codebases and reinforcement learning environments

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You can use Bespoke Labs to train and evaluate AI agents in realistic environments before deploying them to production. The system creates company-scale simulations featuring real codebases and microservices to test complex workflows. You can automatically refine prompts and policy configurations using evolutionary search algorithms through the GEPA engine. It also provides benchmark environments like Terminal-Bench to test agent capabilities systematically. Frontier research labs and engineering teams use this setup to ensure autonomous agents complete long-horizon tasks reliably without breaking actual enterprise systems.

What Bespoke Labs does

Simulate software environments for agent interactionRun automated evolutionary prompt tuningBenchmark agent performance on terminal tasksTrain models with reinforcement learning on real workflowsInspect and evaluate long-horizon agent decisionsCurate high-quality reasoning datasetsSimulate company-scale codebases and microservices for agent testingAutomate prompt and policy tuning using evolutionary search algorithmsEvaluate agents in production-like environments with Terminal-BenchAccess reasoning datasets curated for agent training workflowsTrain reinforcement learning agents on complex, long-horizon tasksBenchmark model capabilities against frontier industry standards