Bespoke Labs

Founded by Mahesh Sathiamoorthy in 2023

Build and test AI agents in realistic company-scale environments

Cost

Demo

Rating

★ People love it

Time to value

Requires Expertise

You can use Bespoke Labs to build reinforcement learning environments that mirror your real production systems, letting AI agents train on actual codebases and workflows. It includes GEPA, an evolutionary algorithm that automatically searches for better prompts and policies without manual engineering. You can also evaluate agents against benchmarks like Terminal-Bench, access curated reasoning datasets like OpenThoughts, and work with their team to make AI agents reliable enough for real enterprise deployments.

What Bespoke Labs does

Create company-scale simulation environments for RL agent trainingRun automated prompt optimization using evolutionary search with GEPAEvaluate AI agents against standardized environment-based benchmarksCurate and access open reasoning datasets for model trainingTest agent reliability on long-horizon, multi-step workflowsTrain agents to handle production microservices and codebase tasksBenchmark agent performance across frontier model capability levelsAutomate policy search to find optimal agent behaviors without manual tuningCompany-scale RL environments built from real codebases and microservicesGEPA optimizer that uses evolutionary algorithms to automatically improve promptsTerminal-Bench: an environment-based benchmark for agentic systems, cited by Anthropic, OpenAI, and Google DeepMindOpenThoughts reasoning dataset with 10k+ monthly downloads on Hugging FaceCollaborative research track record published at ICLR 2026Automated policy search to replace manual prompt engineeringSupports both frontier AI labs and enterprise deploymentsLong-horizon workflow training for production-grade agents