Bespoke Labs
by Bespoke Labs
Reinforcement-learning environments that train reliable, production-ready AI agents
Bespoke Labs builds realistic simulated business environments — codebases, microservices, logs, tickets, email and Slack — where enterprises and AI labs train and evaluate long-horizon agents before deploying them in production. It is aimed at AI teams and frontier labs that need agents to be dependable on real, economically meaningful workflows.
At a Glance
- Category
- Agent Development
- Pricing
- Contact for pricing
- Target Market
- AI/ML Engineers, Data Scientists, CTOs, AI Research Labs
- Founded
- 2024
- Headquarters
- Mountain View, California, USA
Key Features
- ✓Realistic RL environments
Simulated companies with codebases, microservices, logs, tickets, email and Slack that mirror real business settings.
- ✓Long-horizon agent training
Environments designed for economically meaningful, multi-step workflows rather than toy tasks.
- ✓Agent evaluation and measurement
Tools to test, measure and refine autonomous systems before production deployment.
- ✓Terminal-Bench contributions
Core contributor to Terminal-Bench, a widely cited benchmark for agentic coding capability.
- ✓OpenThoughts dataset
Open reasoning dataset downloaded hundreds of thousands of times and used across the AI research community.
Capabilities
Use Cases
- •Pre-production agent testing
Run agents against company-like environments to catch failures before deploying them on live systems.
- •Post-training with reinforcement learning
Use realistic environments to post-train models on long-horizon enterprise workflows.
- •Benchmarking agent reliability
Measure and compare agent performance on standardized, real-world-style tasks.
Ideal For
Best For
- ✓Training long-horizon AI agents on realistic enterprise workflows
- ✓Evaluating agent reliability before production deployment
- ✓Post-training and reinforcement learning for frontier and enterprise models
Integrations
Market Analysis
Pros
- ✓Realistic training environments improve agent reliability
- ✓Backed by respected AI investors and angels from Anthropic, OpenAI and Meta
- ✓Strong open-source and benchmark track record
Cons
- ✗Early-stage with limited public product details
- ✗Pricing not transparent
- ✗Targeted at sophisticated AI teams, not general users
Pricing
Enterprise
Contact for pricing
- ✓Custom RL environments
- ✓Agent training and evaluation
- ✓Dedicated research support
Pricing is not publicly disclosed; Bespoke Labs works directly with enterprise and frontier-lab customers.
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