ENTERPRISE AI INFRASTRUCTURE
Train Agents on Business Outcomes
Custom World models that test and optimize your agents on real production scenarios.
THE PROBLEM
100 tests pass in staging. Customer #1 breaks it.
- •Multi-step negotiations
- •Partial information workflows
- •Your specific business logic
- •$50-150K/year maintaining tests
- •Can't catch edge cases
- •Can't optimize what you can't simulate
You tested generic benchmarks. Not your actual environment.
OUR APPROACH
World Models: Robotics → Your Stack
Robotics simulates physics before deployment.
We do the same for your AI agents.
We embed first. Watch your agents in production.
Train a world model of YOUR environment: APIs, data patterns, edge cases.
Result: A digital twin that generates unlimited test scenarios and enables RL optimization.
We Embed
- • SDK wraps agent calls
- • Collect production traces
- • Learn your environment
Model Trains
- • Simulates realistic responses
- • Generates comprehensive scenarios
- • Captures YOUR edge cases
Continuous Optimization
- • Test pre-production
- • RL on business metrics
- • Validate before rollout
The Embedded RL Wave
Agents are hitting production. Companies need custom evals that match their environment not generic benchmarks.
Model makers won't embed with every enterprise. This supports deep relationships and forward-deployed expertise.
We're first.
Join the First 10
Onboarding 10 design partners Q1 2026. Deploying production agents?