AI agent training gym
Turn real workflows into agent training gyms.
Studio turns one hard enterprise workflow into working tool simulations and realistic data, multi-step tasks, deterministic graders, and difficulty variants that stay near the factory-configured model's edge. Domain, evaluation, and infrastructure teams keep one shared handoff from brief to deployment.
Create a gym from your workflow20 graded tasks · 10 min target · 15 min p95
Structured creation brief
Make the task buildable before spending a factory run.Each required field maps directly to the canonical creation contract.Studio researches the domain, simulates the systems, generates 20 graded tasks, and lets you steer the build before release.
Fictional model-lab workflow
One shared room, from expert brief to cluster proof.
See how domain, evaluation, environment, and infrastructure stakeholders hand one environment forward without losing the decisions that make it useful for RL.
Capability hypothesisExample targets · remeasure after every train round
- Planning baseline
- 6 / 30 manual probes
- Studio admission
- ≥12 / 20 candidates
- Useful boundary
- 20–80% pass-rate band
Frame the capability boundary
The whole team agrees on the systems, the hard exception, the observable state change, and what the grader must prove before generation starts.
- 6 named systems stay in scope
- Cross-system reconciliation is required
- Success is a state change, not a prose answer