RL environments
Resettable workflows with tool access, task state and outcome checks.
For AI labs
Environments for the capability you’re building.
Tell us the workflow, tools and outcome your agent needs to master. We’ll scope the environment with your team.
What we can scope
Define the task. Set the outcome.
The workflow, tools and scoring criteria define what the agent needs to learn.
Post-training data
Task-specific examples built from connected records, decisions and outcomes.
Evaluation sets
Held-out cases with defined evidence, expected outputs and scoring criteria.
Capability-specific data
A focused data search around the model behavior or domain you need to improve.
What helps us assess fit.
The capability or model behavior you want to improve.
The records, tools and context the model should receive.
The outcome or failure you need the evaluation to distinguish.