We build the worlds your agents train in.
Theta is a specialized engineering lab. We clone real software into containerized RL environments with instrumented reward signals. Your team focuses on the model. We build the world it learns in.
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What we build for you. Bespoke environments, not off-the-shelf tools.
We don't sell tooling. We engage with your team, understand your agent's domain, and engineer the environments from scratch — cloned software, reward signals, adversarial conditions, and full telemetry. Delivered ready for your training pipeline.
How we work with you. A structured engagement from scope to scale.
Every environment we build starts with a deep scoping conversation. We don't guess at what your agent needs — we find out exactly, then build to that spec.
Step 01
You tell us the workflows
Share the target software and what your agent needs to master. We ask precise questions about the state space, action space, and success criteria to scope the environment correctly from the start.
Step 02
We design the environment spec
We produce a detailed spec covering the software to clone, state representations, action definitions, reward signals, failure modes, and curriculum structure. You review and approve before we build anything.
Step 03
We build and instrument
We clone the software, containerize it, wire up reward signals, and test the environment end-to-end. You receive a working environment — connected to your training pipeline and ready to run.
Step 04
We iterate as your agent improves
As your agent matures, the environment evolves with it. We add harder failure modes, expand the curriculum, increase instance counts, and refine reward signals based on what you observe in training.
Where we specialize. Three domains. Deep expertise in each.
We've built environments in these domains and understand the software, the failure modes, and the reward structures that matter. If your agent operates in one of these areas, we already know the terrain.
Customer service
Full replicas of CRM dashboards, ticketing systems, and live conversation flows. We cover ticket resolution, refund processing, user authentication, escalation handling, and multi-channel interactions. Your agent trains on the same interface it will operate in production.
Browser & computer use
Browser environments with full DOM access, form fields, navigation flows, and multi-tab task contexts. Desktop simulations covering file systems, spreadsheets, email clients, and SaaS applications. Built for agents that operate across the full GUI surface.
Enterprise workflows
Replicas of the workplace tools that enterprise agents need to operate in. We cover ticket creation, pipeline updates, document editing, message drafting, and complex multi-step workflows spanning multiple applications.
Built on one belief: environment quality determines agent quality.
Most teams build RL environments as an afterthought. We think that's why most agents fail in production.
Most teams treat environment engineering as infrastructure work — a cost center, not a core competency. We treat it as the job. Every reward signal, every failure mode, every state representation gets deliberate design attention.
We've built environments across multiple domains and know where the complexity hides. A team building their first RL environment will spend months on problems we've already solved.
We don't hand off a deliverable and disappear. We work alongside your team through training — adjusting reward signals, expanding failure modes, and scaling infrastructure as your agent's needs evolve.
Your agent is only as good as the world it trains in.
We work with a small number of teams at a time. If you're building production AI agents and need rigorous training environments, we'd like to talk.