Live Environments for Training AI Agents
Powering frontier AI labs with real-world environments and complex, long-horizon agentic data.
Login & purchase are whitelist-only.
Infrastructure for agents that act in the real world
klavis gives labs the environments and data that static benchmarks can't — so agents learn to operate, not just answer.
Real-world environments
High-fidelity, sandboxed worlds that mirror production software, browsers, and operating systems — not synthetic toys.
Long-horizon tasks
Multi-step, stateful workflows that span hours of agent reasoning, tool use, and recovery from failure.
Dense agentic data
Every step, observation, and reward captured as clean trajectories ready for RL and supervised fine-tuning.
Built for scale
Spin up tens of thousands of parallel environments with low-latency stepping and deterministic replay.
Composable harness
Bring your own model or agent. A unified API for resets, actions, and evaluation across every environment.
Lab-grade isolation
Hard sandboxing, full audit logs, and private deployments keep frontier research contained and secure.
From environment to agentic data in three steps
Define the environment
Specify the world, tools, and success criteria — or pick from our library of production-grade environments.
Deploy your agent
Connect any model through a single API. Reset, step, and observe across thousands of parallel instances.
Harvest the data
Export clean, reward-labeled trajectories for reinforcement learning and evaluation — at lab scale.
“klavis is the only place we can train and evaluate agents on tasks that actually look like the work they'll do in production.”
Head of Agents Research · Frontier AI Lab
Build agents that operate in the real world
Access is whitelist-only. Tell us about your lab and we'll get you set up with environments and data.