RL-gyms for AI agents
Push your agent on context-rich simulated environments and specialized RL-gyms. Get high-fidelity trajectories and graded eval signals for training and evaluating AI agents at scale.
Harness-agnostic by design: use Toloka’s harness or yours — with grading hooks and user-LLM emulation.
Trusted by Leading AI Teams
What we build
How it works
Managed end-to-end environment and data operations.
Built by engineers, for engineers.
You share your goals, constraints and success criteria. We translate them in environments, trajectory schemas, rubrics, and QA plans.
Containerized testbeds with seeded data and instrumented trajectory capture, invariants,
and event log.
Domain experts execute seed tasks; we validate invariants, success metrics, and telemetry
to stabilize the environment.
We run demonstrations, targeted eval tasks, and long-horizon workflows to generate trajectories and graded eval signals.
QA AI Agent verifies trubric adherence, logical consistency, environment invariants, task completion, and structural integrity. Senior QAs audit complex, flagged, or sampled cases.
Receive versioned datasets, eval reports, and structured outputs ready for training and benchmarking. Always audit-ready.
Instrumentation and reproducibility
Where this applies
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Privacy, security, and reproducibility
Partner with Toloka
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Offload environment engineering, data collection, and QA operations to a team that does this full-time.
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Faster to first useful dataset; more flexible than hiring for bursty, specialized work.
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Depth in agentic data: instrumented, stateful environments—not just annotation.
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Hybrid QA that blends tool‑enabled checks with senior human judgment, tuned to your rubric.
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A rigorously vetted expert network with measurable quality controls.
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Audit-ready reproducibility: versioned environments, deterministic resets, and comprehensive logs.
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For Tau-style RL-gyms: calibrated difficulty targeting ~50% pass rate and a dedicated tri-role expert pipeline.
Read more on our dedicated blog article
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Trusted by Leading AI Teams