trayn
Practice before production

The rehearsal layer for AI agents

Trayn turns real workflows into stateful, verifiable environments for training and evaluating AI agents across realistic task variations before deployment.

The reality

Real work is not a clean demo.

Agents break on the details: pop-ups, missing fields, UI changes, hidden steps, file attachments, detailed forms, messy states, and edge cases.

Trayn turns those moments — and any workflow — into training environments where agents can rehearse safely, repeatedly, and measurably before deployment.

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Capture · Construct · Train · Evaluate

How Trayn works

Capture

Record real workflows across tools and websites with context-preserving anonymization that runs entirely offline.

rec

Construct

Convert workflows into deterministic, interactive environments with replayable state transitions and trackable agent actions.

Train

Run agents through repeated reps using the Trayn SDK or CLI, with step-level grading and feedback after each attempt.

reps

Evaluate

Test across workflow variations to verify robustness against changing interfaces, inputs, interruptions, and environment states.

Build agents ready for real work.