StageLab creates full synthetic ecosystems — rendered APIs, synthetic users, multi-agent environments — so you can test how your AI agents actually decide before they ever touch production.
Full REST/GraphQL APIs with realistic responses, latency profiles, error codes, and rate limits. Stage entire service graphs without touching staging infrastructure.
Generate synthetic users with real behavior patterns — churn on checkout, network dropout, ambiguous intent, multi-language edge cases. Not just happy paths.
Stage environments where multiple agents interact simultaneously. Test coordination failures, resource contention, message passing, and emergent behavior across agent swarms.
Score not just outcomes but decision paths. Understand why an agent failed — was it a reasoning error, a tool call mistake, or a context misunderstanding? Replay any step.
Run simulation suites in your pipeline. Gate deployments on pass/fail thresholds. Track quality regressions across every commit automatically.
Snapshot and diff synthetic worlds. Regress against a specific version of the environment. Roll back the simulation state without rebuilding from scratch.
Configure the simulation environment — API schemas, persona behavior, failure injection rules, and environment state. Or start from a template.
StageLab spins up the synthetic world and drives your agent through defined scenarios. Multiple parallel runs with different personas and edge cases.
Full replay of every decision step. See what the agent called, in what order, with what state. Score outcomes and decision quality independently.
Set pass/fail thresholds. Run in CI/CD. Every deployment gets a quality report. Agents that don't meet the bar don't ship.
StageLab stages the world. Your agents prove themselves before they matter.