About Relai
Built by engineers tired of losing production failures.
We built Relai to solve a specific problem: production AI agent failures that cannot be reproduced once the execution context closes. The agent corrupts an invoice, drops a tool call, returns the wrong result, and the moment the run ends, the failure state is gone. No artifact to replay against. No environment to step back into. Just a log line and a theory.
People who have felt the pain of unverified fixes.
Relai is angel-backed and headquartered in San Francisco.
Laurent co-founded Relai after years building ML pipeline infrastructure and production debugging tooling for distributed systems teams. He has spent most of his career in the gap between where agent failures happen and where engineers actually have tools to investigate them.
Amara designed Relai's replay environment architecture. She comes from a background building distributed testing frameworks and LLM evaluation infrastructure, and brought the insight that agent failures need the same reproducibility treatment as distributed state transitions.
Dev leads SDK and CI integration. His focus is making observability systems approachable: building the capture hooks, the replay runner, and the GitHub Actions integration that lets a developer go from failure bundle to pull request without leaving their existing workflow.
Talk to us about your agent infrastructure.
If you are debugging production AI agents and want to discuss the infrastructure gap, we are interested in hearing what you are running into.