Debug AI agents by replaying and forking runs
Record, replay, fork & share AI agent executions. See every LLM call, tool invocation, and error your agent makes, then debug and iterate in seconds. Free for 1,000 traces/mo.
Retrace records every LLM call, tool call, and error in a run as a span inside a trace. You can replay a past run step by step, like scrubbing through a video. When you find the step that broke, you fork it, change the input or model at that point and the agent re-executes from there, so you can compare the original and the new path side by side. The part I care most about is the forking: it's closer to git branching than to re-running a prompt. Pre-fork steps replay from the recording; everything downstream runs live. It's early, and I'd really like your feedback — especially on the replay and fork flow, and what would make it fit your stack. Which frameworks or providers are you using? Happy to answer anything here.