Tracely
Production failures become regression tests for AI agents
What it does
Tracely grades every agent trace as it lands, clusters failures into issues, freezes bad runs into hermetic replayable test cases — and blocks the PR that would ship them again. The trace is the test: no hand-authored datasets. Open source, MIT.
Trace your AI agents, grade every run, and turn production failures into regression tests that block the pull request which would ship them again.
LLM observability that closes the loop: every agent trace graded as it lands, failures clustered into issues, bad runs frozen into tests that block the PR. Four moves, no hand-authored datasets. Each one is derived from the last, and the trace starts it all. Every production run streams in over OTLP — durable blob first, one indexed row per span. Agent, conversation and tool semantics are first-class columns, not strings. Online evaluators grade each trace as it lands — LLM-as-judge at conversation, run or span level. One FAIL on a blocking evaluator flips the verdict. One click promotes a failing trace into a hermetic case: recorded input, tool and LLM fixtures bundled, a fail-to-pass…from tracely-ai.com
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Progress AI Observability30d ago · telerik.com · ▲168Trace, evaluate, and improve AI agents in production
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