Tracely

Tracely redefines quality assurance for complex agent systems by using production traces as the foundation for regression testing. Key capabilities include: • Grades every agent trace upon arrival • Clusters trace failures into distinct issues • Freezes problematic runs into replayable test cases • Blocks pull requests that reintroduce past failures Tracely's approach eliminates the need for hand-authored datasets. By capturing and analyzing production traces, it automatically identifies and formalizes failing scenarios. This ensures that every detected issue is directly tied to real-world performance, creating highly relevant and robust regression tests. The platform instruments a wide range of agent stacks, from OpenAI and Anthropic to LangChain and LiteLLM, processing all inputs over OTLP. It uses sophisticated evaluators, often large language models acting as judges, to grade traces and pinpoint specific failures at conversation, run, or span levels. A single critical failure can automatically mark a trace as problematic, which can then be promoted to a hermetic test case with one click, complete with recorded inputs, tool, and language model fixtures. Built for engineering teams managing complex agent systems, Tracely integrates directly into CI/CD pipelines. It reruns test suites on every pull request using offline, deterministic replay, ensuring that no regression ships to production. This provides continuous quality enforcement and stability, making it an indispensable tool for maintaining the reliability of sophisticated agent deployments.