Tired of Reviewing Traces? Meet Automatic Issue Detection for Your Agent
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MLflow 3.11.1 introduces Automatic Issue Detection, an AI-driven feature that analyzes production traces from LLM applications to surface quality problems without manual review. It uses the CLEARS framework (Correctness, Latency, Execution, Adherence, Relevance, Safety) to categorize issues, clusters related failures into patterns, annotates source traces with findings, and provides a structured triage lifecycle (Pending, Resolved, Rejected). The detection pipeline runs asynchronously using an LLM of your choice via MLflow AI Gateway or direct API, replacing hours of manual trace inspection with a 3-click workflow.
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Why Do You Need Automatic Issue Detection? Getting Started How It Works Summary Sort: