Turns raw agent traces into labeled evaluation data by classifying each failure against a deterministic rule-based taxonomy, attaching the evidence and sending unclear traces to human review.
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Updated
Jul 18, 2026 - Python
Turns raw agent traces into labeled evaluation data by classifying each failure against a deterministic rule-based taxonomy, attaching the evidence and sending unclear traces to human review.
Automated Quality Evaluation & Failure-Taxonomy Platform for Voice and Chat AI Agents. Hybrid deterministic rules + LLM-as-a-judge, 7-layer root-cause attribution, zero-trust PII masking, and HDBSCAN failure clustering with live interactive dashboard.
105 documented failures from an agent-run research lab, classified by phase, cause, and catching layer. Sealed dataset v1.1 plus the audited taxonomy and submission format.
A structured Chinese failure atlas and casebook for fictional / roleplay dialogue models.
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