AI Observability & Drift Detection
AI observability and drift detection platforms monitor model behavior, output quality, cost, and latency over time — detecting when model performance degrades, outputs drift from expected patterns, or costs spike unexpectedly. This is distinct from server monitoring (Topic 10) which watches infrastructure; this watches the intelligence itself. Key capabilities include trace visualization, cost attribution, quality score tracking, and automated alerting on behavioral changes.
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