Operations Guide
RAG Retrieval Quality Dashboard Setup for AI Platforms
Retrieval quality is the core lever for RAG production success. This guide structures the monitoring dashboard with quality, latency, and failure tracking.
Implementation Steps
- Configure retrieval quality signals: recall rate, context precision, MRR.
- Track retrieval latency and set alert thresholds for performance degradation.
- Define failure modes: knowledge drift, retrieval attenuation, irrelevant chunks.
- Assign owners for weekly retrieval quality review and corrective actions.
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- Provider and model split recommendations
- Budget guardrail design by traffic stage
- KPI plan for spend, quality, and conversion