RAG Evaluation Checklist
Deploying a RAG system without a structured evaluation framework is one of the most common mistakes we see. This checklist compresses what we've learned from evaluating RAG systems across legal, financial, and healthcare domains into a 12-page structured evaluation framework. Use it before launch to set a quality baseline, and after launch as a monitoring framework.
What's inside
Section 1: Pre-deployment evaluation checklist (35 items across 5 dimensions)
Section 2: The four core metrics - faithfulness, context precision, answer relevance, hallucination rate
Section 3: Test set design - curating evaluation questions that surface domain-specific failure modes
Section 4: Post-deployment monitoring - what to measure weekly in production
Section 5: Regression testing - blocking model or prompt updates that degrade quality
What you'll get
Pre-deployment checklist: 35 items across chunking, embedding, retrieval, generation, and evaluation dimensions
Metric definitions and measurement methodology for all four core RAG metrics
Test set design guide: how to curate domain-specific evaluation questions
Scoring rubric for human evaluators assessing RAG output quality
Production monitoring template: which metrics to track weekly and alert thresholds
Who this is for
Engineers building RAG systems for enterprise knowledge management or support
Technical leads responsible for AI system quality in regulated industries
QA engineers defining acceptance criteria for production RAG deployments
Free to read
RAG Evaluation Checklist
12 pages · No spam
This guide is free to read online - no email required. Or enter your email below for a PDF copy.
