Production RAG with Guardrails
Most RAG tutorials stop at "embed documents, search, generate." Production RAG requires query understanding, intelligent retrieval, answer validation, and safety controls.
Basic RAG vs Production RAG​
| Component | Basic RAG | Production RAG |
|---|---|---|
| Query handling | Pass directly to search | Query routing, rewriting, classification |
| Retrieval | Single vector search | Hybrid search (dense + sparse), re-ranking |
| Context | Top-K chunks | Filtered, deduplicated, relevance-scored |
| Generation | Single prompt | Structured prompt with citations |
| Validation | None | Hallucination detection, source verification |
| Safety | None | Bedrock Guardrails, content filtering |
Architecture Components​
- Query router - Classifies intent and routes to appropriate retrieval strategy
- Hybrid search - Combines semantic (dense) and keyword (sparse) search for better recall
- Re-ranker - Scores and reorders retrieved chunks by relevance
- Citation extractor - Maps generated claims back to source documents
- Hallucination detector - Flags statements not grounded in retrieved context
- Bedrock Guardrails - Content filters, denied topics, and PII redaction
What This Course Covers​
| Module | Topic |
|---|---|
| 1 | Query classification and routing |
| 2 | Hybrid search with OpenSearch |
| 3 | Cross-encoder re-ranking |
| 4 | Citation extraction and grounding |
| 5 | Hallucination detection patterns |
| 6 | Bedrock Guardrails configuration |
| 7 | Evaluation framework for RAG quality |
| 8 | Production deployment with monitoring |
Premium
Production RAG with Guardrails
Get the complete 8-module course with hybrid search, re-ranking, hallucination detection, and Bedrock Guardrails integration.