This article was originally published on AI Study Room . For the full version with working code examples and related articles, visit the original post. RAG Retrieval Optimization: Hybrid Search, Re-Ranking, Query Transformation Introduction Retrieval quality is the single biggest factor in RAG system performance. Even the best LLM cannot produce accurate answers from irrelevant context. This article covers three optimization layers: hybrid search that combines embedding similarity with keyword matching, re-ranking that refines initial results, and query transformation that bridges the gap between user questions and searchable terms. Hybrid Search Pure vector search excels at semantic similarity but misses exact keyword matches. Pure keyword search finds exact terms but misses conceptually related content.…