The original title is: "Optimizing RAG at Scale: Chunking Strategies, Hybrid Retrieval, and Reranking for 95% Recall"

Short summary

A production-focused RAG optimization guide covering chunking strategies (fixed, recursive, semantic, agentic) tuned per document type, hybrid retrieval combining vector search and BM25 with reciprocal rank fusion, and cross-encoder reranking that improves recall by 15% at 50ms cost. Includes concrete recall@10 benchmarks by document type and query transformation patterns to handle poorly-formed user queries. Claims 40% latency reduction and 95% recall@10 in production.

• •Four chunking strategies mapped to document types with measured recall@10 benchmarks
• •Hybrid retrieval via BM25 + vector search + reciprocal rank fusion + cross-encoder rerank funnel
• •Query transformation layer handles bad user queries before retrieval; 40% latency reduction claimed

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