AI9 min read
Production RAG Architecture: Hybrid Search, Re-ranking, and Chunking Strategies
By Sayyed Abrar Akhtar • Published 2025-02-25
Build enterprise Retrieval-Augmented Generation systems with high precision vector search and BM25 hybrid ranking.
Naive RAG setups fail on subtle domain questions. Enterprise RAG systems rely on **Hybrid Search** (combining sparse BM25 keyword matching with dense vector embeddings) followed by cross-encoder re-ranking.
Advanced Chunking Methods
- **Semantic Chunking**: Split text based on embedding similarity drops rather than fixed character lengths.
- **Hierarchical Parent-Child Indexing**: Search fine-grained small chunks but feed full parent context to the LLM.
Tags:#RAG#Vector DB#AI Architecture