AI & ML

Architecting Hybrid Vector Search & RAG in Production

Priya Sundaram

·September 28, 2026·8 min read

Architecting Hybrid Vector Search & RAG in Production

A deep dive into combining keyword BM25 retrieval with dense vector embeddings for low-latency AI assistants.

Retrieval-Augmented Generation (RAG) is now the standard architecture for domain-adapted LLMs. However, pure dense vector search often struggles with precise SKU numbers, product codes, or niche jargon. ### The Power of Reciprocal Rank Fusion By synthesizing results from BM25 sparse keyword indices with modern multilingual embedding spaces, hybrid search dramatically reduces hallucinations and delivers precise answers.