When should I use hybrid RAG instead of pure vector search?

Almost always. Pure vector search struggles with exact identifiers (order numbers, error codes, product SKUs) and short queries. Hybrid RAG adds keyword matching as a safety net. The only reason to skip it is if your queries are always conceptual and never contain specific identifiers.

Hybrid RAG

Written by Max Zeshut

Founder at Agentmelt

A retrieval strategy that combines keyword-based search (BM25, full-text) with semantic vector search to find the most relevant documents for an AI agent's response. Keyword search catches exact matches (error codes, product names, policy numbers) that semantic search misses, while semantic search handles paraphrased queries and conceptual similarity. Fusing both approaches typically improves retrieval accuracy by 15–30% compared to either alone.

Frequently asked questions

When should I use hybrid RAG instead of pure vector search?: Almost always. Pure vector search struggles with exact identifiers (order numbers, error codes, product SKUs) and short queries. Hybrid RAG adds keyword matching as a safety net. The only reason to skip it is if your queries are always conceptual and never contain specific identifiers.

Related niches

AI Support Agent
AI Legal Agent
AI Coding Agent
AI Data Analyst Agent

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