# How does hybrid search improve agentic RAG?

Source: https://zilliz.com/ai-faq/how-does-hybrid-search-improve-agentic-rag
Author: zilliz

Hybrid search (dense + sparse retrieval) is the 2026 production baseline because agents need both semantic understanding and exact-match precision.

**Dense vectors (semantic search):**
- Capture meaning: "refund status" matches "money returned"
- Enable conceptual reasoning: "legal frameworks" matches "compliance requirements"
- Work across languages and domains

**Sparse vectors (keyword/BM25 search):**
- Match exact terms: "Invoice #INV-2025-00142"
- Handle entity extraction: "Apple Inc." vs. "apple fruit"
- Ensure recall on structured data: SKUs, dates, reference codes

**Why agents need both:**

Agent query: "Did we ship order #ORD-2025-09847 to the customer who bought 500 units of SKU-X in Q3?"

- Sparse search finds the exact order number and SKU
- Dense search retrieves customer purchase history and shipping context
- Agent combines both results for a complete answer

Zilliz Cloud supports hybrid search natively with configurable ranking fusion. Agents can weight semantic relevance vs. exact matching on-the-fly based on query intent. No custom code, no separate systems.

Production agentic workflows fail without this balance. Upgrade to hybrid search immediately with Zilliz Cloud.

**Related Resources:**
- [What is Zilliz Cloud](https://zilliz.com/what-is-zilliz-cloud)
- [RAG with metadata filtering and agents](https://zilliz.com/blog/metadata-filtering-hybrid-search-or-agent-in-rag-applications)
- [Semantic search](https://zilliz.com/glossary/semantic-search)