Multi-Query Retrieval for RAG | Query Rewrites in Azure AI Search

✨ Learn how Multi-Query Retrieval for RAG uses query rewrites and Azure AI Search to improve accuracy and boost retrieval quality.

You know that moment when your RAG system looks perfect in testing… and then... real users show up with vague, messy queries that break everything?

That’s the gap Multi-Query Retrieval for RAG is designed to close. If you’re building RAG systems and want more reliable results in production, this technique is worth exploring.

What you’ll discover: 🔥
📌 A clear walkthrough of the Multi‑Query Retrieval for RAG pattern
📌 A real example using a custom query rewriter (integrated with Microsoft Foundry)
📌 How query rewrites work inside Azure AI Search
📌 Testing different retrieval combinations (BM25/Vector Search/QR/SM)
📌 A practical summary to help you apply it in your own RAG system

👉 Blog post: https://deployedinazure.com/multi-query-retrieval-for-rag/

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0:00 Intro
2:22 Example walkthrough
5:02 Multi-Query Retrieval for RAG foundations
11:18 Custom Query Rewriter (C# + Microsoft Foundry)
28:32 Query Rewrites in Azure AI Search (Basics)
39:37 Query Rewrites in Azure AI Search (C# Example)
44:32 Pros and Cons of Multi-Query retrieval pattern
48:48 Summary
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🌐 Blog: https://deployedinazure.com
💻 GitHub: https://github.com/deployed-in-azure/RAG
🔗 LinkedIn: https://www.linkedin.com/company/deployed-in-azure

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