Concept
Search approach that runs keyword (full-text) and vector queries together and merges the results into one ranked list, for example with Reciprocal Rank Fusion (RRF) in Azure AI Search.
| Type | Concept |
|---|---|
| Documentation | learn.microsoft.com/en-us/azure/search/hybrid-search-overview |
2026-07-17 · Video on YouTube
Azure AI Search is Microsoft's intelligent search and information retrieval service for building modern search experiences and AI-powered applications. It combines traditional keyword search with vector search, semantic ranking, and AI enrichment, making it a…
2026-06-07 · Video on YouTube
In this episode, Mirko Peters explores one of the most ambitious experiments in enterprise AI: engineering Microsoft Copilot to analyze and reason across more than 35 million pages of highly complex and interconnected information, inspired by the scale and…
2026-06-08 · Video on YouTube
The explosion of AI-powered applications has created a new challenge: how do you efficiently search through billions of vector embeddings without exploding infrastructure costs? In this episode, we explore the “billion-vector problem” and compare two leading…
2025-11-03 · Video on YouTube
In this episode we walk through what really happens when Azure AI Foundry doesn’t behave the way you expect, especially when the Agent Service or deployments start acting up. Azure AI Foundry is supposed to feel smooth, almost invisible, tying together OpenAI…
2026-06-10 · Video on YouTube
Learn how to build low-cost AI agents in Microsoft Cloud with Azure OpenAI, Copilot Studio, Power Platform, and practical cost controls.
2026-07-16 · Video on YouTube
Vector databases are one of the key technologies powering modern AI applications, yet most people never interact with them directly. Unlike traditional databases that search for exact words or values, vector databases search by meaning, enabling AI to…
2026-07-16 · Video on YouTube
Retrieval-Augmented Generation (RAG) is one of the most important techniques behind modern AI applications, enabling large language models to answer questions using your own business data instead of relying only on their training knowledge. In this episode of…
2026-05-01 · Video on YouTube
This episode explains that vector search on its own is not a complete or reliable strategy for building accurate AI systems like Copilot. While many organizations rely on embeddings and vector databases to retrieve information, this approach often leads to…
Hybrid search combines exact keyword matching for precision with semantic understanding for context. The episode says this gives more reliable, citation-friendly answers than either approach alone. · From the episode: Azure AI Search – Simply Explained
It acts as the retrieval engine behind a RAG app or AI assistant. The episode recommends hybrid search for that role. · From the episode: Azure AI Search – Simply Explained
Hybrid queries combine keyword and vector searches, which the show notes say improves accuracy and reduces hallucinations. · From the episode: RAG on Azure — Simply Explained
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Maintained by Mirko Peters (Microsoft MVP) · Last updated:
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