Welcome back to TechTalks with Manoj — the show where we unpack the tech that’s actually shaping modern systems — not just trending on social feeds.

In today’s episode, we’re diving deep into a service that doesn’t get nearly enough credit: Azure AI Search.

You’ve probably heard of vector search. Maybe semantic search. But Azure AI Search? It’s doing all of that — and then some — powering everything from hybrid retrieval to LLM grounding, and transforming how enterprises mine value from unstructured data.

This isn’t “just” search. It’s an intelligent retrieval engine — stacked with full-text, vector, semantic, and hybrid capabilities — plus a built-in AI enrichment pipeline that turns PDFs, blobs, and images into knowledge-ready chunks.

Here’s what we’re covering:

* The full retrieval stack — from Lucene to vectors to semantic reranking

* How hybrid search + semantic captions give LLMs real-world grounding

* When to use built-in vs custom enrichment, and how to host your own skills

* Why Reciprocal Rank Fusion (RRF) changes the game for RAG precision

* Practical tips for scaling, caching, and index tuning in production

* Security, compliance, and when not to use Customer Managed Keys

* And how to build an enterprise-grade, RAG-ready architecture using Azure AI Search, OpenAI, and your own data lake

If you're building copilots, internal bots, or search experiences that actually work — Azure AI Search is your silent MVP.

Let’s get into it.

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