Azure Cognitive Search concepts

Azure · Oct 9, 2023 · 1b6e50d · 1b6e50d
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diff --git a/docs/content/en/docs/Concepts/azure-cognitive-search.md b/docs/content/en/docs/Concepts/azure-cognitive-search.md
@@ -7,4 +7,17 @@ categories: [Azure]
 tags: [docs, cognitive-search]
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-TODO
+Azure Cognitive Search (formerly known as "Azure Search") is a cloud search service that gives developers infrastructure, APIs, and tools for building a rich search experience over private, heterogeneous content in web, mobile, and enterprise applications.
+
+Search is foundational to any app that surfaces text to users, where common scenarios include catalog or document search, online retail apps, or data exploration over proprietary content. When you create a search service, you'll work with the following capabilities:
+
+* A search engine for full text and vector search over a search index containing user-owned content
+* Rich indexing, with lexical analysis and optional AI enrichment for content extraction and transformation
+* Rich query syntax for vector queries, text search, fuzzy search, autocomplete, geo-search and more
+* Programmability through REST APIs and client libraries in Azure SDKs
+* Azure integration at the data layer, machine learning layer, and AI (Azure AI services)
+
+In our solution we will use Azure Cognitive Search to serve an index of vectorized content, that will be used by our LLM (ChatGPT) to respond to user's query.
+
+Learn more at the official documentation: [What is Azure Cognitive Search?](https://learn.microsoft.com/en-us/azure/search/search-what-is-azure-search).
+Learning Path:[Implement knowledge mining with Azure Cognitive Search - Learning Path](https://learn.microsoft.com/en-us/training/paths/implement-knowledge-mining-azure-cognitive-search/)
diff --git a/docs/content/en/docs/Overview/_index.md b/docs/content/en/docs/Overview/_index.md
@@ -39,12 +39,12 @@ This delivery consists of the following steps:
 1. Upload custom data files and perform vector search.
 
 ### Day 3:
-1. Customize the solutions look and feel.
+1. Customize the solution's look and feel.
 1. Extend the solution with prompt engineering and plugins.
 1. Show how the solution scales and integrates with other services.
 1. Show how the security and monitoring works.
 1. Plan the next steps.
 
 ## Closing
-By the end of  the **Activate GenAI with Azure** delivery, stakeholders will have a   powerful and innovative solution that can help them improve their document retrieval efficiency, enhance their user experience, increase their productivity, share their knowledge, gain data insights and analytics, and comply with security standards.ss
+By the end of  the **Activate GenAI with Azure** delivery, stakeholders will have a  powerful and innovative solution that can help them improve their document retrieval efficiency, enhance their user experience, increase their productivity, share their knowledge, gain data insights and analytics, and comply with security standards.ss