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Implementing an intelligent search solution with Azure AI Search (formerly Azure Cognitive Search).
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This module dives into creating an end-to-end intelligent search pipeline using Azure AI Search. You will learn how to provision and configure search services, enrich content with custom skills, and persist enriched results in a knowledge store for advanced querying and analytics.
Before you begin, ensure you have an Azure subscription and sufficient permissions to create resource groups, Search services, and storage resources. For development scenarios, consider using a separate resource group to manage costs.
What we’ll cover
  • Provisioning and configuring an Azure AI Search service
  • Defining indexes and connecting data sources for ingestion
  • Implementing and integrating custom skills (Azure Functions or web APIs) into enrichment pipelines
  • Building a knowledge store to retain and query enriched data
Goals at a glance
GoalOutcomeKey steps / examples
Set up Azure AI SearchA running Search service with an index ready to ingest dataProvision Search in Azure portal or via CLI; create an index and map fields; connect blob, Cosmos DB, or SQL data sources
Build & integrate custom skillsEnrich content during indexing (e.g., OCR, entity recognition, translation)Implement Azure Functions or custom web APIs; register skills in a skillset; add to indexer pipeline
Create a knowledge storeStructured repository of enriched content for analytics and queryingConfigure a knowledge store (Azure Storage or Cosmos DB); route enriched documents to the store
Recommended reading and references This module prepares you to design, implement, and operate an intelligent search solution that supports advanced content enrichment and delivers rich query experiences for applications.

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