AI-powered cloud search

Enable AI-powered cloud search to Existing Mobile and Web Apps

AI-powered Cloud Search Service for Mobile and Web App Development
(Implementation Complexity: Easy, 2 days)

Azure Cognitive Search is the only cloud search service with built-in AI capabilities that enrich all types of information to easily identify and explore relevant content at scale. Formerly known as Azure Search, it uses the same integrated Microsoft natural language stack that Bing and Office have used for more than a decade, and AI services across vision, language, and speech. Spend more time innovating and less time maintaining a complex cloud search solution.

  • Cloud search powered with AI capabilities - Auto-complete, geospatial search, filtering, and faceting capabilities for a rich user experience.
  • Start, maintain, and scale with minimal investment - Deploy a fully configured search service with intuitive user experiences such as scoring, faceting, suggestions, synonyms, and geo-search—all while avoiding the operational overhead needed to debug index corruption, monitor service availability, or manually scale during traffic fluctuations.
  • Take advantage of Azure AI speech, vision, and language services to transform raw, unstructured information into searchable content.
  • Support for web, mobile, and enterprise applications.
  • Simple API implementation on every app.
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Cognitive Search using .NET

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Cognitive Search in Java

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Cognitive Search Quickstart in Javascript

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If you don’t have Azure Account:

Meet Azure Cognitive Search – AI-Powered Search for your apps

Azure Cognitive Search (formerly known as "Azure Search") is a cloud search service that gives developers APIs and tools for building a rich search experience over private, heterogeneous content in web, mobile, and enterprise applications.

Azure Cognitive Search is well suited for the following application scenarios:

  • Consolidate heterogeneous content into a private, user-defined search index.
  • Easily implement search-related features: relevance tuning, faceted navigation, filters (including geo-spatial search), synonym mapping, and autocomplete.
  • Transform large undifferentiated text or image files, or application files stored in Azure Blob storage or Cosmos DB, into searchable JSON documents. This is achieved during index through cognitive skills that add external processing.
  • Add linguistic or custom text analysis. If you have non-English content, Azure Cognitive Search supports both Lucene analyzers and Microsoft's natural language processors. You can also configure analyzers to achieve specialized processing of raw content, such as filtering out diacritics, or recognizing and preserving patterns in strings.

For more information about specific functionality, see Features of Azure Cognitive Search

diagram of azure cognitive skills

A search service has the following components:

  • Search engine for full text search
  • Persistent storage of user-owned indexed content
  • APIs for indexing and querying
  • Optional AI-based enrichments, creating searchable content out of images, raw text, application files
  • Optional integration with other Azure services for data, machine learning/AI, and security

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Follow these 4 steps to implement core search capabilities:

  • Step 1: Create a search service at the shared Free tier or a billable tier for dedicated resources used only by your service. All quickstarts and tutorials can be completed on a shared service.
  • Step 2: Create a search index using the portal, REST API, .NET SDK, or another SDK. The index schema defines the structure of searchable content.
  • Step 3: Upload content using the "push" model to push JSON documents from any source, or use the "pull" model (indexers) if your source data is on Azure.
  • Step 4: Query an index using Search explorer in the portal, REST API, .NET SDK, or another SDK.
diagram of azure cognitive search

Additional samples can be downloaded here:

Explore Azure Cognitive Search advanced scenarios: