What is Azure AI Search?
Azure AI Search is a fully managed search service that combines full-text search with semantic ranking, vector search, and AI enrichment. The service forms the foundation for intelligent search applications and is the recommended retrieval component for RAG architectures. Alongside the established Dedicated pricing model with fixed allocated capacity, Azure AI Search now also offers a consumption-based Serverless pricing model currently in preview.
Core Features
- Semantic Search: Understands query meaning and ranks results by relevance
- Vector Search: Similarity search based on embeddings for conceptual search
- Hybrid Search: Combines keyword search and vector search for best results
- AI Enrichment: Automatically extracts text from images, recognizes entities, and translates content
- Facets and Filters: Structured navigation and filtering across large datasets
- Geo Search: Location-based search with distance calculation
Typical Use Cases
RAG for LLM Applications: Azure AI Search delivers relevant documents as context for Azure OpenAI. The combination of semantic search and LLM enables precise answers to natural language questions.
Enterprise Search: Employees search SharePoint, Confluence, and file shares through a unified search interface. AI Enrichment automatically extracts text from PDFs and images.
E-Commerce Product Search: Customers find products even with imprecise search queries. Semantic ranking understands synonyms and product descriptions for relevant matches.
Benefits
- Combines the best of classic search and AI
- Scales to billions of documents
- Native integration with Azure OpenAI for RAG
- Managed service without infrastructure overhead
Integration with innFactory
As a Microsoft Solutions Partner, innFactory supports you with Azure AI Search: We implement RAG architectures for your knowledge base, build intelligent product searches for e-commerce, and integrate enterprise search into existing portals.
Typical Use Cases
Frequently Asked Questions
What is the difference between Azure AI Search and classic full-text search?
Azure AI Search combines classic full-text search with semantic ranking and vector search. Semantic ranking understands query meaning and delivers more relevant results.
How does vector search work in Azure AI Search?
Texts are converted to vectors (embeddings) and searched by similarity. This enables search by meaning rather than just keywords.
Can Azure AI Search be used for RAG?
Yes, Azure AI Search is the recommended retrieval component for RAG architectures with Azure OpenAI. The service provides relevant documents as context for LLM responses.
Which data sources are supported?
Indexers connect to Azure Blob Storage, SQL Database, Cosmos DB, SharePoint, and more. Data can also be indexed via REST API.
How is Azure AI Search billed?
In the Dedicated model, billing is based on service tier (Basic, Standard, Storage Optimized) through search units made up of replicas and partitions. Alternatively, a consumption-based Serverless pricing model (preview) is available without fixed capacity planning.
Note: All product information on this page has been compiled with care, but is provided without guarantee and may be outdated or incomplete. Cloud services evolve rapidly — features, pricing, SLAs, and availability change frequently. Authoritative and up-to-date information can only be found on the official product page of Azure (official documentation). This page does not represent an offer by Azure.
