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Azure AI Search - Enterprise Search Service

Azure AI Search: Fully managed search service with AI enrichment, vector search, and semantic search for enterprise applications.

ai-machine-learning
Pricing Model Per search unit (SU) + storage
Availability All Azure regions
Data Sovereignty EU regions available
Reliability 99.9% SLA

Azure AI Search on Microsoft Azure

What is Azure AI Search?

Azure AI Search (formerly Azure Cognitive Search) is a fully managed search service for integrating search into applications. The service combines classic full-text search with AI enrichment, vector search, and semantic search.

The service indexes data from various sources (Azure Blob Storage, SQL, Cosmos DB) and enables queries via REST API or SDKs. AI Enrichment Pipelines can automatically enrich documents with OCR, entity extraction, translation, and custom skills.

Azure AI Search is particularly relevant for Retrieval-Augmented Generation (RAG) scenarios where LLMs are enriched with enterprise-specific knowledge.

Typical Use Cases

Enterprise search: Employees search documents, wikis, and knowledge bases. AI Enrichment extracts structure from unstructured PDFs and images.

E-commerce: Product search with faceting, filtering, and personalized recommendations. Synonyms, fuzzy search, and autocomplete improve search experience.

Knowledge mining: Automatic analysis of large document collections. OCR for scanned documents, entity extraction for metadata.

RAG for LLMs: Vector search finds relevant document chunks for GPT-4 or other LLMs. Hybrid search combines vector and keyword search for better results.

Frequently Asked Questions about Azure AI Search

What is the difference to Elasticsearch?

Azure AI Search is fully managed (no cluster management), has integrated AI Enrichment pipelines, and native Azure integration. Elasticsearch offers more low-level control and is open source. For Azure-native applications, Azure AI Search is often simpler.

What is vector search?

Vector search finds semantically similar documents based on embeddings rather than keywords. Documents are stored as high-dimensional vectors. Azure AI Search supports vector search with HNSW algorithm and Azure OpenAI embeddings.

How does AI Enrichment work?

Skillsets define enrichment pipelines: OCR extracts text from images, Entity Recognition finds people/places, Key Phrase Extraction identifies important terms. Custom Skills can call Azure Functions.

What does Azure AI Search cost?

Prices are based on service tier (Basic, Standard, Storage Optimized) and number of search units. Basic starts at approximately 65 EUR/month. Standard S1 with 25 GB index approximately 230 EUR/month. Semantic search and vector search require higher tiers.

Can I combine Azure AI Search with Azure OpenAI?

Yes, Azure AI Search is the recommended solution for RAG with Azure OpenAI. Documents are indexed, vector search finds relevant chunks, which are passed as context to GPT-4.

Integration with innFactory

As a Microsoft Solutions Partner, innFactory supports you in implementing Azure AI Search. We help with index design, AI enrichment pipelines, and RAG architectures.

Contact us for a non-binding consultation on Azure AI Search.

Typical Use Cases

Enterprise search across documents
E-commerce product search
Knowledge mining
RAG for generative AI

Microsoft Solutions Partner

innFactory is a Microsoft Solutions Partner. We provide expert consulting, implementation, and managed services for Azure.

Microsoft Solutions Partner Microsoft Data & AI

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