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Azure AI Search

99.9% uptime SLA
Service built on top of Apache Lucene

Data Representation in Search Storage

image

Azure AI Search provides the infrastructure and tools to create search solutions that extract data from various structured, semi-structured, and non-structured documents. image

Features

  • Data from any source: accepts data from any source provided in JSON format, with auto crawling support for selected data sources in Azure.
  • Full text search and analysis: offers full text search capabilities supporting both simple query and full Lucene query syntax.
  • AI powered search: has Azure AI capabilities built in for image and text analysis from raw content.
  • Multi-lingual offers linguistic analysis for 56 languages to intelligently handle phonetic matching or language-specific linguistics. Natural language processors available in Azure AI Search are also used by Bing and Office.
  • Geo-enabled: supports geo-search filtering based on proximity to a physical location.
  • Configurable user experience: has several features to improve the user experience including autocomplete, autosuggest, pagination, and hit highlighting.

Data Ingestion

Original Data Artifacts may come from:

  1. Azure Blob Storage
  2. Azure SQL Database
  3. Azure Cosmos DB.
  4. Regardless of where your data originates, if you can provide it as a JSON document, the search engine can index it. image

Indexers

Most indexers support change detection, which makes data refresh a simpler exercise.

Indexers. Data Enrichment

Indexers also support AI enrichment.
You can attach a skillset that applies a sequence of AI skills to enrich the data, making it more searchable.
Optionally, enriched content can be sent to a knowledge store, which stores output from an AI enrichment pipeline in tables and blobs in Azure Storage for independent analysis or downstream processing.

Built In Skills. Image processing skills: creates text representations of image content, making it searchable

  • Key Phrase Extraction: uses a pre-trained model to detect important phrases based on term placement, linguistic rules, proximity to other terms, and how unusual the term is within the source data.
  • Text Translation Skill: uses a pre-trained model to translate the input text into various languages for normalization or localization use cases.