Search Azure terms

AI and Machine Learning premium Semantic ranker Semantic ranker is an Azure AI Search capability that applies language understanding to an initial result set and reranks the most relevant matches. It can improve keyword, vector, or hybrid search results and supports semantic captions, answers, and reranker scores when the index and query are configured correctly. Azure AI Search semantic ranking fundamentals 5 commands Aliases: semantic reranker, Azure AI Search semantic ranker, semantic ranking, semantic search ranking Quick peek Open full term page

AI and Machine Learning expanded Semantic captions Semantic captions are optional per-result snippets returned by Azure AI Search semantic ranking for matching documents. They extract relevant passages, can include highlights, and help users scan why each result is relevant before opening the underlying source in a search experience. Azure AI Search intermediate 3 commands Aliases: semantic result captions, @search.captions, extractive captions, semantic snippets Quick peek Open full term page

AI and Machine Learning premium Azure AI Search index An Azure AI Search index is the place where your application searches. It is not just a pointer to a database or blob container. It is a separate searchable structure with documents, fields, and rules for how text, filters, facets, semantic ranking, and vectors behave. If the index schema is wrong, the search experience feels wrong even when the source data is good. Developers and operators use indexes to make. AI platform and search intermediate 5 commands Aliases: Azure AI Search index, search index, AI Search index, azure-ai-search-index Quick peek Open full term page

AI and Machine Learning premium Azure AI Search Azure AI Search is a managed retrieval service for full-text, vector, hybrid, and semantic search across application and enterprise content. It provides search services, indexes, indexers, skillsets, ranking features, security controls, and APIs used by apps, copilots, and knowledge portals. Search fundamentals 4 commands Aliases: Azure AI Search, AI Search, Azure Cognitive Search, enterprise search, vector search, hybrid search, semantic search, Search service Quick peek Open full term page

AI and Machine Learning premium Azure AI Search service Azure AI Search service is the Azure resource that hosts Azure AI Search indexes, indexers, skillsets, keys, capacity, networking, and query endpoints. AI platform and search intermediate 4 commands Aliases: AI Search resource, AI Search service, Azure Search service, Search service, search service Quick peek Open full term page

AI and Machine Learning premium Azure AI Search skillset Azure AI Search skillset is a reusable Azure AI Search enrichment object that applies built-in or custom processing during indexer execution. AI platform and search intermediate 4 commands Aliases: AI enrichment skillset, Search skillset, cognitive skillset, skillset Quick peek Open full term page

AI and Machine Learning premium Azure AI Search indexer An Azure AI Search indexer is the automated worker that fills a search index from another data source. Instead of your application pushing every document into Azure AI Search, the indexer pulls from places such as Blob Storage, Azure SQL, Cosmos DB, or Data Lake Storage. It can map fields, detect changes, crack documents, and run enrichment skills before writing searchable documents. It is useful when source data changes regularly. AI platform and search intermediate 5 commands Aliases: Azure AI Search indexer, search indexer, indexer, azure-ai-search-indexer Quick peek Open full term page

AI and Machine Learning premium Azure AI Search data source Azure AI Search data source is the connection definition an Azure AI Search indexer uses to read content from a supported external data store. AI platform and search intermediate 4 commands Aliases: Search data source, SearchIndexerDataSourceConnection, data source connection, indexer data source, search data source connection Quick peek Open full term page

AI and Machine Learning premium Search semantic configuration A search semantic configuration is an Azure AI Search index setting that names the fields used by semantic ranker. It prioritizes title, content, and keyword fields so semantic ranking, captions, and answers can evaluate the most meaningful document text during semantic queries. Search advanced 5 commands Aliases: Azure AI Search semantic configuration, semantic search configuration, semantic ranker configuration, prioritized fields, semantic config Quick peek Open full term page

AI and Machine Learning command-rich Data source in AI Search Data source in AI Search is documented by Microsoft as part of the Azure AI Search area in Azure. Azure AI Search intermediate 6 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium Azure AI Language Azure AI Language is the Azure natural-language processing service for analyzing and understanding text with prebuilt and customizable language capabilities. AI services intermediate 4 commands Aliases: Azure Language, Azure Language in Foundry Tools, Azure Language service, Language in Foundry Tools, Language service Quick peek Open full term page

AI and Machine Learning premium Azure AI services Azure AI services is the family of Azure cloud AI APIs and resources, surfaced through Foundry Tools, for vision, speech, language, translation, content, and generative scenarios. AI services fundamentals 4 commands Aliases: AI services, Azure AI services account, Cognitive Services, Foundry Tools Quick peek Open full term page

AI and Machine Learning premium Azure AI Vision The Azure vision service that analyzes images and visual content for tasks such as OCR, object information, captions, tags, and image understanding. AI services intermediate 4 commands Aliases: Azure Vision, Computer Vision, Image Analysis, Vision in Foundry Tools Quick peek Open full term page

AI and Machine Learning premium Azure AI Foundry Create a governed project boundary where AI teams can build agents, evaluations, files, and model deployments without unmanaged sprawl.; Compare, evaluate, and approve model deployments before a generative AI feature is AI platform fundamentals 5 commands Aliases: AI Foundry, Microsoft Foundry, Foundry resource, Foundry project, Azure AI Foundry, azure ai foundry Quick peek Open full term page

AI and Machine Learning premium Azure AI Content Safety Azure AI Content Safety is the Azure AI service used to detect harmful text and image content before it reaches users, moderators, or automated workflows. In Azure, teams encounter it when applications accept user posts, comments, uploads, prompts, or model outputs that need moderation and policy review. The useful question is what behavior it proves, Responsible AI advanced 4 commands Aliases: Content Safety, Azure Content Safety, harm detection, content moderation API Quick peek Open full term page

AI and Machine Learning premium Azure AI Foundry hub Azure AI Foundry hub is the classic Foundry hub resource used to group AI projects that share common security, data access, connections, and platform settings. In Azure, teams encounter it when teams need hub-based projects for selected Foundry and Azure Machine Learning scenarios such as fine-tuning, shared connections, and custom ML work. The useful question AI platform advanced 4 commands Aliases: AI Hub, Foundry AI Hub, hub-based project, Azure AI hub Quick peek Open full term page

AI and Machine Learning premium Azure AI Foundry project An Azure AI Foundry project is the working area where a team builds and organizes an AI application inside Microsoft Foundry. It keeps related agents, evaluations, files, indexes, tools, connections, and model usage together instead of scattering them across a shared portal. Think of it as the project boundary for one AI product, prototype, or team. It is useful because AI work quickly becomes messy: prompts, test data, model deployments, safety checks, and access decisions all need a home with ownership and repeatable operations. AI platform advanced 4 commands Aliases: AI Foundry project, AI project, Foundry project, Microsoft Foundry project Quick peek Open full term page

AI and Machine Learning premium Azure AI metrics Azure AI metrics is the measurable signals used to observe Azure AI applications, model endpoints, agents, evaluations, safety checks, and business outcomes. Azure AI services intermediate 4 commands Aliases: AI metrics, AI service metrics, Azure AI Metrics Advisor, Azure Monitor metrics for AI, Metrics Advisor, time series anomaly detection Quick peek Open full term page

AI and Machine Learning premium Azure AI services account An Azure resource that provides endpoints, keys, identity, networking, billing, and monitoring for one or more Azure AI service capabilities. Azure AI services fundamentals 4 commands Aliases: AI services account, Azure AI multi-service resource, Foundry resource, Microsoft.CognitiveServices account Quick peek Open full term page

AI and Machine Learning premium Azure AI Speech The Azure speech service for converting speech to text, text to speech, speech translation, pronunciation assessment, and related speech-enabled capabilities. AI services intermediate 4 commands Aliases: Azure Speech, Speech in Foundry Tools, Speech service, Speech-to-text Quick peek Open full term page

AI and Machine Learning premium Azure AI Translator A cloud-based machine translation service for translating text and documents across supported languages through REST APIs and client libraries. AI services intermediate 4 commands Aliases: Azure Translator, Document Translation, Text Translation, Translator Quick peek Open full term page

AI and Machine Learning premium Search relevance Search relevance in Azure AI Search is the process of ranking matching documents so the most useful results appear first. Relevance can depend on BM25 keyword scoring, analyzers, filters, scoring profiles, vector retrieval, semantic ranking, application query design, and production feedback. Search intermediate 5 commands Aliases: Azure AI Search relevance, search ranking, result relevance, BM25 relevance, semantic relevance, ranking quality Quick peek Open full term page

AI and Machine Learning field-manual-complete Vector search Vector search retrieves content by comparing embedding vectors, helping Azure applications find semantically similar documents, images, products, or passages. Search fundamentals 4 commands Aliases: semantic vector search, similarity search, nearest-neighbor search, AI Search vector search Quick peek Open full term page

AI and Machine Learning expanded Semantic configuration A semantic configuration is part of an Azure AI Search index that identifies title, content, and keyword fields for semantic ranking. It guides reranking, captions, and answers, can be added to existing indexes, and lets applications reference a named relevance setup in query requests. Azure AI Search advanced 4 commands Aliases: semantic config, semantic ranking configuration, Azure AI Search semantic configuration, semantic field configuration Quick peek Open full term page

AI and Machine Learning expanded Semantic caption A semantic caption is an extractive snippet returned by Azure AI Search for one result after semantic ranking. It summarizes the part of a document that appears most relevant to the query and can include highlighted phrases so users understand why the result matched. Azure AI Search advanced 3 commands Aliases: semantic result caption, @search.captions, extractive caption, semantic snippet Quick peek Open full term page

AI and Machine Learning premium Azure OpenAI Azure OpenAI provides OpenAI model capabilities through Azure resources, deployments, identity, networking, quota, and monitoring controls. Azure OpenAI intermediate 8 commands Aliases: Azure OpenAI Service Quick peek Open full term page

AI and Machine Learning premium Search analyzer A search analyzer is the Azure AI Search text-processing component that breaks strings into searchable tokens during indexing and query execution. Built-in, language, or custom analyzers control tokenization, normalization, stemming, stop words, and other lexical behavior for searchable string fields. Azure AI Search fundamentals 8 commands Aliases: Azure AI Search analyzer, text analyzer, search text analyzer, custom analyzer, language analyzer Quick peek Open full term page

AI and Machine Learning premium Hybrid search Hybrid search in Azure AI Search combines vector search and keyword or full-text search in a single request and merges the results. Azure AI Search advanced 5 commands Aliases: Hybrid search, hybrid search Quick peek Open full term page

AI and Machine Learning premium Search filter A search filter is an OData expression in Azure AI Search that narrows query results before or during retrieval. Filters compare fields, ranges, collections, geography, or security values so the service returns only documents that satisfy those conditions. It depends on filterable fields and trusted query construction. Azure AI Search fundamentals 5 commands Aliases: Azure AI Search filter, OData filter, search query filter, filter expression, Azure Search filter, document filter Quick peek Open full term page

AI and Machine Learning premium Search index A search index is the searchable data structure in Azure AI Search. It defines fields, attributes, analyzers, vector settings, scoring options, and stored documents so applications can run queries, filters, facets, and retrieval workflows. It is the contract that applications query at runtime. Search fundamentals 5 commands Aliases: Azure AI Search index, Azure Search index, search schema, index schema, searchable index, retrieval index Quick peek Open full term page

AI and Machine Learning premium Search scoring profile A search scoring profile is an Azure AI Search index configuration that boosts or suppresses ranking for matching documents. It can use weighted text fields and scoring functions such as freshness, magnitude, distance, or tags to shape relevance during query execution. Search intermediate 5 commands Aliases: Azure AI Search scoring profile, search ranking profile, scoring profile, relevance boost profile, search boost profile Quick peek Open full term page

Databases premium Hybrid search in Cosmos DB Hybrid search in Cosmos DB is a Cosmos DB for NoSQL capability that combines vector search with full-text search scoring, then merges results with Reciprocal Rank Fusion. Azure Cosmos DB advanced 4 commands Aliases: Cosmos DB hybrid search, Cosmos DB RRF search, Hybrid search in Azure Cosmos DB, hybrid search in cosmos db, Hybrid search in Cosmos DB Quick peek Open full term page

AI and Machine Learning premium BM25 ranking BM25 ranking is the ordering of Azure AI Search full-text results by BM25 relevance scores for searchable text fields and query terms. Azure AI Search fundamentals 3 commands Aliases: No aliases yet Quick peek Open full term page

Databases premium Cosmos DB vector search Cosmos DB vector search is an Azure glossary term for the Azure Cosmos DB capability for storing vector embeddings with operational data and querying for similar items instead of only exact field matches. In practice, it helps teams reason about semantic retrieval, recommendation, retrieval augmented generation, and similarity search inside a Cosmos DB workload using live Azure evidence, documented ownership, and Microsoft Learn guidance. It should be reviewed through security, reliability, operations, cost, and performance lenses before production changes. Azure Cosmos DB advanced 3 commands Aliases: Azure Cosmos DB vector search Quick peek Open full term page

AI and Machine Learning command-rich Search admin key A search admin key is one of the generated API keys for an Azure AI Search service that allows full read-write data-plane access. It can create, update, or delete indexes, indexers, data sources, and documents, so it must be protected, rotated, and replaced with role-based access when possible. Azure AI Search fundamentals 5 commands Aliases: Azure AI Search admin key, search service admin key, Azure Search API admin key, primary admin key, secondary admin key Quick peek Open full term page

Databases field-manual-complete Redis vector similarity search Redis vector similarity search lets Redis answer questions like “which stored items are most similar to this embedding?” Instead of matching only exact words, applications store vectors that represent meaning, images, products, documents, or events. Redis indexes those vectors and returns nearby results quickly. In Azure, this is useful when a team wants low-latency AI retrieval or recommendations close to the application cache. It is not a magic model; the quality still depends on embeddings, index design, metadata filters, and refresh discipline. Azure Managed Redis advanced 5 commands Aliases: Redis vector search, Redis VSS, RediSearch vector search, Redis KNN search Quick peek Open full term page

AI and Machine Learning field-manual-complete Semantic answer A semantic answer is a short answer that Azure AI Search extracts from indexed documents when a user asks a question. Azure AI Search advanced 4 commands Aliases: semantic answers, extractive answer, @search.answers Quick peek Open full term page

AI and Machine Learning expanded Semantic answers Semantic answers are extractive answer passages that Azure AI Search can return from the highest-ranked documents in a semantic query. They appear in @search.answers when the query resembles a question and indexed text contains content that directly answers it. Azure AI Search intermediate 4 commands Aliases: extractive semantic answers, @search.answers, semantic answer array, semantic answer results Quick peek Open full term page

AI and Machine Learning expanded Semantic cache A semantic cache stores previous prompts and responses with vector representations so later requests with similar meaning can reuse a cached response. In Azure, this pattern is used with services such as API Management and Azure Managed Redis to reduce latency, backend load, and LLM calls. Azure Managed Redis and API Management advanced 4 commands Aliases: semantic caching, LLM semantic cache, AI gateway semantic cache, vector response cache Quick peek Open full term page

Databases premium Azure Managed Redis Azure Managed Redis is a Microsoft-managed in-memory data store based on Redis Enterprise, used for low-latency caching, session storage, messaging, and semantic cache scenarios. Managed cache intermediate 6 commands Aliases: Managed Redis, Redis Enterprise on Azure, Azure Redis Enterprise Quick peek Open full term page

AI and Machine Learning premium Search data source A search data source is an Azure AI Search indexer object that describes where external content comes from. It specifies the supported source type, connection information, credentials or identity, container or query, and sometimes change or deletion detection used by indexers. Azure AI Search fundamentals 5 commands Aliases: Azure AI Search data source, indexer data source, SearchIndexerDataSourceConnection, data source connection, Azure Search data source object Quick peek Open full term page

AI and Machine Learning premium Search document A search document is a single searchable JSON record stored in an Azure AI Search index. It contains field values defined by the index schema, including a unique key, retrievable content, filters, facets, sortable values, and sometimes vector fields. Azure AI Search fundamentals 5 commands Aliases: Azure AI Search document, search index document, indexed document, searchable document, document in search index Quick peek Open full term page

AI and Machine Learning premium Search index projection A search index projection defines how enriched content from an Azure AI Search skillset is projected into one or more indexes. It is commonly used to create chunked child documents with parent metadata for retrieval-augmented generation. It is configured as part of the enrichment pipeline. Azure AI Search fundamentals 5 commands Aliases: Azure AI Search index projection, indexer projection, projected search index, RAG chunk projection, skillset index projection, index projections, projection selector, projected index, chunk projection Quick peek Open full term page

AI and Machine Learning premium Search indexer A search indexer is an Azure AI Search component that crawls a supported data source, extracts or enriches content, and loads documents into a search index. It can run on demand or on a schedule. It connects source freshness to searchable content. Azure AI Search fundamentals 5 commands Aliases: Azure AI Search indexer, Azure Search indexer, search crawler, pull indexing pipeline, managed search ingestion, indexer run, indexer schedule, search ingestion job Quick peek Open full term page

AI and Machine Learning premium Search partition A search partition is a capacity unit in Azure AI Search that provides storage and indexing resources for indexes. Increasing partitions expands index storage and can improve throughput for data ingestion and some query workloads. It is configured on the search service capacity model. Azure AI Search intermediate 5 commands Aliases: Azure AI Search partition, Azure Search partition, search service partition, search capacity partition, partition count, search unit partition Quick peek Open full term page

AI and Machine Learning premium Search query key A search query key is an Azure AI Search API key that permits read-only document queries against indexes. It is intended for client applications that need search results but should not manage indexes, data sources, indexers, skillsets, or service configuration. Search fundamentals 5 commands Aliases: Azure AI Search query key, search API query key, read-only search key, query API key, Azure Search query key Quick peek Open full term page

AI and Machine Learning premium Search replica A search replica is a copy of the Azure AI Search engine used to serve query and indexing workloads. Adding replicas increases query concurrency and availability, while partitions provide storage capacity; together they determine search units, cost, and production capacity-planning decisions. Search fundamentals 5 commands Aliases: Azure AI Search replica, search service replica, replica count, query replica, search capacity replica Quick peek Open full term page

AI and Machine Learning premium Search service An Azure AI Search service is the provisioned Azure resource that hosts indexes, indexers, skillsets, query APIs, keys, networking, replicas, partitions, and monitoring settings. It is the management and data-plane boundary for building searchable content and retrieval experiences. and governance reviews. Azure AI Search fundamentals 5 commands Aliases: Azure AI Search service, search resource, search endpoint, Microsoft.Search search service, managed search service Quick peek Open full term page

Monitoring and Observability premium Search service diagnostic logs Search service diagnostic logs are Azure Monitor resource logs from Azure AI Search that record query, suggest, autocomplete, lookup, indexing, service statistics, and operational events. They are collected in Log Analytics or storage when diagnostic settings are enabled on the search service. Data operations intermediate 5 commands Aliases: Azure AI Search logs, search resource logs, Microsoft.Search diagnostics, search operation logs, Search diagnostic settings Quick peek Open full term page

AI and Machine Learning premium Search skill A search skill is one processing step inside an Azure AI Search skillset. It transforms extracted source content during indexing, such as OCR, entity recognition, translation, text splitting, embedding generation, or custom enrichment, and writes output into the enriched document tree. Search intermediate 5 commands Aliases: Azure AI Search skill, enrichment skill, cognitive skill, custom skill, indexing skill Quick peek Open full term page