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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 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 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 AI evaluation AI evaluation is the Microsoft Foundry process of testing a generative AI model, agent, or application against a dataset and measuring its quality, safety, and task performance with built-in or custom evaluators. Microsoft Foundry intermediate 3 commands Aliases: Azure AI evaluation, Foundry evaluation, generative AI evaluation, model evaluation Quick peek Open full term page

AI and Machine Learning premium AI red teaming AI red teaming is the practice of probing a generative AI system with adversarial prompts, attack strategies, and risk categories to discover unsafe behavior, jailbreak weaknesses, and harmful-output paths before or after deployment. Responsible AI advanced 3 commands Aliases: AI Red Teaming Agent, red team scan, adversarial AI testing, LLM red teaming Quick peek Open full term page

AI and Machine Learning premium AI tracing AI tracing captures execution telemetry for generative AI applications and agents, including model calls, prompts, tool invocations, retrieval steps, latency, token usage, errors, and run relationships so teams can debug and monitor behavior in Microsoft Foundry and Azure Monitor. AI observability intermediate 3 commands Aliases: Foundry tracing, agent tracing, LLM tracing, AI distributed tracing Quick peek Open full term page

AI and Machine Learning verified Responsible AI policy Microsoft Learn guidance for Responsible AI practices in Azure OpenAI emphasizes defined content policies, misuse detection, user blocking mechanisms, human review, safety evaluation, and escalation. In Azure, a Responsible AI policy is the operating rule set that turns those practices into enforceable product behavior. Azure OpenAI intermediate 7 commands Aliases: AI safety policy, Azure OpenAI responsible AI policy, generative AI policy, AI acceptable use policy, Responsible AI guardrails Quick peek Open full term page

AI and Machine Learning verified Provisioned throughput for AI Provisioned throughput for AI in Microsoft Foundry allocates provisioned throughput units to supported model deployments. PTUs give reserved processing capacity for predictable latency and throughput, with deployment choices such as regional, data-zone, or global provisioned capacity and separate reservation-based billing options. Microsoft Foundry advanced 6 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium Azure OpenAI Service Azure OpenAI Service provides managed access to OpenAI model capabilities through Azure endpoints and enterprise controls. Generative AI fundamentals 11 commands Aliases: Azure OpenAI 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 Foundry Local Foundry Local is an on-device AI runtime and SDK for shipping applications that run curated generative AI models locally on user hardware. Microsoft Foundry intermediate 5 commands Aliases: Microsoft Foundry Local, Foundry Local CLI, on-device AI inference, local AI runtime Quick peek Open full term page

AI and Machine Learning premium Foundry resource A Foundry resource is the primary Azure resource for building, deploying, and managing generative AI models, agents, evaluations, and applications. Microsoft Foundry intermediate 5 commands Aliases: Microsoft Foundry resource, Foundry AIServices resource, AI Services Foundry resource Quick peek Open full term page

AI and Machine Learning premium Embedding An embedding is a list of numbers that captures meaning in a way software can compare. Instead of matching only exact words, an application can compare the embedding for a user question with embeddings for documents, products, tickets, or records. Similar ideas end up near each other in vector space even when the wording differs. In Azure, embeddings commonly come from Azure OpenAI models and are stored in vector indexes. Generative AI fundamentals 4 commands Aliases: Embedding, text embedding, vector embedding, embedding vector, embedding Quick peek Open full term page

AI and Machine Learning premium Grounded generation Grounded generation is a generative AI pattern where model responses are based on supplied source material, retrieved enterprise content, tool results, or other approved grounding data. Generative AI intermediate 4 commands Aliases: grounded AI generation, grounded response generation, RAG answer generation Quick peek Open full term page

AI and Machine Learning premium Grounding Grounding is the practice of supplying relevant external information, retrieved content, or tool results so a generative AI model can base its answer on known context. AI platform and search intermediate 4 commands Aliases: AI grounding, model grounding, grounding a prompt Quick peek Open full term page

AI and Machine Learning premium Model deployment Model deployment is the step where a trained or selected model becomes something an application can actually call. The model may have performed well in experiments, but deployment decides how it is hosted, secured, scaled, monitored, and routed. Generative AI fundamentals 4 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium Context window The amount of input and output text a model can process in one request. Generative AI advanced 3 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning verified Prompt A prompt is what you give an AI model so it knows what to do. Generative AI fundamentals 6 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning verified Prompt Shields Prompt Shields is a Microsoft Foundry and Azure AI Content Safety capability that detects adversarial inputs against language-model applications. It covers direct user prompt attacks and indirect document attacks, helping apps identify attempts to override instructions, exfiltrate data, or manipulate model behavior before generation. Azure AI services intermediate 6 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning verified Prompt engineering Prompt engineering is the craft of asking an AI model for work in a way it can follow reliably. It includes clear instructions, examples, context, boundaries, and required output formats. In Azure OpenAI and Foundry applications, prompt engineering is not magic phrasing; it is application design. A strong prompt explains the task, what evidence to use, what to avoid, and how success will be measured. It still needs testing because one good example does not prove the prompt works everywhere. AI platform and search intermediate 5 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning verified RAG Retrieval-augmented generation grounds generative AI responses in retrieved enterprise content instead of relying only on model training. In Azure, RAG commonly combines Azure AI Search indexes, grounding data, embeddings, and an Azure OpenAI or Foundry model to answer using current, domain-specific information. Generative AI advanced 5 commands Aliases: Retrieval augmented generation, retrieval-augmented generation Quick peek Open full term page

AI and Machine Learning field-manual-complete Tokenizer A tokenizer converts text into the tokens consumed and produced by generative AI models. In Azure OpenAI and Foundry model workloads, tokenization determines how prompts, retrieved context, tool results, and completions fit within model context limits, rate limits, and billing meters. Azure OpenAI and Foundry Models intermediate 5 commands Aliases: AI tokenizer, model tokenizer, tokenization, token counter, text tokenizer Quick peek Open full term page

AI and Machine Learning template-specs-upgraded Safety system message Microsoft Learn explains that safety system messages guide Azure OpenAI model behavior, improve response quality, and reduce the likelihood of harmful outputs. They are one layer in a broader safety strategy and are also described as system prompts or metaprompts. Microsoft Foundry intermediate 5 commands Aliases: Azure OpenAI safety system message, safety metaprompt, system prompt safety guidance, Foundry safety message, AI safety instructions Quick peek Open full term page

AI and Machine Learning field-manual-ready Model A model is a trained or selected AI artifact that performs predictions, generation, classification, embeddings, or another inference task. Generative AI fundamentals 4 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning field-manual-ready Model evaluation Model evaluation measures a model against defined data, tasks, metrics, thresholds, safety checks, and business expectations. Azure Machine Learning intermediate 4 commands Aliases: No aliases yet 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 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 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 AI connection AI connection is a Microsoft Foundry project connection that links the project to an external or Azure resource such as models, storage, search, or services. In everyday Azure work, teams use it to let AI applications and agents use approved resources without every prototype hardcoding endpoints and credentials. The useful evidence is connection name, target AI platform intermediate 4 commands Aliases: Foundry connection, AI project connection, connected resource, AI service connection 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 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 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 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 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 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 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 Multi-service AI account Multi-service AI account means a shared Azure AI services account for applications that need several supported AI capabilities from one governed endpoint boundary. You see it when teams connect language, vision, speech, translation, or content-understanding features to production applications. Think of it as one managed account boundary for several AI capabilities, not one unlimited permission bucket. It matters because the setting changes how teams design, secure, operate, and troubleshoot the workload. Before changing it in production, know the owner, dependency, evidence, expected result, and rollback path. Azure AI services intermediate 4 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium Multi-service AI resource Multi-service AI resource means an Azure AI resource that exposes supported AI service capabilities through one managed resource object. You see it when teams build applications that combine language, vision, speech, translation, or content services without creating a separate resource for every feature. Think of it as one Azure resource boundary for supported AI capabilities, with identity, network, monitoring, and billing attached. It matters because the setting changes how teams design, secure, operate, and troubleshoot the workload. Before changing it in production, know the owner, dependency, evidence, expected result, and rollback path. Azure AI services fundamentals 4 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium AI quota AI quota is the Azure allocation that limits model deployment capacity, usually by subscription, region, model, and deployment type, using measures such as tokens per minute, requests per minute, concurrent requests, or provisioned throughput. Microsoft Foundry intermediate 3 commands Aliases: Foundry quota, Azure OpenAI quota, model quota, TPM quota, RPM quota Quick peek Open full term page

Monitoring and Observability premium AI service diagnostic settings AI service diagnostic settings are Azure Monitor settings on an Azure AI or Foundry Tools resource that route resource logs and platform metrics to destinations such as Log Analytics, Storage, or Event Hubs for investigation and retention. Azure Monitor intermediate 3 commands Aliases: Azure AI diagnostic settings, Foundry Tools diagnostic logging, Cognitive Services diagnostic settings, AI resource logs Quick peek Open full term page

AI and Machine Learning premium AI service endpoint An AI service endpoint is the HTTPS base address that applications use to call an Azure AI or Foundry Tools resource. It identifies the resource, region or custom subdomain, and may resolve through public DNS or a private endpoint. Azure AI services fundamentals 3 commands Aliases: Azure AI endpoint, Cognitive Services endpoint, Foundry Tools endpoint, AI resource URL Quick peek Open full term page

AI and Machine Learning premium AI service key An AI service key is a secret access key for an Azure AI service resource. Clients pass it, commonly with the Ocp-Apim-Subscription-Key header, to authenticate API requests when key-based authentication is used. Azure AI services fundamentals 3 commands Aliases: Azure AI service key, Cognitive Services key, Ocp-Apim-Subscription-Key, resource key Quick peek Open full term page

AI and Machine Learning premium AI services account key An AI services account key is a secret key for a multi-service Azure AI or Microsoft Foundry resource. It can authenticate requests for supported services tied to that resource, making storage, rotation, and access control especially important. Azure AI services intermediate 3 commands Aliases: multi-service account key, Foundry resource key, AIServices account key, Cognitive Services account key Quick peek Open full term page

AI and Machine Learning premium AI services endpoint An AI services endpoint is the base URL for a multi-service Azure AI or Microsoft Foundry resource. Applications combine this endpoint with a supported API path and authentication method to call the resource. Azure AI services fundamentals 3 commands Aliases: multi-service endpoint, Foundry resource endpoint, AIServices endpoint, Cognitive Services endpoint Quick peek Open full term page

AI and Machine Learning premium AI services resource An AI services resource is the Azure resource, commonly Microsoft.CognitiveServices/accounts with kind AIServices, that provides the governance scope for AI service access, networking, billing, monitoring, keys, endpoints, model deployments, projects, and related configuration. Azure AI services fundamentals 3 commands Aliases: Azure AI services resource, Foundry resource, AIServices resource, Cognitive Services account Quick peek Open full term page