Microsoft Fields
Class Fields 32 members
Models published by Microsoft.
## Azure AI Content Safety ## Introduction Azure AI Content Safety is a safety system for monitoring content generated by both foundation models and humans. Detect and block potential risks, threats, and quality problems. You can build an advanced safety system for foundation models to detect and mitigate harmful content and risks in user prompts and AI-generated outputs. Use Prompt Shields to detect and block prompt injection attacks, groundedness detection to pinpoint ungrounded or hallucinated materials, and protected material detection to identify copyrighted or owned content. ## Core Features - **Block harmful input and output** - **Description**: Detect and block violence, hate, sexual, and self-harm content for both text, images and multimodal. Configure severity thresholds for your specific use case and adhere to your responsible AI policies. - **Key Features**: Violence, hate, sexual, and self-harm content detection. Custom blocklist. - **Policy customization with custom categories** - **Description**: Create unique content filters tailored to your requirements using custom categories. Quickly train a new custom category by providing examples of content you need to block. - **Key Features**: Custom categories - **Identify the security risks** - **Description**: Safeguard your AI applications against prompt injection attacks and jailbreak attempts. Identify and mitigate both direct and indirect threats with prompt shields. - **Key Features**: Direct jailbreak attack, indirect prompt injection from docs. - **Detect and correct Gen AI hallucinations** - **Description**: Identify and correct generative AI hallucinations and ensure outputs are reliable, accurate, and grounded in data with groundedness detection. - **Key Features**: Groundedness detection, reasoning, and correction. - **Identify protected material** - **Description**: Pinpoint copyrighted content and provide sources for preexisting text and code with protected material detection. - **Key Features**: Protected material for code, protected material for text ## Use Cases - Generative AI services screen user-submitted prompts and generated outputs to ensure safe and appropriate content. - Online marketplaces monitor and filter product listings and other user-generated content to prevent harmful or inappropriate material. - Gaming platforms manage and moderate user-created game content and in-game communication to maintain a safe environment. - Social media platforms review and regulate user-uploaded images and posts to enforce community standards and prevent harmful content. - Enterprise media companies implement centralized content moderation systems to ensure the safety and appropriateness of their published materials. - K-12 educational technology providers filter out potentially harmful or inappropriate content to create a safe learning environment for students and educators. ## Benefits - **No ML experience required**: Incorporate content safety features into your projects with no machine learning experience required. - **Effortlessly customize your RAI policies**: Customizing your content safety classifiers can be done with one line of description, a few samples using Custom Categories. - **State of the art models**: ready for use APIs, SOTA models, and flexible deployment options reduce the need for ongoing manual training or extensive customization. Microsoft has a science team and policy experts working on the frontier of Gen AI to constantly improve the safety and security models to ensure our customers can develop and deploy generative AI safely and responsibly. - **Global Reach**: Support more than 100 languages, enabling businesses to communicate effectively with customers, partners, and employees worldwide. - **Scalable and Reliable**: Built on Azure’s cloud infrastructure, the Azure AI Content Safety service scales automatically to meet demand, from small business applications to global enterprise workloads. - **Security and Compliance**: Azure AI Content Safety runs on Azure’s secure cloud infrastructure, ensuring data privacy and compliance with global standards. User data is not stored after the translation process. - **Flexible deployment**: Azure AI Content Safety can be deployed on cloud, on premises and on devices. ## Technical Details - **Deployment** - **Container for on-premise deployment**: [Content safety containers overview - Azure AI Content Safety - Azure AI services | Microsoft Learn](https://learn.microsoft.com/azure/ai-services/content-safety/how-to/containers/container-overview) - **Embedded Content Safety**: [Embedded Content Safety - Azure AI Content Safety - Azure AI services | Microsoft Learn](https://learn.microsoft.com/azure/ai-services/content-safety/how-to/embedded-content-safety?tabs=windows-target%2Ctext) - **Cloud**: [Azure AI Content Safety documentation - Quickstarts, Tutorials, API Reference - Azure AI services | Microsoft Learn](https://learn.microsoft.com/azure/ai-services/content-safety/) - **Requirements**: Requirements vary feature by feature, for more details, refer to the Azure AI Content Safety documentation: [Azure AI Content Safety documentation - Quickstarts, Tutorials, API Reference - Azure AI services | Microsoft Learn](https://learn.microsoft.com/azure/ai-services/content-safety/). - **Support**: Azure AI Content Safety is part of Azure AI Services. Support options for AI Services can be found here: [Azure AI services support and help options - Azure AI services | Microsoft Learn](https://learn.microsoft.com/azure/ai-services/cognitive-services-support-options?context=%2Fazure%2Fai-services%2Fcontent-safety%2Fcontext%2Fcontext). ## Pricing Explore pricing options here: [Azure AI Content Safety - Pricing | Microsoft Azure](https://azure.microsoft.com/pricing/details/cognitive-services/content-safety/).
public static readonly AIFoundryModel AzureAIContentSafetyAzureAIContentUnderstanding Section titled AzureAIContentUnderstanding staticreadonly AIFoundryModel # Azure AI Content Understanding ## Introduction Azure AI Content Understanding empowers you to transform unstructured multimodal data—such as text, images, audio, and video—into structured, actionable insights. By streamlining content processing with advanced AI techniques like schema extraction and grounding, it delivers accurate structured data for downstream applications. Offering prebuilt templates for common use cases and customizable models, it helps you unify diverse data types into a single, efficient pipeline, optimizing workflows and accelerating time to value. ## Core Features - **Multimodal data ingestion** Ingest a range of modalities such as documents, images, audio, or video. Use a variety of AI models to convert the input data into a structured format that can be easily processed and analyzed by downstream services or applications. - **Customizable output schemas** Customize the schemas of extracted results to meet your specific needs. Tailor the format and structure of summaries, insights, or features to include only the most relevant details—such as key points or timestamps—from video or audio files. - **Confidence scores** Leverage confidence scores to minimize human intervention and continuously improve accuracy through user feedback. - **Output ready for downstream applications** Automate business processes by building enterprise AI apps or agentic workflows. Use outputs that downstream applications can consume for reasoning with retrieval-augmented generation (RAG). - **Grounding** Ensure the information extracted, inferred, or abstracted is represented in the underlying content. - **Automatic labeling** Save time and effort on manual annotation and create models quicker by using large language models (LLMs) to extract fields from various document types. ## Use Cases - **Post-call analytics for call centers**: Generate insights from call recordings, track key performance indicators (KPIs), and answer customer questions more accurately and efficiently. - **Tax process automation**: Streamline the tax return process by extracting data from tax forms to create a consolidated view of information across various documents. - **Media asset management**: Extract features from images and videos to provide richer tools for targeted content and enhance media asset management solutions. - **Chart understanding**: Enhance chart understanding by automating the analysis and interpretation of various types of charts and diagrams using Content Understanding. ## Benefits - **Streamline workflows**: Azure AI Content Understanding standardizes the extraction of content, structure, and insights from various content types into a unified process. - **Simplify field extraction**: Field extraction in Content Understanding makes it easier to generate structured output from unstructured content. Define a schema to extract, classify, or generate field values with no complex prompt engineering. - **Enhance accuracy**: Content Understanding employs multiple AI models to analyze and cross-validate information simultaneously, resulting in more accurate and reliable results. - **Confidence scores & grounding**: Content Understanding ensures the accuracy of extracted values while minimizing the cost of human review. ## Technical Details - **Deployment**: Deployment options may vary by service, reference the following docs for more information: [Create an Azure AI Services multi-service resource](https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/create-multi-service-resource). - **Requirements**: Requirements may vary depending on the input data you are analyzing, reference the following docs for more information: [Service quotas and limits](https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/service-limits). - **Support**: Support options for AI Services can be found here: [Azure AI services support and help options](https://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-support-options?view=doc-intel-4.0.0). ## Pricing View up-to-date pay-as-you-go pricing details here: [Azure AI Content Understanding pricing](https://azure.microsoft.com/en-us/pricing/details/content-understanding/).
public static readonly AIFoundryModel AzureAIContentUnderstandingAzureAIDocumentIntelligence Section titled AzureAIDocumentIntelligence staticreadonly AIFoundryModel ## Azure AI Document Intelligence Document Intelligence is a cloud-based service that enables you to build intelligent document processing solutions. Massive amounts of data, spanning a wide variety of data types, are stored in forms and documents. Document Intelligence enables you to effectively manage the velocity at which data is collected and processed and is key to improved operations, informed data-driven decisions, and enlightened innovation. ## Core Features - **General extraction models** - **Description**: General extraction models enable text extraction from forms and documents and return structured business-ready content ready for your organization's action, use, or development. - **Key Features** - Read model allows you to extract written or printed text liens, words, locations, and detected languages. - Layout model, on top of text extraction, extracts structural information like tables, selection marks, paragraphs, titles, headings, and subheadings. Layout model can also output the extraction results in a Markdown format, enabling you to define your semantic chunking strategy based on provided building blocks, allowing for easier RAG (Retrieval Augmented Generation). - **Prebuilt models** - **Description**: Prebuilt models enable you to add intelligent document processing to your apps and flows without having to train and build your own models. Prebuilt models extract a pre-defined set of fields depending on the document type. - **Key Features** - **Financial Services and Legal Documents**: Credit Cards, Bank Statement, Pay Slip, Check, Invoices, Receipts, Contracts. - **US Tax Documents**: Unified Tax, W-2, 1099 Combo, 1040 (multiple variations), 1098 (multiple variations), 1099 (multiple variations). - **US Mortgage Documents**: 1003, 1004, 1005, 1008, Closing Disclosure. - **Personal Identification Documents**: Identity Documents, Health Insurance Cards, Marriage Certificates. - **Custom models** - **Description**: Custom models are trained using your labeled datasets to extract distinct data from forms and documents, specific to your use cases. Standalone custom models can be combined to create composed models. - **Key Features** - **Document field extraction models** - **Custom generative**: Build a custom extraction model using generative AI for documents with unstructured format and varying templates. - **Custom neural**: Extract data from mixed-type documents. - **Custom template**: Extract data from static layouts. - **Custom composed**: Extract data using a collection of models. Explicitly choose the classifier and enable confidence-based routing based on the threshold you set. - **Custom classification models** - **Custom classifier**: Identify designated document types (classes) before invoking an extraction model. - **Add-on capabilities** - **Description**: Use the add-on features to extend the results to include more features extracted from your documents. Some add-on features incur an extra cost. These optional features can be enabled and disabled depending on the scenario of the document extraction. - **Key Features** - High resolution extraction - Formula extraction - Font extraction - Barcode extraction - Language detection - Searchable PDF output ## Use Cases - **Accounts payable**: A company can increase the efficiency of its accounts payable clerks by using the prebuilt invoice model and custom forms to speed up invoice data entry with a human in the loop. The prebuilt invoice model can extract key fields, such as Invoice Total and Shipping Address. - **Insurance form processing**: A customer can train a model by using custom forms to extract a key-value pair in insurance forms and then feeds the data to their business flow to improve the accuracy and efficiency of their process. For their unique forms, customers can build their own model that extracts key values by using custom forms. These extracted values then become actionable data for various workflows within their business. - **Bank form processing**: A bank can use the prebuilt ID model and custom forms to speed up the data entry for "know your customer" documentation, or to speed up data entry for a mortgage packet. If a bank requires their customers to submit personal identification as part of a process, the prebuilt ID model can extract key values, such as Name and Document Number, speeding up the overall time for data entry. - **Robotic process automation (RPA)**: Using the custom extraction model, customers can extract specific data needed from distinct types of documents. The key-value pair extracted can then be entered into various systems such as databases, or CRM systems, through RPA, replacing manual data entry. Customers can also use custom classification model to categorize documents based on their content and file them in proper location. As such, an organized set of data extracted from the custom model can be an essential first step to document RPA scenarios for businesses that manage large volumes of documents regularly. ## Benefits - **No experience required**: Incorporate Document Intelligence features into your projects with no machine learning experience required. - **Effortlessly customize your models**: Training your own custom extraction and classification model can be done with as little as one document labeled, making it easy to train your own models. - **State of the art models**: ready for use APIs, constantly enhanced models, and flexible deployment options reduce the need for ongoing manual training or extensive customization. ## Technical Details: - **Deployment**: Deployment options may vary by service, reference the following docs for more information: [Use Document Intelligence models](https://learn.microsoft.com/azure/ai-services/document-intelligence/how-to-guides/use-sdk-rest-api?view=doc-intel-3.1.0&tabs=linux&pivots=programming-language-rest-api) and [Install and run containers](https://learn.microsoft.com/azure/ai-services/document-intelligence/containers/install-run?view=doc-intel-4.0.0&tabs=read). - **Requirements**: Requirements may vary slightly depending on the model you are using to analyze the documents. Reference the following docs for more information: [Service quotas and limits](https://learn.microsoft.com/azure/ai-services/document-intelligence/service-limits?view=doc-intel-4.0.0). - **Support**: Support options for AI Services can be found here: [Azure AI services support and help options - Azure AI services | Microsoft Learn](https://learn.microsoft.com/azure/ai-services/cognitive-services-support-options?context=%2Fazure%2Fai-services%2Fdocument-intelligence%2Fcontext%2Fcontext&view=doc-intel-4.0.0). ## Pricing View up-to-date pricing information for the pay-as-you-go pricing model here: [Azure AI Document Intelligence pricing](https://azure.microsoft.com/pricing/details/ai-document-intelligence/).
public static readonly AIFoundryModel AzureAIDocumentIntelligence Azure AI Language service.
public static readonly AIFoundryModel AzureAILanguage Azure AI Translator service.
public static readonly AIFoundryModel AzureAITranslator ## Azure AI Vision ## Introduction The Azure AI Vision service gives you access to advanced algorithms that process images and videos and return insights based on the visual features and content you are interested in. Azure AI Vision can power a diverse set of scenarios, including digital asset management, video content search & summary, identity verification, generating accessible alt-text for images, and many more. The key product categories for Azure AI Vision include Video Analysis, Image Analysis, Face, and Optical Character Recognition. ## Core Features - **Video analysis** - **Description**: Video Analysis includes video-related features like Spatial Analysis and Video Retrieval. Spatial Analysis analyzes the presence and movement of people on a video feed and produces events that other systems can respond to. Video Retrieval lets you create an index of videos that you can search in your natural language. - **Key Features**: Video retrieval, spatial analysis, person counting, person in a zone, person crossing a line, person distance - **Face** - **Description**: The Face service provides AI algorithms that detect, recognize, and analyze human faces in images. Facial recognition software is important in many different scenarios, such as identification, touchless access control, and face blurring for privacy. - **Key Features**: Face detection and analysis, face liveness, face identification, face verification - **Image analysis** - **Description**: The Image Analysis service extracts many visual features from images, such as objects, faces, adult content, and auto-generated text descriptions. - **Key Features**: Image tagging, image classification, object detection, image captioning, dense captioning, face detection, optical character recognition, image embeddings, and image search - **Optical character recognition** - **Description**: The Optical Character Recognition (OCR) service extracts text from images. You can use the Read API to extract printed and handwritten text from photos and documents. It uses deep-learning-based models and works with text on various surfaces and backgrounds. These include business documents, invoices, receipts, posters, business cards, letters, and whiteboards. The OCR APIs support extracting printed text in several languages. - **Key Features**: OCR ## Use Cases - Boost content discovery with image analysis - Verify identities with the Face service - Search content in videos ## Benefits - **No experience required**: Incorporate vision features into your projects with no machine learning experience required. - **Effortlessly customize your models**: Customizing your image classification and object detection models can be done with as little as one image per tag, making it easy to train your own models. - **State of the art models**: Ready to use APIs, constantly enhanced models, and flexible deployment options reduce the need for ongoing manual training or extensive customization. ## Technical Details - **Deployment**: Deployment options may vary by service, reference the following docs for more information: [Image Analysis Overview](https://learn.microsoft.com/azure/ai-services/computer-vision/overview-image-analysis?tabs=4-0), [Optical Character Recognition Overview](https://learn.microsoft.com/azure/ai-services/computer-vision/overview-ocr), [Video Analysis Overview](https://learn.microsoft.com/azure/ai-services/computer-vision/intro-to-spatial-analysis-public-preview?tabs=sa), and [Face Overview](https://learn.microsoft.com/azure/ai-services/computer-vision/overview-identity). - **Requirements**: Requirements may very slightly depending on the data you are analyzing, reference the following docs for more information: [Image Analysis Overview](https://learn.microsoft.com/azure/ai-services/computer-vision/overview-image-analysis?tabs=4-0), [Optical Character Recognition Overview](https://learn.microsoft.com/azure/ai-services/computer-vision/overview-ocr), [Video Analysis Overview](https://learn.microsoft.com/azure/ai-services/computer-vision/intro-to-spatial-analysis-public-preview?tabs=sa), and [Face Overview](https://learn.microsoft.com/azure/ai-services/computer-vision/overview-identity). - **Support**: Support options for AI Services can be found here: [Azure AI services support and help options - Azure AI services | Microsoft Learn](https://learn.microsoft.com/azure/ai-services/cognitive-services-support-options?context=%2Fazure%2Fai-services%2Fcomputer-vision%2Fcontext%2Fcontext). ## Pricing View up-to-date pricing information for the pay-as-you-go pricing model here: [Azure AI Vision pricing](https://azure.microsoft.com/pricing/details/cognitive-services/computer-vision).
public static readonly AIFoundryModel AzureAIVisionAzureLanguageLanguageDetection Section titled AzureLanguageLanguageDetection staticreadonly AIFoundryModel Language detection quickly and accurately identifies the language of any text, supporting over 100 languages and dialects, including the ISO 15924 standard for a select number of languages.
public static readonly AIFoundryModel AzureLanguageLanguageDetectionAzureLanguageTextPiiRedaction Section titled AzureLanguageTextPiiRedaction staticreadonly AIFoundryModel PII Redaction for Text automatically detects and masks sensitive information such as names, addresses, phone numbers, credit card details, and other personally identifiable information (PII) in unstructured text.
public static readonly AIFoundryModel AzureLanguageTextPiiRedaction Transcribes streaming or recorded audio into readable text across 140+ languages and dialects. Accuracy can be further optimized with custom models for your specialized use cases.
public static readonly AIFoundryModel AzureSpeechSpeechToText Text-to-speech enables your applications, tools, or devices to convert text into natural synthesized speech. It leverages advanced out-of-the-box [prebuilt neural voices](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?t
public static readonly AIFoundryModel AzureSpeechTextToSpeechAzureSpeechTextToSpeechAvatar Section titled AzureSpeechTextToSpeechAvatar staticreadonly AIFoundryModel Text to speech avatar converts text into a digital video of a human (either a standard avatar or a custom text to speech avatar) speaking with a natural-sounding voice. The text to speech avatar video can be synthesized asynchronously or in real time. Deve
public static readonly AIFoundryModel AzureSpeechTextToSpeechAvatar Voice Live API is a single unified API that enables low-latency, high-quality speech to speech interactions for voice agents.
public static readonly AIFoundryModel AzureSpeechVoiceLiveAzureTranslatorDocumentTranslation Section titled AzureTranslatorDocumentTranslation staticreadonly AIFoundryModel Document translation is a cloud-based, multilingual service that uses AI to translate documents from one language to another while preserving the document layout.
public static readonly AIFoundryModel AzureTranslatorDocumentTranslationAzureTranslatorTextTranslation Section titled AzureTranslatorTextTranslation staticreadonly AIFoundryModel Text translation is a cloud-based, multilingual service that uses neural machine translation models (NMT) and/or large language models (LLM) to translate text from one language to another, supporting 135 languages.
public static readonly AIFoundryModel AzureTranslatorTextTranslation Azure Language Detection service.
public static readonly AIFoundryModel LanguageDetection MAI-DS-R1 is a DeepSeek-R1 reasoning model that has been post-trained by the Microsoft AI team to fill in information gaps in the previous version of the model and improve its harm protections while maintaining R1 reasoning capabilities.
public static readonly AIFoundryModel MaiDSR1 Model router is a deployable AI model that is trained to select the most suitable large language model (LLM) for a given prompt.
public static readonly AIFoundryModel ModelRouter Refresh of Phi-3-mini model.
public static readonly AIFoundryModel Phi35MiniInstruct A new mixture of experts model
public static readonly AIFoundryModel Phi35MoEInstruct Refresh of Phi-3-vision model.
public static readonly AIFoundryModel Phi35VisionInstruct Same Phi-3-medium model, but with a larger context size for RAG or few shot prompting.
public static readonly AIFoundryModel Phi3Medium128kInstruct A 14B parameters model, proves better quality than Phi-3-mini, with a focus on high-quality, reasoning-dense data.
public static readonly AIFoundryModel Phi3Medium4kInstruct Same Phi-3-mini model, but with a larger context size for RAG or few shot prompting.
public static readonly AIFoundryModel Phi3Mini128kInstruct Tiniest member of the Phi-3 family. Optimized for both quality and low latency.
public static readonly AIFoundryModel Phi3Mini4kInstruct Same Phi-3-small model, but with a larger context size for RAG or few shot prompting.
public static readonly AIFoundryModel Phi3Small128kInstruct A 7B parameters model, proves better quality than Phi-3-mini, with a focus on high-quality, reasoning-dense data.
public static readonly AIFoundryModel Phi3Small8kInstruct Phi-4 14B, a highly capable model for low latency scenarios.
public static readonly AIFoundryModel Phi4 3.8B parameters Small Language Model outperforming larger models in reasoning, math, coding, and function-calling
public static readonly AIFoundryModel Phi4MiniInstruct Lightweight math reasoning model optimized for multi-step problem solving
public static readonly AIFoundryModel Phi4MiniReasoning First small multimodal model to have 3 modality inputs (text, audio, image), excelling in quality and efficiency
public static readonly AIFoundryModel Phi4MultimodalInstruct State-of-the-art open-weight reasoning model.
public static readonly AIFoundryModel Phi4Reasoning Azure Language Text PII service.
public static readonly AIFoundryModel TextPii