Official Technical Resources: Microsoft (page 18)
Official Technical Resources · Microsoft: 312 entries in total; this page lists entries 256–270.
Use Document Intelligence incremental classifiers
Incrementally train custom classifiers by adding new samples to existing classes or adding new classes.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Multimodal Models · Structured Outputs · Retrieval-Augmented Generation (RAG)
Link last checked: 2026-09-24
Understanding Document Intelligence Layout API Markdown Output Format
Description of the supported Markdown elements returned as part of the Layout API response and how to use the response in your applications.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Multimodal Models · Structured Outputs · Retrieval-Augmented Generation (RAG)
Link last checked: 2026-09-24
Document Intelligence query field extraction
Use Document Intelligence query fields to extend model schema.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Multimodal Models · Structured Outputs · Retrieval-Augmented Generation (RAG)
Link last checked: 2026-09-24
Retrieval-Augmented Generation with Azure Document Intelligence in Foundry Tools
Introduction to how semantic chunking can help with Retrieval-Augmented Generation (RAG) implementation using Azure Document Intelligence in Foundry Tools Layout model.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Multimodal Models · Structured Outputs · Retrieval-Augmented Generation (RAG)
Link last checked: 2026-09-24
Configure Language docker containers
Language service provides each container with a common configuration framework, so that you can easily configure and manage storage, logging, and security settings for your containers.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Agent · Agent Frameworks
Link last checked: 2026-09-24
Project versioning
Learn how versioning works in conversational language understanding
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Agent · Agent Frameworks
Link last checked: 2026-09-24
Service limits for Azure Language in Foundry Tools
Data and service limitations for Azure Language in Foundry Tools features.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Tool Calling · AI Agent
Link last checked: 2026-09-24
Language encryption of data at rest
Learn how Azure Language service encrypts your data when persisted to the cloud.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Agent · Agent Frameworks
Link last checked: 2026-09-24
Azure Language tools and agents
Learn how Azure Language in Foundry Tools integrates with Microsoft Foundry, including Model Context Protocol (MCP) server endpoints, intent routing agents, and exact question answering agents.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Tool Calling · AI Agent
Link last checked: 2026-09-24
Model lifecycle
This article describes the timelines for models and model versions used by Language service features.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Agent · Agent Frameworks
Link last checked: 2026-09-24
Multilingual and emoji support in Language features
Learn about offsets caused by multilingual and emoji encodings in Language service features.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Agent · Agent Frameworks
Link last checked: 2026-09-24
When to use conversational language understanding or orchestration workflow apps
Learn when to choose between conversational language understanding or orchestration workflow.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Supervised Learning · Embedding
Link last checked: 2026-09-24
Best practices for conversational language understanding
Learn how to apply best practices when you use conversational language understanding.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Supervised Learning · Embedding
Link last checked: 2026-09-24
Entity components
Learn how conversational language understanding extracts entities from text.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Supervised Learning · Embedding
Link last checked: 2026-09-24
Conversational language understanding model concepts
Learn core concepts for conversational language understanding models: evaluation metrics, the None intent, and accepted data formats.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Model Evaluation and Benchmarks · Large Language Model (LLM)
Link last checked: 2026-09-24