Programmatically extract data and apply schemas to unstructured documents across text-based and multi-modal content using Azure AI Foundry, Azure OpenAI, Azure AI Content Understanding, and Cosmos DB.

Designed to help customers transition their SQL queries to new environments quickly and efficiently. This accelerator is particularly useful for organizations modernizing their data estates, as it simplifies the process of translating SQL queries from various dialects.

A comprehensive guide for modernizing mainframe applications (IBM z/OS, Unisys, GCOS, ACOS) using Azure AI Foundry with GitHub and Azure DevOps, preserving existing investments while enabling modern DevOps and AI capabilities.

Bud AI Foundry - A comprehensive inference stack for compound AI deployment, optimization and scaling. Bud Stack provides intelligent infrastructure automation, performance optimization, and seamless model deployment across multi-cloud/multi-hardware environments.

AI Foundry Agent with ISV Partner MCP Server integration

This example shows how to propagate a user's Entra ID identity end-to-end — from the browser, through an AI Foundry agent with MCP tools, through API Management, all the way to the backend API. No service accounts in the data path.

MCP Server that supports Azure AI Foundry image generation and editing capabilities.

AIFoundryGenie is a small, Python-based sample/framework repo that shows how to create and run Azure AI Foundry Agents that can query a Databricks AI/BI Genie Space (via the Databricks AI Bridge) and then return formatted, data-driven answers.

Azure-native RAG knowledge base with FastAPI, Azure AI Search, Azure OpenAI, Blob Storage, and Container Apps.

Connect AI agents to financial markets using a universal trading interface with an open standard for seamless integration.

An example of calling Grounding with Bing Search in Semantic Kernel.

Example scripts to build and chat with Azure AI Foundry Agents using Microsoft Fabric as a live grounding/knowledge source