Prepare for an AI development projectSelect, deploy, and evaluate modelsCreate a generative AI chat appCreate a generative AI chat app that uses toolsOptimize generative AI model performanceApply guardrails to prevent the output of harmful contentConfigure secure AI infrastructure in AzureBuild and deploy an AI agentBuild an agent with custom toolsConnect MCP tools to Azure AI AgentsIntegrate an AI agent with Foundry IQPublish a Foundry agent to TeamsCreate an Agent-driven WorkflowDevelop an Azure AI agent with the Microsoft Agent Framework SDKDevelop a multi-agent solutionConnect to remote Azure AI Agents with the A2A protocolAnalyze textDevelop a text analysis agentUse speech-capable generative AI modelsCreate a speech-enabled appUse Azure Speech in an agentDevelop a Voice Live agentTranslate text and speechDevelop a vision-enabled chat appGenerate images with AIGenerate video with Sora 2 in Microsoft FoundryAnalyze images with Content UnderstandingExtract information from multimodal contentDevelop a Content Understanding client applicationAnalyze documents with Document IntelligenceCreate a knowledge mining solutionImplement RAG with your own data and Azure OpenAI modelsImplement vector and GPT searchesDevelop an AI copilot with Azure Cosmos DB for MongoDB and Azure OpenAIDevelop a RAG application with Spring AI and Azure OpenAIImplement the Evaluator-Optimizer agent pattern with Spring AIOptimize vector search in Azure Database for PostgreSQLBuild a semantic search application with Azure Cosmos DB for NoSQLImplement Microsoft Foundry Content Safety
Work IQ - Workplace intelligence for AI agents (optional)Fine-tune a language modelRecognize and synthesize speechBuild an automated RAG ingestion pipeline with Content UnderstandingGet Started with Azure AI ServicesManage Azure AI Services SecurityMonitor Azure AI ServicesUse an Azure AI Services ContainerImplement Azure AI Content Safety