You’ll learn how to build enterprise-ready AI with Azure Foundry to transform your team with structured, auditable, and compliant AI solutions — directly inside the Microsoft cloud — in this episode.

Who this episode is for:
• You want practical strategies you can apply instantly
• You want real execution — not theory
• You want to unlock Microsoft 365, Power Platform, and Azure for real business outcomes

Scenario:
AI solutions lack structure, traceability, and enterprise-grade governance, leading to inefficiencies and compliance risks.

Step-by-step – what they will learn:
• What Azure Foundry does to create enterprise-ready AI
• How to configure its model, instructions, and tools for disciplined performance
• How threads, runs, and run steps ensure auditable, reproducible workflows
• How to integrate it with Microsoft tools like SharePoint, Power Automate, and Azure AI Search for seamless operations

Tools + tech included:
• Microsoft 365 / Power Automate / Teams / SharePoint / Azure
• Azure Foundry threads, runs, and custom tools
• MCP (Model Context Protocol) for scalable integration
• Enterprise-grade security with Microsoft Entra

Practical payoff (why this matters):
• Reduce manual effort with AI-driven automation
• Improve clarity and compliance with structured logs
• Achieve faster, more reliable workflows

Example business cases listeners can apply immediately:
• Automating contract analysis with traceable outputs
• Generating auditable reports from enterprise data
• Enabling secure, tool-connected AI operations

Outcome statement:
By the end of this episode — you’ll be able to create governed, auditable AI agents that transform workflows and deliver real business value.

Call-to-action:
Start building your skills today and transform your workflows with Azure Foundry!

#aiaudittrail #modelexecution #azureai #aideployment #customapis

CHAPTERS:
00:00 - Azure AI Agent Service Overview
03:16 - Azure AI Agent Service Threads Explained
06:25 - Azure AI Agent Service Runs and Run Steps
09:34 - Arsenal and Alliances in AI
13:02 - Conclusion and Key Takeaways

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