John Savill’s Technical Training presents an in-depth exploration of Microsoft Foundry IQ, detailing its AI-driven knowledge retrieval, reasoning processes, and integration with Azure AI Search for technical audiences.

Deep Dive into Foundry IQ and Azure AI Search

Author: John Savill’s Technical Training

Overview

This session covers Microsoft Foundry IQ with a focus on:

  • How Foundry IQ leverages modern AI models and RAG (Retrieval Augmented Generation)
  • Integration with Azure AI Search
  • Management of multiple, remote, and new types of knowledge sources
  • Agentic RAG and reasoning architecture
  • Limits (SKUs, resource quotas, collections)
  • Best practices for knowledge base structuring and use
  • Output modes, self-reflection features, and demonstration of reasoning paths

Key Topics and Chapters

  • 00:00 - Introduction: Overview of Foundry IQ’s role in Microsoft AI landscape
  • 00:15 - AI models and their knowledge: How AI models ingest and utilize information
  • 01:31 - RAG to the rescue: Introduction to Retrieval Augmented Generation for accurate Q&A
  • 03:12 - Azure AI Search: Foundational component for structured knowledge retrieval
  • 08:24 - Foundry IQ: Feature walkthrough
  • 09:03 - Agentic RAG: Agent-based approaches for enhanced reasoning
  • 09:32 - Multiple knowledge sources: Managing complex knowledge bases
  • 10:18 - New/Remote knowledge sources: Flexibility in content ingestion
  • 11:55 - Knowledge bases: Tying together knowledge and Azure AI Search resources
  • 14:22 - Use of Azure AI Search resource
  • 15:44 - Adding knowledge sources: Best practices
  • 17:09 - SKU limits & quotas: Operational considerations (See documentation)
  • 17:46 - Collections of knowledge sources
  • 18:49 - Reasoning effort & self-reflection: How the model explains its answers
  • 22:31 - Importance of good descriptions/instructions
  • 23:51 - Output modes and live demonstrations
  • 33:11 - Peeking inside its thinking & summary
  • 35:15 - IQs collaboration scenarios

Key Links & Resources

Technical Takeaways

  • Foundry IQ builds on Azure AI Search and AI models to provide scalable, extensible, and explainable retrieval workflows
  • Remote and varied knowledge sources facilitate success in complex, enterprise-scale data environments
  • Agentic RAG improves retrieval accuracy through deeper reasoning steps
  • Importance of good knowledge base design, resource quotas, and clear instructions for optimal performance

Additional Learning

  • Onboard to Azure: https://learn.onboardtoazure.com
  • DevOps/Azure Master Classes and Certification Playlists (see channel links above)

Author

John Savill’s Technical Training

For full demonstrations and all feature walkthroughs, see the video link and supplementary links above.