Deep Dive into Foundry IQ and Azure AI Search
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.