Integrating AI agents with vast enterprise knowledge has been challenging for many of us, but Microsoft’s Foundry IQ within the Agent Framework. Foundry IQ is Microsoft’s intelligent knowledge layer for AI agents, built on Azure AI Search. By introducing a plug-and-play knowledge layer, Foundry IQ streamlines the connection between agents and diverse data sources, minimizing custom code and maximizing scalability.
The Problem with Traditional RAG
Most organizations using traditional retrieval-augmented generation (RAG) face repeated, fragmented development. Each team often builds its own data pipelines, embedding, and permission systems, leading to duplicated effort and inconsistent performance. Foundry IQ solves this by offering centralized, reusable Knowledge Bases that handle context provisioning and complexity behind the scenes.
Simplified Integration with Azure AI Search Context Provider
Developers can now connect agents to enterprise knowledge with ease using the Azure AI Search Context Provider. This feature streamlines indexing, vectorization, and advanced query planning, meaning developers only need to specify the relevant domain knowledge.
Key benefits include:
- Unified API: Works seamlessly across major LLM providers like Azure OpenAI and Anthropic
- Pluggable Context Providers: Effortlessly inject knowledge into agent workflows
- Tool and Protocol Support: Standardized interfaces simplify tool and multi-agent protocol integration
What Makes Foundry IQ Different?
Unlike simple retrieval systems, Foundry IQ treats knowledge access as an intelligent reasoning process. It offers:
- Query Planning: Breaks down complex queries into manageable sub-queries
- Multi-Hop Reasoning: Enables agents to connect information across multiple documents
- Answer Synthesis: Delivers comprehensive, cited answers, not just raw facts
- Unified Knowledge Bases: Abstracts and unifies data sources for natural querying
Internal Microsoft benchmarks reveal up to 36% improved response relevance for complex queries compared to older RAG solutions.
Flexible Retrieval Modes
The Azure AI Search Context Provider offers two retrieval modes to suit varying needs:
- Semantic Mode: Combines vector, keyword, and semantic search for quick, efficient queries
- Agentic Mode (Foundry IQ): Supports deep, multi-hop reasoning for research and analytics
Existing Azure AI Search users can easily upgrade to Foundry IQ, just link your current index, or reference an existing Knowledge Base for a seamless transition to advanced retrieval.
Customizing Agent Reasoning
Fine-tune agent performance by adjusting reasoning depth and output format:
- Retrieval Reasoning Effort: Choose from simple lookups to advanced multi-hop planning based on the task
- Output Modes: Opt for raw data extraction or synthesized, ready-to-use answers depending on the system’s needs
Easy Onboarding for Developers
Getting started is straightforward, building a RAG agent with Foundry IQ takes about 20 lines of Python code. Microsoft provides clear documentation, sample code, and video demos to help developers ramp up quickly.
Get Started
- Install:
pip install agent-framework-azure-ai-search --pre - Docs: Azure AI Search Context Provider documentation
- Video: Foundry IQ for multi-source AI knowledge bases
Key Takeaway: Smarter Agents, Streamlined Integration
The combination of Azure AI Search Context Provider and Foundry IQ sets a new standard for enterprise AI. Developers can now build intelligent agents capable of reasoning and synthesizing information across complex, siloed datasets, with less overhead and greater security. Whether you need rapid semantic search or deep analytical capabilities, this integration offers flexibility and scalability for modern enterprise needs.
Source: Microsoft Foundry Blog
Foundry IQ and Microsoft Agent Framework Are Redefining Enterprise AI Integration