Understanding RAG for agents
Unit 2 of 7 · Module 10: Build knowledge-enhanced AI agents with Foundry IQ
Before you start
Short explainers for ideas this lesson builds on. Watch these first if they're new to you.
Go deeper
Unlocks when you've watched the lesson.
Read this lesson
Where simple agents fall short
To see why Foundry IQ matters, start with the problems simple agents hit at work. First, the knowledge cutoff: with no recent information, they can't help with a feature released last week, or a policy that just changed. Second, private data: they can't see your procedures, support knowledge, or product specs, so they only give generic answers. Third, missing context: they ignore your security requirements and approval workflows, so their advice doesn't fit. Fourth, fabricated responses: confident-sounding but wrong, and that's a compliance and security risk. And fifth, scalability: every team rebuilds the same RAG setup, so the engineering effort is duplicated. At work, accuracy and reliability are non-negotiable, so these are real barriers.
Retrieve, augment, generate
Retrieval augmented generation, or RAG, connects an agent to your organization's knowledge sources in real time. Instead of relying only on static training data, the agent looks things up. It works in three coordinated steps. Retrieve: the system searches knowledge bases for content related to the question. Augment: it combines what it found with the user's question, so the model has factual context. And generate: the agent writes its answer using both its training and the retrieved information.
What RAG gives you
That gives you three big advantages. Real-time updates: agents stay current with your policies and procedures, without retraining. Source transparency: users see exactly which documents informed each answer, so they can trust it and check it. And factual grounding: answers are anchored in your actual content, so made-up answers become far less likely, and compliance is easier to keep. But building RAG yourself takes serious technical expertise. That's where Foundry IQ comes in: a ready-made knowledge platform that removes the complexity of custom RAG. That's next.
Facts from Microsoft's documentation: Retrieval augmented generation (RAG) and indexes in Microsoft Foundry; What is Foundry IQ? (CC BY 4.0), rewritten in Loop's own words and examples. Narration, animation, and quiz by Loop. Microsoft, Azure, and Microsoft Foundry are trademarks of Microsoft. Loop is independent and not affiliated with or endorsed by Microsoft.