Multimodal RAG: Ask Questions Across PDFs, Web Pages, and YouTube

Imagine asking a single question and getting an answer sourced from your documents, online articles, and even YouTube videos. In this session, you will learn how to build a multimodal RAG system that understands text, images, audio, and video and brings all that knowledge together into one searchable assistant.

What You Will Learn

• How multimodal RAG works and why it goes beyond text only systems
• How to extract and process information from PDFs, web pages, and YouTube videos
• How to combine text, visuals, and transcripts into a unified knowledge base
• How to ask natural questions and get grounded answers backed by multiple sources

Why This Session Matters
Most of the world’s information is locked inside mixed formats. A multimodal RAG system helps you cut through that complexity by combining retrieval and generation across different types of content. It gives you clearer answers, better context, and stronger accuracy because it sees more than just text.

What You Will Take Away

• A working multimodal RAG workflow that can pull insights from videos, documents, and online content
• A simple method to build a single assistant that understands multiple source types
• Templates for processing PDFs, scraping pages, and extracting YouTube transcripts
• A toolkit you can reuse for research, study, content creation, onboarding, or project planning

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