What is Multimodal RAG?
TL;DR
A next-generation RAG technology that retrieves and uses not just text but also images, tables, and diagrams to generate answers.
Multimodal RAG: Definition & Explanation
Multimodal RAG extends traditional text-based RAG (Retrieval-Augmented Generation) to search and retrieve diverse data formats — images, tables, graphs, diagrams, PDFs, and audio — for use in LLM answer generation. For example, it can search for relevant diagrams from technical manuals or slides from meeting decks, and feed them alongside text to multimodal LLMs (GPT-4o, Gemini, Claude) for more accurate and context-rich answers. Since enterprise documents frequently contain charts, tables, and PDFs, multimodal support is essential for practical RAG systems. Frameworks like LangChain and Dify support building multimodal RAG applications.