Beyond Text: Building Multimodal RAG Systems

Retrieval-Augmented Generation (RAG) doesn’t stop at text. The future is **multimodal RAG**, where models can reason over **documents, images, charts, and more**. In this hands-on session, we’ll explore: * What **Multimodal RAG** is and why it matters * How to combine text + images in a retrieval pipeline * Using **vision-language embeddings** for storing & searching multimodal data * Running live demos with small VLMs (Vision-Language Models) and vector databases * Practical use cases: compliance checks, document Q&A, product search, and research workflows 🔹 **Format:** Interactive demo + live coding walkthrough 🔹 **Who’s it for:** AI engineers, researchers, and product teams building advanced AI systems 🔹 **Takeaway:** A working notebook + examples of multimodal retrieval powering next-gen AI apps