AI assistants are evolving from simple Q&A bots to intelligent, multimodal, multilingual, and agentic systems capable of reasoning, retrieving, and autonomously acting. In this talk, we’ll showcase how to build a voice-enabled, multilingual, multimodal RAG (Retrieval-Augmented Generation) assistant using Gradio, OpenAI’s Whisper, LangChain, LangGraph, and FAISS. Our assistant will not only process voice and text inputs in multiple languages but also intelligently retrieve information from structured and unstructured data. We’ll demonstrate this with a flight search use case—leveraging a flight database for retrieval and, when necessary, autonomously searching external sources using LangGraph. You will gain practical insights into building scalable, adaptive AI assistants that move beyond static chatbots to autonomous agents that interact dynamically with users and the web.