AI-Research Explorer using RAG and LLM

AI-Research Explorer is an intelligent research assistant designed to help users find, understand, and summarize scientific information quickly. The system uses Retrieval-Augmented Generation (RAG) to fetch relevant research papers or web documents in real time. A powerful Large Language Model (LLM) then processes the retrieved content and generates accurate, context-aware answers. Users can ask research questions in natural language and receive well-structured responses with sources. The tool improves decision-making for students, researchers, and professionals by providing verified information instead of hallucinated responses. It supports features like keyword search, summarized insights, and citation extraction. The system continuously learns and updates its knowledge base to keep up with the latest studies. This project demonstrates advanced AI integration, enhancing research productivity and knowledge discovery efficiently.