Our project seeks to develop a sophisticated multilingual AI-powered Research Assistant that optimizes the management and utilization of research papers. Utilizing the LLAMA3 LLM, this platform integrates advanced functionalities, including automated clustering and summarization of research papers, and interactive Q&A capabilities. The system allows users to upload their own documents or access papers from the ArXiv database, supporting interactions through both text and audio inputs/outputs. The incorporation of a Retrieval-Augmented Generation (RAG) framework facilitates seamless and intuitive engagement with research content. This all-encompassing solution significantly enhances research efficiency, broadens access to critical information, and addresses language barriers, thereby supporting the effective integration and application of new knowledge on a global scale.