Paper Title
TROVE.AI - A FULL-STACK CHATBOT FOR DYNAMIC DATA INTERACTION AND QUERY RESOLUTION

Abstract
This paper presents the Document Analyzer, a full-stack application designed for efficient document analysis through natural language queries. Users can upload PDFs and DOCX files, from which the system extracts text and processes it using advanced natural language processing techniques. Built with React for the frontend and FastAPI for the backend, it leverages LlamaIndex for document embeddings and MistralAI for query interpretation. Data is stored in a flexible MongoDB database, ensuring secure user authentication and personalized experiences by retrieving historical interactions. This solution streamlines the extraction of insights from complex documents, making it an essential tool for users seeking to navigate extensive information efficiently. Keywords - Document Analysis, Natural Language Processing, Full-Stack Development, User Authentication, Machine Learning.