With the increasing volume of digital information, people work with various document formats such as PDFs, scanned documents, text files , handwritten notes , images . Manually extracting useful information from these documents can be time-consuming and difficult. The AI Multimodal Document Processing System addresses this problem by providing an intelligent and automated approach to document processing and understanding.

It uses Optical Character Recognition (OCR), document parsing, and Artificial Intelligence to extract meaningful content from different document formats. Google Gemini AI is used to generate summaries, identify key entities such as names, organization , names, dates, and monetary values, and also create quizzes from the document content. It also provides a chat feature that allows users to ask questions and receive answers based on uploaded documents.

The system is developed using Next.js, React, TypeScript, Node.js, Express.js, MongoDB Atlas, Tesseract.js, and Google Gemini AI. MongoDB and GridFS are used to securely manage uploaded documents and processed information. Users can also export quizzes, chat conversations, and extracted information in various formats.

This particular system integrates document processing, summarization, information extraction, learning, and document-based interaction into a single platform, making it useful for students, professionals, researchers and other users handling large amounts of document-based information.