International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Docflow - AI-powered Document Summarizer + QNA

Author(s) Ms. Akanksha Bhausaheb Parbhane, Mr. Tanishk Nilesh Chitale, Ms. Mayuri Brarate, Ms. Ashwini Gaikwad, Prof. Renuka Kanade
Country India
Abstract In an era dominated by digital information, the challenge of efficiently processing and comprehending lengthy documents is significant. This paper addresses the time-consuming nature of extracting key insights from PDF documents and the barriers presented by foreign languages. The development of an intelligent web-based platform designed to automate document analysis is proposed. Leveraging a state-of-the-art Large Language Model (LLM), Google's Gemini, Docflow provides users with three core functionalities: AI-powered summarization, automated question and answer (Q&A) generation and on-demand multi-language translation. The system is built on a robust client-server architecture, with a React.js frontend for an interactive user experience and a Node.js backend to handle file processing and secure API communication. The primary goal of Docflow is to enhance productivity, accelerate learning and make information more accessible, thereby providing a powerful tool for students, researchers and professionals alike.
Keywords AI-Powered Summarization, Automated Q&A Generation, Large Language Models (LLM), Natural Language Processing (NLP), Google Gemini API Integration, React.js Frontend, Node.js & Express.js Backend, RESTful API Architecture, Automated Text Extraction (PDF-to-Text), Responsive Web Design, Multi-Language Translation, Intelligent Document Processing (IDP)
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 8, Issue 1, January-February 2026
Published On 2026-01-31
DOI https://doi.org/10.36948/ijfmr.2026.v08i01.66661
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E-ISSN 2582-2160
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