AI-Powered PDF Question and Answer System for Supporting Academic Research

Dr. K. Satyam1, Shaik Jaheer Vakhid2
1Associate Professor, Department of MCA, Annamacharya Institute of Technology & Sciences, Tirupati, AndhraPradesh, India.
2 Post Graduate, Department of MCA, Annamacharya Institute of Technology & Sciences, Tirupati, AndhraPradesh, India.

Abstract:The time and effort needed for researchers to extract pertinent information from scientific materials has increased dramatically due to the fast development of academic publications. Conventional manual reading techniques are frequently ineffective, particularly when handling lengthy technical reports and research papers. This study offers an AI-powered PDF Question Answering system intended to improve academic research procedures in order to address this issue. Users can submit a research paper URL and ask natural language questions about its content using the suggested web-based application. In order to produce precise and context-aware responses, the system gets the document, examines the textual data, and applies the Gemini 2.0 Flash big language model. The platform, which was developed with Python and Flask, provides an interactive interface that speeds up information retrieval and makes research paper analysis easier. The system successfully gathers insightful information from scholarly publications and provides prompt, organised responses, as demonstrated by experimental use. This approach enhances research productivity and makes better academic support tools possible by incorporating artificial intelligence into document understanding.Keywords: Artificial Intelligence, Natural Language Processing, Document Question Answering, Academic Research Automation,Large Language Models, Gemini API, Intelligent Document Analysis, Research Workflow Optimization