ResearchMind AI An AI-Powered Multi-Domain Research Paper Analysis and Report Generation System

ResearchMind AI is an AI-powered system designed to simplify research paper analysis across multiple domains. It enables users to upload and analyze multiple research papers in PDF format. PyMuPDF is used to extract text, while Sentence Transformers generate semantic embeddings. ChromaDB stores and retrieves relevant information through semantic search. Retrieval-Augmented Generation (RAG) is integrated with an open-source Large Language Model (LLM) to provide context-based answers. The system supports automated literature survey generation, research gap identification, paper comparison, and intelligent question answering. It also generates structured research reports summarizing key findings and future research directions. The application uses React.js for the frontend and Flask with Python for the backend. ResearchMind AI aims to reduce manual effort, improve research organization, and make literature analysis more efficient.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-28
DOI
https://doi.org/10.5281/zenodo.23720775
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
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article

ResearchMind AI An AI-Powered Multi-Domain Research Paper Analysis and Report Generation System

Maajida A, Karthikha shree S M, Mr Sanjay Krishna B, Lekha P et al.
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Zenodo (CERN European Organization for Nuclear Research)
Topic Modeling
article

ResearchMind AI An AI-Powered Multi-Domain Research Paper Analysis and Report Generation System

Maajida A, Karthikha shree S M, Mr Sanjay Krishna B, Lekha P, Anandhi A
article en

Abstract

ResearchMind AI is an AI-powered system designed to simplify research paper analysis across multiple domains. It enables users to upload and analyze multiple research papers in PDF format. PyMuPDF is used to extract text, while Sentence Transformers generate semantic embeddings. ChromaDB stores and retrieves relevant information through semantic search. Retrieval-Augmented Generation (RAG) is integrated with an open-source Large Language Model (LLM) to provide context-based answers. The system supports automated literature survey generation, research gap identification, paper comparison, and intelligent question answering. It also generates structured research reports summarizing key findings and future research directions. The application uses React.js for the frontend and Flask with Python for the backend. ResearchMind AI aims to reduce manual effort, improve research organization, and make literature analysis more efficient.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 14%
Topic Modeling
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