Research Gap AI

ResearchGap is an intelligent AI-based research assistant designed to simplify one of the most challenging parts of academic research: identifying meaningful research gaps from a large collection of scientific papers. Instead of spending days or weeks reading dozens of papers, comparing methodologies, and manually identifying unexplored areas, the system automates this process using Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and semantic search. The application allows users to upload multiple research papers in PDF format or specify a research topic. It then extracts and processes the contents of these papers, builds a searchable knowledge base, and enables users to ask questions about the literature. Rather than simply summarizing papers, the system analyzes similarities and differences across multiple studies, identifies limitations and unresolved problems, and generates potential future research directions supported by evidence from the uploaded literature. Why Was This Project Built? One of the biggest challenges for students and researchers is conducting a literature review. A researcher often has to read 50–200 papers before deciding on a research topic. This process is extremely time-consuming because they must: Read each paper carefully. Understand different methodologies. Compare experimental results. Identify limitations. Discover unexplored research opportunities. Write comprehensive literature reviews. Existing AI tools can summarize individual papers, but they usually cannot compare multiple papers together to identify genuine research gaps. ResearchGap addresses this limitation by providing an AI system capable of understanding relationships between multiple research papers and suggesting promising future research directions.