WisPaper serves as an AI-powered research assistant designed to facilitate the quick and intelligent search, filtering, and synthesis of academic literature. Its innovative “Scholar Search” function operates like a virtual agent, allowing users to pose inquiries about specific topics while WisPaper delves into research databases to uncover the most pertinent papers, abstracts, metrics, and insights. Instead of merely generating lists, WisPaper enhances the user experience by enabling the screening and filtering of results based on relevance, date, citations, and impact, all while providing valuable summaries and contextual information to assist users in focusing on what is truly important. Additionally, for those who may not have precise terminology, WisPaper offers concept exploration capabilities by suggesting related keywords or starting from broader ideas to refine them further. The platform is designed with a user-friendly interface that streamlines the literature review process, significantly minimizing the time spent on manual searches, extensive reading of abstracts, and the need for cross-referencing multiple sources, ultimately empowering researchers to work more efficiently in their academic endeavors. Moreover, this efficiency is essential in today’s fast-paced research environment, where time and accuracy are critical.