Undermind is an AI-powered research assistant designed to transform how researchers conduct literature reviews and discovery. The platform reads thousands of papers, carefully evaluates their relevance to specific research questions, and adapts its search strategy recursively while traversing the full citation graph. Unlike traditional search engines, Undermind mirrors the structured search process of a human expert by using the latest language models for in-depth reasoning at key steps within the research process.

The platform delivers unprecedented breadth and depth in scientific literature exploration. It analyzes both abstracts and full texts where available, providing researchers with comprehensive insights through features like custom table generation, inline citation verification, relevance sorting and filtering, and automated alerts for newly published relevant papers. Undermind's unique algorithms have been benchmarked to deliver 10x better results than Google Scholar, with the ability to understand complex research topics and find highly specific papers that match nuanced requirements.

Researchers use Undermind to assess novelty of ideas, scope complex topics before investing resources, uncover cross-disciplinary insights, identify gaps in the literature, and solve research bottlenecks by finding relevant methods, datasets, and prior solutions. The platform has proven valuable across diverse fields, from chemistry to clinical trial data, condensing days or weeks of work into minutes. Research groups at institutions including MIT, Harvard, Caltech, Princeton, Berkeley, and Cambridge trust Undermind for their literature search needs.