StudBuds
Built at Meta Global AI Developer Hackathon · Oct 26, 2026 · Remote

As a pair of new college transfer students adapting to an unfamiliar environment once again, we found through experience that the biggest obstacle to making friends was simply knowing where to find people who shared our ambitions and interests. That insight, combined with the numerous studies and stories we encountered about college loneliness, led us to build this project. We believe a solution made by college students, for college students, is the best way to address the problem, since we have the firsthand experience to understand our market. From personal experience with clubs and many empirical studies online, we learned that one of the best ways to build long-lasting friendships is to complete a shared activity, like studying. Using this idea, we settled on a study buddy discovery platform designed to eliminate the complexities and social barriers of meeting peers in college. Namely, it focuses on anonymity, a user-influenced interface, and incredible ease of navigation. Anonymity lets students connect over shared courses, goals, and study styles without the pressure of a first impression, and they decide when and how much to reveal. The user-influenceable interface allows customizable profiles and filters, so the platform evolves around what students truly need. Finally, our navigability-first design, supported by Meta AI, ensures that finding a study partner takes only a few steps, so the only obstacle left is the user’s own drive to take the next step.