MatchKit

MatchKit transforms team formation into a data-informed discipline. We built the platform to help organizations understand how people collaborate best, using research-driven algorithms that balance skills, personality, and goals. What began as a startup concept evolved into an open-source tool called DreamTeam adopted across Cornell Tech’s graduate programs to form teams.

Overview

MatchKit helps leaders assemble teams with intention. Its matching algorithms draw from academic research on high-performing teams, turning qualitative goals into definable matchmaking criteria.

I co-founded the product with Cornell Tech classmates Angel Wong and Yu-Chien Chan. After delivering a functional MVP, we chose not to pursue funding and instead transitioned MatchKit into an educational tool—now called Dream Team—used for every student cohort at Cornell Tech.

The Pitch

I developed and refined MatchKit’s pitch over four months, sharing it with investors, executives, students, and researchers. The heart of the pitch included the problem statement, our unique solution, competitive analysis, market sizing, and business model. The evolving deck helped us clarify the story and validate interest across different audiences.

The Process

MatchKit’s product direction shifted frequently as we iterated. Each cycle started with scrappy sketches, moved into wireframes, and culminated in UI prototypes informed by user interviews, competitive analysis, and pricing research.

The Product

The final experience was a cloud-based web tool built on AWS, React.js, Bootstrap, zerorpc, and the Gurobi optimization engine. MatchKit generated optimized team assignments in minutes and delivered clear, shareable reports for program directors.

The Brand

Designing MatchKit allowed me to craft a full visual identity—from concept sketches to production-ready assets. The brand system was created in Adobe Illustrator and Photoshop, resulting in a cohesive set of logos, colors, and typographic guidelines.