The Goal
PGadmit wanted prospective students to stop drowning in scattered research, comparing dozens of institutions by hand and guessing at their odds, and get to a shortlist they could actually trust. For PGadmit as a business, that meant a stronger, clearly differentiated product in a crowded EdTech market.
What We Built
We built an AI recommendation engine that reads a student’s academic history, interests and goals, then matches them against university and program data to produce ranked, relevant suggestions instead of a generic search box.
- AI recommendation engine: connects student profiles directly to the most relevant universities and programs.
- Data modeling and ranking logic: structures institution and student data so recommendations stay accurate as the catalog grows.
- Scalable architecture: built to add new institutions, programs and AI features without a rebuild.
The Result
After launch, PGadmit’s own search tool saw a 40% increase in usage and a 25% increase in signups, numbers reported directly by the client. Students get a shortlist instead of a spreadsheet of open tabs, and PGadmit has a clearer product story in a crowded EdTech market.
