Goal
PGAdmit wanted future students to stop comparing dozens of universities by hand and guessing their chances, and to reach a shortlist they could trust. For PGAdmit itself, that meant a more clearly differentiated product in a crowded EdTech market.
What we built
We built an AI recommendation engine that takes a student's academic history, interests and goals, compares them with data on universities and programmes, and returns ranked recommendations instead of a generic search.
- Recommendations by profile: every student sees the universities and programmes that fit their profile.
- Data model and ranking logic: institution and student data is structured so recommendations stay precise as the catalogue grows.
- Room to grow: new institutions, programmes and AI features can be added without a rebuild.
Result
After launch, use of PGAdmit's search tool rose 40% and signups rose 25%, according to figures from the client. Students get a shortlist instead of a pile of open browser tabs, and PGAdmit gets a stronger product story.
