Uni Hunter

Advisor Dashboard
Student Dashboard
Profile Scan
Roadmap Builder
Event Browsing
University Matching

Inspiration

The inspiration behind Uni Hunter comes from the growing complexity of university applications and the overwhelming workload faced by admissions consultants managing multiple students. We observed that while each student requires highly personalized guidance, consultants often struggle to scale their support effectively. This gap motivated us to build a platform that leverages AI to streamline mentoring, enhance decision-making, and improve student outcomes.

What it does

Uni Hunter is an AI-powered platform designed to assist admissions consultants in managing and mentoring students through the university application process. It analyzes student profiles, recommends best-fit universities, and generates personalized roadmaps that include timelines, tasks, and strategic activities. The platform also tracks student progress, evaluates profile strength, and suggests relevant extracurricular opportunities, helping consultants guide each student toward stronger applications and higher chances of acceptance.

How we built it

We built Uni Hunter using a modern full-stack architecture. The frontend was developed with React and TypeScript to create a responsive and intuitive user interface. The backend was powered by Node.js and Express.js, providing scalable APIs and business logic. PostgreSQL was used as the primary database to manage structured student and application data. Docker was utilized to containerize the application for consistent development and deployment. Additionally, we integrated OpenAI to enable intelligent recommendations, profile analysis, and roadmap generation.

Challenges we ran into

One of the main challenges was designing a system that balances automation with human control, ensuring that AI-generated recommendations remain customizable for consultants. Structuring and analyzing diverse student profile data was also complex, especially when trying to generate meaningful insights and competitive scores. Another challenge was building a flexible roadmap system that adapts dynamically as students update their goals and progress.

Accomplishments that we're proud of

We are proud of successfully creating a platform that not only automates key aspects of admissions consulting but also enhances the quality of mentorship. The integration of AI to generate personalized roadmaps and profile insights is a major achievement. Additionally, the ability to visualize student progress and manage multiple mentees efficiently demonstrates the platform's real-world applicability and scalability.

What we learned

Through this project, we learned how to design AI-assisted systems that complement human expertise rather than replace it. We gained experience in structuring complex user workflows, handling relational data effectively, and integrating machine learning capabilities into a full-stack application. We also learned the importance of user-centric design, especially when building tools for professionals like consultants.

What's next for Uni Hunter

Moving forward, we plan to enhance the AI capabilities by incorporating more real-world data from successful applicants and improving recommendation accuracy. We aim to introduce collaboration features for student teams, expand scholarship and event databases, and refine analytics dashboards for deeper insights. Ultimately, we want to scale Uni Hunter into a comprehensive platform used by consulting institutions globally.