07-evidence-bank
06-assistant-welcome
09-scholarship-detail
08-assistant-response
04-applications
05-documents
03-my-goal
01-dashboard
02-discover

Inspiration

Students often struggle to manage multiple scholarships, eligibility criteria, deadlines, and documents. We built SCHOLARAi to simplify scholarship management and help students decide what to apply for and what to do next.

What it does

SCHOLARAi is an AI-powered scholarship discovery and application assistant that helps students:

Discover relevant scholarships
Understand eligibility requirements
Manage application documents and deadlines
Identify blockers across applications
Prioritize tasks based on funding needs
Receive AI-assisted application guidance

How we built it

We designed SCHOLARAi using a modern web application architecture with a student dashboard, scholarship discovery, goal planning, application management, and AI-assisted recommendations. The planned technology stack includes Python, TypeScript, Next.js, FastAPI, LLMs, RAG, and PostgreSQL.

Challenges we ran into

Organizing scholarship information from different sources
Connecting eligibility requirements and shared documents across applications
Prioritizing tasks based on deadlines, funding needs, and application progress
Ensuring AI recommendations remain transparent and trustworthy

Accomplishments that we're proud of

A funding-focused approach to scholarship discovery
Cross-application dependency and blocker identification
Personalized next-best-action planning
A student-centered design focused on simplicity and accessibility

What we learned

We explored how AI agents, structured data, and retrieval-based knowledge can support scholarship planning. We also learned the importance of reliable sources, responsible AI, and keeping students in control of their applications.