Live deployment: https://hack-the-scholarship-frontend.vercel.app/

๐ŸŒŸ Inspiration

Every year, billions of dollars in scholarships go unclaimed - not because students are unqualified, but because the application process is confusing, exhausting, and overwhelmingly generic.

Students are told: โ€œWrite a compelling essay.โ€ But theyโ€™re never told what makes an essay compelling for a specific scholarship.

A merit scholarship wants academic rigor. A service scholarship wants community impact. A leadership scholarship wants initiative.

Yet students write one essay and send it to everything.

We asked ourselves: โ€œWhat if AI could read a scholarship the way a human judge does? What if it could uncover what the scholarship truly values - and then help students tell the right story for the right audience?โ€

That insight became the foundation of Scholarly - the AI-powered system that helps students not just find scholarships, but actually win them.

๐Ÿš€ What we built

Scholarly is a fully deployed, end-to-end AI scholarship application platform that helps students:

  • Create a reusable, structured personal profile
  • Analyze any scholarship automatically
  • Generate tailored application essays based on scholarship-specific priorities
  • Understand why the Claude AI wrote each section (explainability matrix)
  • Add new scholarships simply by pasting a URL - our scraper handles the rest

We also built a chrome extension that autofills the applications for you too!

๐Ÿ” How it works (Our Pipeline)

We designed a multi-stage AI pipeline using LLMs:

  1. Scholarship Personality Analysis LLM extracts hidden values, patterns, and success traits.

  2. Adaptive Weight Generation Each scholarship gets a custom weight profile

  3. Student Profile Structuring The system organizes the student's background into a structured vector:

  4. Targeted Essay Drafting Using scholarship weights ร— student strengths, Claude AI generates a perfectly tailored essay.

  5. Explainability Matrix Every sentence is tied to a scholarship value and a user strength.

  6. Scholarship Scraper Integration Paste any URL โ†’ scrape โ†’ clean text โ†’ run analysis โ†’ generate essay.

    ๐Ÿ› ๏ธ How we built it

    We built ScholarAI as a full-stack platform:

  • Next.js + TypeScript for the front-end
  • TailwindCSS + shadcn/ui for a modern, clean UI
  • PostgreSQL + Prisma for persistent user profiles & applications
  • Node API routes for LLM orchestration
  • Claude 3.5 Sonnet for the multi-stage AI reasoning pipeline
  • Recharts for adaptive weighting visualizations
  • Custom Web Scraper for extracting scholarship text
  • Vercel Deployment for production-level hosting

๐Ÿ”ฎ What's next for Scholarly

  • LLMs are incredible at pattern recognition, but only when given structure.
  • Explainability matters. Students trust AI more when they understand why it writes what it writes.
  • Modularity beats mega-prompts when building reliable AI systems.
  • UX is everything - especially for stressed students applying to scholarships.

Built With

  • claude
  • nextjs
  • tailwind
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