Live deployment: https://hack-the-scholarship-frontend.vercel.app/
๐ 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: โWrite a compelling essay.โ But theyโre 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: โWhat 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.
๐ 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!
๐ How it works (Our Pipeline)
We designed a multi-stage AI pipeline using LLMs:
Scholarship Personality Analysis LLM extracts hidden values, patterns, and success traits.
Adaptive Weight Generation Each scholarship gets a custom weight profile
Student Profile Structuring The system organizes the student's background into a structured vector:
Targeted Essay Drafting Using scholarship weights ร student strengths, Claude AI generates a perfectly tailored essay.
Explainability Matrix Every sentence is tied to a scholarship value and a user strength.
Scholarship Scraper Integration Paste any URL โ scrape โ clean text โ run analysis โ generate essay.
๐ ๏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
๐ฎ 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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