🚀 Resume Benchmark AI

An AI-powered resume analysis tool that helps Software Engineering students understand why their resumes get rejected and how to improve them.

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🔍 Problem

Most students applying for SWE internships face the same issue: • Apply to 100+ roles • Get no responses • No feedback on what’s wrong

Resumes feel like they’re going into a black hole.

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💡 Solution

Resume Benchmark AI analyzes resumes and provides: • 📊 Resume Score (out of 100) • ⚠️ Key gaps in the resume • ✅ Strengths detected • 📈 Comparison with accepted resumes • 🔒 Paywalled detailed insights

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🧠 How It Works

The system extracts signals from resumes such as: • Internship experience • Open-source contributions (OSS) • GitHub presence • Tech stack depth • Project deployment • Measurable impact (metrics)

These signals are compared against patterns found in accepted SWE resumes.

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✨ Features • 📄 Upload PDF resumes • ⚡ Instant analysis • 🧩 Dynamic scoring (not generic) • 🔍 Personalized feedback • 🔐 Paywall for detailed insights • 📊 Accepted resume benchmarking

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🛠 Tech Stack • Frontend: Next.js 14 • Backend: Next.js API Routes • Parsing: pdf-parse • Deployment: Vercel • Language: TypeScript

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📂 Project Structure

src/
├── app/
│   ├── analyze/       # Upload page
│   ├── report/        # Results page
│   └── api/analyze/   # Resume analysis logic
├── lib/               # (future dataset logic)

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⚙️ Installation

Clone the repo:

git clone https://github.com/your-username/resume-benchmark-ai.git
cd resume-benchmark-ai

Install dependencies:

npm install

Run locally:

npm run dev

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🚀 Deployment

This project is optimized for deployment on Vercel.

Make sure: • Node runtime is enabled • PDF size < 2MB • Environment is correctly configured

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📊 Future Improvements • 🤖 AI-based bullet point rewriting • 📚 Accepted resume dataset (1000+ resumes) • 🧠 Machine learning scoring model • 💳 Razorpay payment integration • 🏆 Resume leaderboard

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💰 Monetization Model • Free: Resume score + basic feedback • Paid (₹199): • Full gap analysis • Improvement suggestions • Advanced insights

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🙌 Contributing

Feel free to open issues or contribute improvements.

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📣 Feedback

This is an early-stage project. If you try it, your feedback is highly valuable.

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⭐ If you found this useful

Give it a star on GitHub — it helps a lot!

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👨‍💻 Author

Built by Saad Ahmed 3rd Year CSE (AI & ML)

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⚡ Vision

To build a data-driven resume intelligence platform that helps students land better opportunities. This is a Next.js project bootstrapped with create-next-app.

Getting Started

First, run the development server:

npm run dev
# or
yarn dev
# or
pnpm dev
# or
bun dev

Open http://localhost:3000 with your browser to see the result.

You can start editing the page by modifying app/page.tsx. The page auto-updates as you edit the file.

This project uses next/font to automatically optimize and load Geist, a new font family for Vercel.

Learn More

To learn more about Next.js, take a look at the following resources:

• Next.js Documentation - learn about Next.js features and API.
• Learn Next.js - an interactive Next.js tutorial.

You can check out the Next.js GitHub repository - your feedback and contributions are welcome!

Deploy on Vercel

The easiest way to deploy your Next.js app is to use the Vercel Platform from the creators of Next.js.

Check out our Next.js deployment documentation for more details.