Swiped-In transforms job searching and hiring into an interactive, AI-driven experience. Inspired by swipe-based apps, we built a seamless matching platform where job seekers and recruiters connect effortlessly. This project was built for HackNYU 2025 within an intense 1 day coding sprint. 🚀
The hiring process is often slow, impersonal, and frustrating. We set out to create a fast, intuitive, and engaging way to match candidates with jobs—just like dating apps revolutionized relationships, we’re reimagining hiring.
- Job Seekers: Upload resumes, add key details, and swipe through job listings.
- Recruiters: Swipe through potential candidates, filtering the best fits.
- Matching System: A match occurs when both parties swipe right.
- AI-Powered Screening: The recruiter's AI agent conducts short, dynamic screening interviews.
- Additional Features:
- Chat management for seamless communication.
- Application tracking to monitor job progress.
- Personalized job and candidate recommendations.
- Frontend: React Native for a smooth, cross-platform mobile experience.
- Backend: Node.js with Express to handle API requests.
- Database: MongoDB Atlas for scalable, real-time data management.
- AI Integration: Google Gemini API for recruiter avatars & AI-powered screening interviews.
- Authentication: Secure login for job seekers and recruiters.
- Hosting: Cloud deployment for scalability.
- AI Screening Integration: Fine-tuning AI interview questions for different job roles.
- Scalability: Structuring MongoDB to handle job postings, resumes, matches, AI responses, and chat interactions efficiently.
- Time Constraints: Building a fully functional job-matching platform in under 18 hours.
- Built a working prototype in just 18 hours! 🚀
- Successfully integrated AI-powered recruiter interviews.
- Created a smooth, intuitive swipe-based job-matching experience.
- Used MongoDB Atlas for fast, scalable data handling.
- Secured the domain swiped.in for future expansion.
- Power of AI in Hiring: How AI can streamline recruitment and improve hiring efficiency.
- MongoDB Atlas for Scalability: Leveraging cloud databases for handling real-time data.
- User Experience Matters: Designing an intuitive job-matching system that feels natural.
- Team Collaboration Under Pressure: Building a complex project in a tight timeframe.
- Enhancing AI Screening: More sophisticated AI recruiter agents.
- Smarter Matching Algorithms: More personalized job and candidate recommendations.
- Improved Application Tracking: Data-driven career insights.
- Monetization & Scaling: Premium job postings, recruiter subscriptions.
- Launch on App Stores: Bringing Swiped-In to a global audience.
- Node.js & npm installed
- MongoDB Atlas account
- Google Gemini API key
# Clone the repository
git clone https://github.com/yourusername/swiped-in.git
cd swiped-in
# Install dependencies
npm install
# Set up environment variables (.env file)
MONGO_URI=your_mongodb_uri
GEMINI_API_KEY=your_gemini_api_key
# Start the backend
npm run server
# Start the frontend
cd client
npm install
npm start- Frontend: Next.js
- Backend: Node.js, Express
- Database: MongoDB Atlas
- AI: Google Gemini API
- Hosting: Cloud-based deployment
HackNYU 2025 Project | Made with ❤️ by Team Swiped-In 🚀