Aerena

🚀 Inspiration Students waste hours scrolling through internship portals, applying blindly, and getting zero responses. The core problem isn’t lack of opportunities — it’s poor matching and visibility. We wanted to fix this by building a system that actually understands a student’s profile instead of just matching keywords. 💡 What it does Aerena is an AI-powered platform that recommends internships based on a student’s skills, projects, and interests. Upload your resume Get a personalized match score for each internship Receive recommendations tailored to your profile Avoid irrelevant applications Instead of applying everywhere, users can focus on high-probability opportunities. ⚙️ How we built it Frontend: React + TypeScript + Vite Backend: Node.js / Express (assumed — adjust if needed) AI Matching: NLP-based similarity (TF-IDF / embeddings / cosine similarity) Database: MongoDB / Firebase Resume Parsing: Extract skills, education, and experience We designed a scoring system that compares: Resume content Job description Skill overlap ⚔️ Challenges we ran into Resume parsing is messy (PDF formats are inconsistent) Keyword matching alone gives poor results Building a meaningful “match score” is harder than it looks Lack of real dataset for internships Most platforms fake intelligence — we had to actually make it work. 🏆 Accomplishments that we're proud of Built a working AI-based recommendation system Created a clean and fast UI using Vite Designed a scalable matching logic Reduced irrelevant recommendations significantly 📚 What we learned AI is useless without good data UX matters as much as algorithm accuracy Real-world problems are messy, not textbook-clean Simplicity beats overengineering 🔮 What's next for Aerena Real-time internship scraping APIs Recruiter dashboard Skill gap analysis (what you need to improve) Personalized career roadmap Integration with LinkedIn / GitHub

Built With

• icnp
• mern
• ml