Inspiration Applying for internships can feel scattered and overwhelming, especially for students who are still figuring out how to present their skills. We wanted to build a tool that makes the process clearer, faster, and more personalized using AI.
What It Does: InternAI helps students manage their internship journey in one place. It parses resumes, extracts skills, matches users with relevant internships, highlights missing skills, generates tailored cover letters, improves resume bullet points, and tracks applications through different stages.
How We Built It: We built InternAI with a React and Vite frontend, a FastAPI backend, and Google Gemini for AI-powered resume parsing, job matching, cover letter generation, and resume optimization. The backend uses SQLAlchemy for data models, JWT for authentication, and supports SQLite or PostgreSQL for storage.
Challenges We Ran Into: One challenge was making the AI outputs reliable and structured, especially when parsing resumes or returning job match analysis. We also had to handle fallback behavior when the Gemini API was unavailable, misconfigured, or returned unexpected responses.
Accomplishments That We're Proud Of: We are proud of building a complete internship-focused platform instead of just a single AI feature. InternAI combines resume intelligence, job discovery, match scoring, cover letters, and application tracking into one usable workflow.
What We Learned: We learned how to integrate AI into a real full-stack application, design fallback systems for reliability, structure FastAPI services cleanly, and build a student-focused product that solves a practical career problem.
What's Next For InternAI: Next, we want to improve job scraping quality, add more detailed career recommendations, support multiple resume versions, include interview preparation tools, and make the AI match scoring more transparent and personalized.
Built With
- antigravity
- fastapi
- kanban
- python


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