AI Internship Navigator

Inspiration

Students often struggle to understand which internship roles actually fit their current skills and what to learn next. Job descriptions feel overwhelming, and generic roadmaps don’t provide personalized direction. This project was inspired by the need for clear, honest, and human-style guidance.

What it does

AI Internship Navigator analyzes a student’s resume or skills, matches them with suitable internship roles, identifies skill gaps, and generates a personalized 30-day learning roadmap. It also provides AI mentor explanations that help students understand why a role fits and how to prepare effectively.

How we built it

The backend is built with FastAPI and handles resume parsing, skill matching, and API endpoints. The frontend uses Streamlit for an interactive user experience. Large language models via the Groq API generate mentor-style roadmaps and explanations, while deterministic logic ensures transparent and explainable skill matching.

Challenges we ran into

Designing AI outputs that felt helpful without being overly long or generic was challenging. We also faced deployment issues related to Python package imports and environment configuration, which required restructuring the backend for production-grade reliability.

Accomplishments that we’re proud of

Built a full-stack AI application from scratch

Deployed a live backend and frontend

Created mentor-style AI outputs instead of generic text

Designed a system that balances explainability with AI reasoning

What we learned

We learned how to combine deterministic logic with large language models to create human-centered AI experiences. We also gained hands-on experience with deployment, API design, and building AI systems that prioritize clarity and user control.