The Problem
At my school, the lecture notes should be a lifeline, but students can’t make sense of them when they need clarity most—buried under dense terminology, scattered across endless slides, and lacking any immediate indication of whether they’re on the right track.
Seeing this, I envisioned and began developing NoteInsight, a seamless AI‑driven companion that transforms sprawling lecture materials into interactive notes, and guides students through targeted questions to illuminate their knowledge gaps.
Building NoteInsight
Building NoteInsight meant more than just writing code—it meant really getting to know how students learn. I sat down with classmates overwhelmed by long, complex lectures to hear where they struggled most. I also met with professors to pinpoint the key ideas students often miss. Watching study groups in action showed me how peers quiz each other—and where feedback was lacking. The main platform is now live, and we’re focused on user acceptance testing before a full campus rollout.
The Stack and Infrastructure
NoteInsight's architecture is designed to handle complex data analysis securely and efficiently. I chose Next.js for a dynamic, fast-loading frontend experience. The backend is powered by a robust Spring Boot application, utilizing Spring Security to guarantee enterprise-grade data protection and user authentication. For persistent storage, I integrated PostgreSQL, ensuring relational data integrity and scalable performance. At the heart of the platform's intelligence, I utilized the Gemini API to drive the sophisticated note analysis and interactive quizzing features.
