Studium

Inspiration

We noticed that very few classmates were rewatching lecture recordings, even when they struggled with the material. The barrier wasn't a lack of motivation—it was time. Sitting through hours of lecture footage to review key concepts felt overwhelming. We asked ourselves: what if we could transform dense lecture transcripts into engaging, digestible study videos that students would actually want to watch? That's how Studium was born.

What it does

Studium converts lecture transcript PDFs into personalized study videos and emails them directly to students. Users simply upload their lecture transcript PDF and enter their email address through our web interface. Within minutes, they receive a custom-generated video that explains the material in a clear, concise way—turning hours of lecture content into focused study resources.

How we built it

We built Studium with a full-stack approach that seamlessly connects multiple technologies:

Frontend: Framer for a modern, intuitive UI where users upload transcripts and enter their email Backend: Flask API to handle file uploads, validate data, and communicate with our workflow engine Workflow Automation: n8n to orchestrate the entire pipeline—from receiving the PDF to coordinating AI services AI Processing: OpenAI to analyze transcripts and generate engaging video scripts Video Generation: OpenNote API to transform scripts into professional study videos Delivery: Automated email system to send completed videos directly to students

Challenges we ran into

Our biggest challenge was fully automating the AI pipeline with n8n. As first-time users of the platform, we had to learn how to properly configure webhooks, manage data flow between different APIs, and handle error cases—all while racing against the hackathon clock. Debugging the communication between Flask, n8n, OpenAI, and OpenNote required patience and creative problem-solving, but we eventually got all the pieces working together seamlessly.

Accomplishments that we're proud of

We're incredibly proud of building a complete, functional AI pipeline from scratch in just one weekend. Watching a PDF transcript transform into an actual study video—automatically—felt like magic. We successfully integrated four different technologies (Framer, Flask, n8n, and multiple AI APIs) into a cohesive product that solves a real problem students face every day.

What we learned

This project taught us invaluable lessons about building AI-powered applications and connecting disparate systems. We learned how to design and implement complex workflows with n8n, how to properly structure API communications between services, and how to think about user experience when dealing with asynchronous processes. Most importantly, we learned that ambitious ideas are achievable when you break them down into manageable components and tackle them systematically.

What's next for Studium

Our vision is to integrate Studium directly into the Yuja platform (our university's lecture recording system). This would allow students to generate study materials with a single click—right from the lecture page they're already viewing. We also plan to add features like customizable video length, topic-specific focus areas, and support for multiple study formats (flashcards, quiz questions, summary notes) to give students even more ways to learn effectively.

Built With

• flask
• framer
• n8n
• opennote