The Problem
Movie lovers struggle to track and save the endless stream of film recommendation videos they see on TikTok, making finding and remembering these recommended movies tedious and disorganized.
To address this, I developed FilmPad, a free platform that identifies movies from TikTok recommendation videos and automatically populates them into a manageable watchlist.
Building FilmPad
Building FilmPad involved creating an automated pipeline to parse TikTok recommendation videos, extract the featured titles, and deliver tailored recommendations. I worked to design a sleek, user-friendly interface that tracks trending movies on TikTok and lets users easily organize their lists. The result is a free tool that simplifies movie discovery and curation, which today helps over 1200+ users keep track of their next favorite films.
The Stack and Infrastructure
To ensure FilmPad operates with high performance and reliability, I engineered the tech stack for scalability and rapid data processing. The frontend is built with Next.js, delivering a highly responsive, server-side rendered user interface. On the backend, I implemented a robust Node.js architecture paired with MongoDB for flexible, scalable data storage. The core of the platform's automation is powered by a custom pipeline leveraging the Gemini API for intelligent content parsing, integrated seamlessly with the TMDB API to fetch accurate, real-time movie data.
