Classifi.me is an app designed to predict a user's Myers-Briggs (MBTI) personality type and assess their happiest photo and overall sentiment throughout the year by analyzing their photos and videos on social media. Developed by University of Central Florida students Isabella Moreira, Tyler Leonhardt, and Eric Smithson, the app uses a combination of APIs including Instagram, Clarifai, and uClassify to transform visual content into data that reveals insights about one's online persona versus real personality traits. The developers were inspired by the curiosity of whether social media accurately reflects users' personalities and built the app with a frontend of HTML/CSS/JS and a backend using Node.js with Express. Despite the challenges of handling vast amounts of raw data, the team found the process rewarding, especially using Clarifai's reliable tagging API, which greatly facilitated the data processing. The app is described as "scary accurate" and has successfully matched its predictions with results from traditional Myers-Briggs tests, even humorously determining the personality type of an office dog.