Outfit Darling was inspired by Cher’s iconic virtual closet in Clueless, along with 90s fashion magazines, scrapbook aesthetics, and classic dress-up games. We wanted to bring that nostalgic experience into a modern app that helps people make the most of the clothes they already own. We built a digital wardrobe where users can create outfits, save their favorite looks, plan what to wear throughout the week, and get personalized styling suggestions from an AI stylist.

We built Outfit Darling using React, JavaScript, and CSS for the frontend, with Node.js and Express for the backend. We integrated Google Gemini for AI-powered styling advice, remove.bg for clothing photo background removal, and Open-Meteo for weather forecasts that help inform outfit recommendations. We also used IndexedDB to store users’ closets, saved outfits, and weekly plans directly on their devices, and made the app installable as a progressive web app.

Throughout the project, we learned how to integrate multiple APIs, connect frontend and backend services, and combine AI with practical, user-focused features. One of our biggest challenges was making the different features work together seamlessly, especially ensuring the AI stylist recommends only clothing items users actually own and that weather conditions influence outfit suggestions appropriately. We also had to consider what happens when an API is unavailable, allowing users to continue using the core app even when certain features cannot connect. Ultimately, Outfit Darling taught us how to turn a creative idea into a functional, full-stack application while balancing technical functionality with an intentional visual design.