Layered

Layered transforms the daily outfit dilemma into an intelligent, personalized styling experience. Built with cutting-edge SwiftUI and Core ML, this AI-powered wardrobe manager learns your style preferences, considers weather conditions, and suggests coordinated outfits from your existing wardrobe. The app features advanced ARKit integration for virtual try-ons, smart categorization of clothing items, and seasonal outfit planning.

I architected the entire iOS and watchOS experience, implementing sophisticated machine learning models that analyze color coordination, style compatibility, and personal preferences. The app includes intelligent photo recognition for cataloging wardrobe items, weather-aware outfit suggestions, and social sharing capabilities. The watchOS companion provides quick outfit approvals and weather-adjusted recommendations right from your wrist.

This project pushed the boundaries of AI integration in consumer apps, combining computer vision, machine learning, and augmented reality to solve a real-world problem. The result is an app that doesn't just organize your clothes—it becomes your personal stylist, learning and evolving with your taste while helping you make confident style choices every day.