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Fashionmate
LANCERProject Description
A fashion-tech startup specializing in AI-driven personal styling approached Oodles to build a mobile solution that could deliver personalized clothing recommendations in real time. The client aimed to offer an engaging fashion assistant with virtual try-on capabilities to help users make confident style choices and strengthen their brand in the online fashion space.
Scope Of Work
The client sought Oodles for an intelligent styling app capable of analyzing user features, detecting garment attributes, and delivering instant outfit suggestions. The project covered areas like AI-powered style matching, virtual try-on integration, real-time feedback, and a seamless cross-platform experience—targeting a smooth, intuitive, and highly personalized user journey.
Our Solution
To achieve the client’s vision, Fashionmate was developed as a cross-platform mobile application using React Native for fast, native-like performance on iOS and Android. A serverless architecture was implemented with Google Firebase and Cloud Functions to ensure scalability and real-time responsiveness. The application featured:
- AI-Powered Outfit Recommendations – Machine learning models processed facial features, clothing patterns, and personal style preferences to suggest suitable outfits instantly.
- Virtual Try-On Experience – Enabled users to visualize clothing items in real time using augmented image overlay.
- Smart Fashion Assistant “Jenny” – Offered interactive styling advice, outfit ratings, and trend suggestions.
- Real-Time Feedback Mechanism – Ensured instant analysis and recommendations based on changing user inputs.
- Personalized Wardrobe Insights – Helped users build style profiles and track favorite looks.