Cross-Platform App Migration to Flutter for Personalized Fashion Recommendation System

The client requires transitioning from native Android and iOS applications to a unified cross-platform solution to improve maintainability, user experience, and performance. The current native apps pose challenges related to code duplication, slow updates, and limited ability to rapidly adapt to design and feature changes, especially under tight deadlines for investor commitments and product launches.

A mid to large-sized fashion retail technology company seeking to enhance user experience with a unified, high-performance mobile app for personalized outfit recommendations and shopping suggestions.

• Rebuild the existing native mobile application using a cross-platform framework to streamline development and maintenance.
• Deliver an MVP within a specified tight deadline to support investor funding and market entry.
• Enhance user experience through optimized performance, modern UI design, and engaging animations.
• Achieve a high user adoption rate, aiming for over 1 million downloads post-launch.
• Facilitate iterative feature releases to incorporate user feedback and continuously improve functionality.

• User authentication and profile management
• Integration with user's existing wardrobe data and photo uploads
• AI-powered outfit and shopping recommendations based on occasion and mood
• Ability to create, view, and edit outfit ensembles using personal closet images or stock photos
• Modern, engaging UI with smooth animations and responsive design
• Iterative release of new features based on user feedback
• Analytics dashboard for tracking user engagement and app performance

• Backend services for user data, preferences, and AI recommendation algorithms
• Photo management and storage services
• Analytics and user engagement tracking tools

• Ensure app performance is on par with native applications, with smooth animations and quick load times
• Scalability to support a growing user base, targeting over 1 million downloads in initial phases
• High security standards for user data privacy and secure transactions
• Availability of frequent updates and feature rollouts in Agile iterations
• Maintainability and ease of updates through shared codebase

Anticipated to significantly improve user engagement and satisfaction through a unified, high-performance app. The project aims to achieve over 1 million downloads within the first year, enhance user retention with personalized AI suggestions, and provide a scalable platform that supports rapid feature deployment to adapt to evolving market needs.