Business Situation & Requirements
The client wanted to offer Gen Z users a more engaging and easier way to find outfits that matched their style or recreate looks from social media. Existing visual search and styling features had room for improvement to make product discovery smoother and boost engagement.
To solve this, the client wanted an AI-enabled Shopping Assistant with visual search, smart outfit recommendations, and virtual try-on. The goal was to simplify product discovery and create a seamless shopping experience, guiding users smoothly from inspiration to purchase.
Key requirements were:
Define a scalable AI-first architecture and choose the right technology stack to support real-time personalisation, visual processing, and smooth integrations.
Design an intuitive interface that lets users upload wardrobe details manually or via photos with ease.
Build machine learning models to analyse preferences, browsing behaviour, and purchase history for relevant outfit recommendations.
Implement visual search so users can upload images or select inspiration to quickly find matching products.
Use augmented reality and 3D imaging to let users virtually try outfits and make confident purchases.
Develop a smart styling engine that combines clothing, footwear, and accessories, enhancing overall product discovery.
