CLOQR
ExpertsCloud developed a mobile application that integrates AI-driven styling, cloud storage, and intelligent recommendation systems. During onboarding, users provide body data and fashion preferences. They can then upload their wardrobe items into a digital closet. All user data is securely stored in Amazon RDS (PostgreSQL), while wardrobe images are stored in Amazon S3. For outfit recommendations, the system uses Amazon Nova Pro to analyze user preferences, wardrobe inventory, and contextual inputs such as weather and occasion. The recommended outfits are then visualized on the user’s body using Amazon Nova Canvas, enabling a realistic virtual try-on experience. Additionally, an AI-powered chatbot was implemented using AWS Bedrock tools, allowing users to ask questions about their wardrobe, outfit combinations, and styling suggestions based on their saved items and recent activity.
- AI-powered personalized outfit recommendations
- Digital wardrobe (closet) management system
- Virtual try-on using user body images
- Occasion-based outfit suggestions
- Weather-aware styling recommendations
Client Overview
The client aimed to build an innovative AI-powered fashion solution that simplifies how users manage their wardrobe and make daily outfit decisions. The vision was to create a digital styling assistant that goes beyond traditional fashion apps by combining wardrobe digitization, personalized recommendations, and virtual try-on capabilities.
Engagement Objectives
To create a highly interactive, AI-powered fashion experience that keeps users engaged through personalization, visualization, and intelligent styling assistance.
- Increase daily user engagement through personalized outfit recommendations
- Enable continuous interaction via AI-powered fashion chatbot
- Encourage users to upload and manage complete digital wardrobes
- Improve user retention with virtual try-on experiences
- Help users plan outfits based on occasions, weather, and calendar events
Results And Outcomes
Delivered smarter wardrobe decisions, reduced outfit confusion, and enhanced user experience through AI-powered personalization and virtual try-on capabilities.
- Improved user decision-making for daily outfit selection
- Delivered highly personalized AI-based fashion recommendations
- Reduced effort in wardrobe management through digitization
- Enhanced user engagement via virtual try-on experience
- Enabled smarter outfit planning using weather and calendar data
Conclusion
CLOQR demonstrates how AI can transform personal fashion management by combining wardrobe digitization, virtual try-on technology, and intelligent styling recommendations into a single platform. By leveraging AWS cloud services and generative AI capabilities, ExpertsCloud delivered a scalable, secure, and highly personalized fashion experience that helps users confidently plan and visualize their outfits every day.