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Development of Integrated Ecommerce Platform with AI-Driven Custom Sizing Solution

rst.software

eCommerce

Environmental Services

Information technology

Key Challenges Identified

Legacy Angular frontend components needed integration with modern Vue.js architecture while enhancing backend capabilities to support ML-powered sizing algorithms and zero-waste production workflows. Required improved CMS functionality for efficient ecommerce management.

About the Client

Clothing technology company specializing in made-to-order garments using machine learning for perfect-fit sizing

Strategic Project Goals

Create unified frontend architecture combining legacy and modern components
Enhance Django backend to support advanced machine learning workflows
Implement intuitive user experience for custom clothing configuration
Enable seamless made-to-order production with zero inventory waste

Core System Capabilities

AI-powered clothing size generator (4-input: height, weight, age, shoe size)
Seamless Angular-Vue.js frontend integration
Custom CMS for product and order management
User account system with saved size profiles
Mobile-optimized shopping experience
Production waste tracking dashboard

Technology Stack Requirements

Vue.js

Django

Python

Google Cloud

Docker

Gulp

System Integration Needs

Content Management System (CMS)
Machine Learning engine API
Production workflow automation tools
Analytics and reporting platforms

Operational Requirements

99% sizing algorithm accuracy
Scalable cloud infrastructure
High-performance frontend rendering
Enterprise-grade data security

Expected Business Outcomes

Enables mass customization of clothing with 140,000+ tons annual fabric waste reduction, improves customer satisfaction through perfect-fit guarantee, increases conversion rates with intuitive UX, and establishes foundation for AI-driven fashion production ecosystem.