October 18, 2025
Featured Project

Moyle

Moyvle — a US-focused K-fashion marketplace app built with React Native, delivering fast checkout, real-time tracking, and clear sizing for Korean brands.

Node.js
Express.js
ReactNative
Firebase
Mysql
AWS
Python
FastApi
Selenium

Project Images

Moyle - Image 1
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About This Project

Moyvle is a mobile marketplace I built to bring authentic Korean fashion to shoppers in the United States, with a clean, fast experience from discovery to delivery. Developed in React Native with TypeScript, the app integrates directly with backend catalog, order, and payment APIs to provide real-time inventory, clear US pricing, and reliable checkout. Users can browse curated brands and indie designers, search with smart filters for size, fit, color, and price, and make confident choices with detailed product pages, measurement-based sizing guidance tailored to Korean labels, and community reviews. The end-to-end flow includes secure, encrypted payments, transparent shipping windows, live order tracking, and an easy returns process, while wishlists, favorites, and optional price/restock alerts keep customers engaged. Under the hood, image optimization, cached queries, and incremental loading maintain smooth scrolling and quick time-to-interactive; robust error handling, retry/backoff, and idempotent order steps protect the checkout path; and analytics events across the funnel inform iteration on conversion and retention. Designed for performance, privacy, and scale, Moyvle turns K-fashion discovery into a dependable, mobile-first shopping experience for the US market.


Highlights

  • Curated catalog with smart filters (size, fit, brand, price) and detailed product pages

  • Secure, fast checkout with real-time order tracking

  • Wishlists, price/restock alerts, clear US pricing & shipping windows

  • Accurate sizing guidance tailored to Korean brands


Architecture

  • RN app (state mgmt + offline caching) ↔ backend APIs (catalog, orders, payments)

  • Background tasks for cart sync, notifications, and tracking events

  • Release pipeline with versioning and crash/usage analytics


Challenges & solutions

  • Sizing & returns: standardized fit notes + measurement tables to reduce confusion

  • Performance: image optimization, cached lists, and incremental loading for smooth scroll

  • Reliability: idempotent order flows and robust error handling around payments & network

Project Links

Live Demos

Demo 1Demo 2

Project Info

Status
⭐ Featured
Technologies9
Images3
Demos2

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