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Closet AI منصة تجارة إعادة البيع by Ruoxuan Pan, Junjie Tang and Huixiang Chen

Closet AI منصة تجارة إعادة البيع by Ruoxuan Pan, Junjie Tang and Huixiang Chen is a highly esteemed winner of the very prestigious 2026 جائزة A' Design Award الحديدية in تصميم تقنيات وتطبيقات وبرمجيات الجوال Competition Category.


حديدالجوال· 2026

Closet AI منصة تجارة إعادة البيع

by Ruoxuan Pan, Junjie Tang and Huixiang Chen

جائزة A' Design Award الحديدية Winner in الجوال Category

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Verified Award Winner

Verify Award Status for #182338

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The Design

About Closet AI منصة تجارة إعادة البيع

"Closet AI" هي منصة تطبيق للهواتف المحمولة مخصّصة لإعادة بيع الملابس المستعملة. يقوم المستخدمون برفع صور الملابس، ويولّد التطبيق الفئات والأوصاف والأسعار المقترحة استناداً إلى بيانات إعادة البيع. وخلال مرحلة التفاوض، يصوغ النظام اقتراحات للردود يمكن للمستخدمين تعديلها أو الموافقة عليها، بحيث تبقى القرارات النهائية بيد البائع. كما يتضمّن نظام مكافآت يتتبّع التقدّم من خلال المهام والشارات والإنجازات. وقد جرى تطوير المنصة استناداً إلى أبحاث حول سلوك إعادة البيع، بهدف تقليص الوقت والجهد اللذين يثبّطان المشاركة في الموضة الدائرية.

The Recognition

About the جائزة A' Design Award الحديدية

Closet AI منصة تجارة إعادة البيع هو فائز بجائزة A' Design Award الحديدية، وهي تقدير مرموق يُمنح للتصاميم الجيدة التي تلبّي المتطلبات المهنية والصناعية المنتظرة من الإبداعات حسنة التصميم. ويُظهر الفائزون بالحديدية مهارة كبيرة وتخصصًا عاليًا وفهمًا خبيرًا وقدرة إبداعية لدى صنّاعهم. ويُتوقع أن يكون Closet AI منصة تجارة إعادة البيع إبداعًا عالي التقدير ومحل إعجاب وحب، عمليًا ومبتكرًا. وهذا التصميم الفائز بجائزة A' Design Award الحديدية يدمج أفضل ممارسات القطاع، وله خصائص تقنية كفؤة ترتبط بالدراية والموهبة. ويحظى Closet AI منصة تجارة إعادة البيع بالاحترام لدقته، وقد صُمّم لتقديم تحسينات لجودة الحياة تساعد على جعل العالم مكانًا أفضل.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties
Closet AI is an AI powered resale platform designed to remove friction from circular fashion. It automates listing creation, pricing suggestions and negotiation support, transforming second hand selling into a streamlined experience. By integrating intelligent automation with a reward system that tracks impact and milestones, Closet AI reduces emotional barriers and encourages sustainable participation, making fashion circulation measurable and efficient.
Dimensions & Packaging
Closet AI is a mobile first digital platform prototyped in Figma at 402 x 874 pixels aligned with iPhone interface standards. The system follows a modular and scalable architecture supporting real time feedback and adaptive interaction flows. A structured design system ensures visual consistency accessibility compliance and responsive layout behavior across future multi platform extensions.
Tags
AI powered resale platform, UX/UI design, circular fashion system, sustainable commerce design, intelligent negotiation support, automated listing generation, user centered interaction design, behavioral incentive system, mobile marketplace experience, fashion sustainability innovation
Production Technology
Closet AI was developed through a human centered design process informed by user research and resale behavior analysis. Insights into pricing uncertainty and negotiation stress shaped the interaction framework. Computer vision, natural language generation and data driven recommendations were integrated as supportive technologies. Iterative prototyping refined the system into an assisted workflow that reduces cognitive load while preserving user agency.
Design Challenge
The major challenge was balancing automation with user autonomy. Fully automated systems risk removing agency, while manual systems maintain friction. Closet AI introduces assisted intelligence, where AI drafts and recommends actions but users retain final control. Another challenge was integrating sustainability incentives without overwhelming users. The solution implements subtle impact indicators and milestone badges that reinforce behavior without creating gamified complexity.
Research
Type of Research: Qualitative behavioral research and workflow analysis. Research Objectives: To identify barriers preventing users from participating in clothing resale despite sustainability awareness. Methodology: User interviews journey mapping and competitive benchmarking. Data Collection: Structured interviews usability testing and prototyping. Participants: Gen Z and Millennial users. Results: Identified negotiation fatigue and listing complexity as key friction points. Insights and Impact: Automation reduces participation barriers and supports circular fashion adoption.
Inspiration
Closet AI was inspired by the gap between sustainable intention and practical behavior. While many Gen Z and Millennial users want to reduce waste, resale platforms often demand time and effort. Listing creation, price negotiation and cross platform management introduce friction that discourages participation. The project explores how artificial intelligence can reduce this friction and connect resale with meaningful environmental impact.
Project Duration
The project began in Dec 2025 in Austin and is currently in advanced prototype development.
Operation Flow
Users upload clothing images to generate automatic categories, descriptions, and smart pricing suggestions based on resale data. They publish listings, track engagement insights, and receive recommendations such as price adjustments or repost timing. Users complete quests, earn badges, and unlock milestones as they list, optimize, and close deals. During negotiations, AI drafts reply suggestions that users can edit or approve, keeping full control.
Team Members
Ruoxuan Pan
Junjie Tang
Huixiang Chen
Image Credits
Main Image: Creator Junjie Tang, Huixiang Chen, Closet AI Home page and Swipe flow, 2026
Image #1: Creator Huixiang Chen, Item Scan, Item Swipe and Select, Item Editing, and Item Posting page, 2026
Image #2: Creator Ruoxuan Pan, AI listing and message assistant flow, 2026
Image #3: Creator Junjie Tang, reward and badge pages, 2026
Image #4: Creator Ruoxuan Pan, Huixiang Chen, Junjie Tang, Closet AI interface overview, 2026

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