Closet AI 리세일 커머스 플랫폼 by Ruoxuan Pan, Junjie Tang and Huixiang Chen is a highly esteemed winner of the very prestigious 2026 A' Design Award 철상 in 모바일 기술, 애플리케이션 및 소프트웨어 디자인 Competition Category.
철모바일· 2026
Closet AI 리세일 커머스 플랫폼
by Ruoxuan Pan, Junjie Tang and Huixiang Chen
A' Design Award 철상 Winner in 모바일 Category
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The Design
About Closet AI 리세일 커머스 플랫폼
Closet AI는 중고 의류를 위한 모바일 리세일 플랫폼입니다. 사용자가 의류 이미지를 업로드하면 애플리케이션이 리세일 데이터를 기반으로 카테고리, 설명, 추천 가격을 생성합니다. 협상 과정에서는 시스템이 답변 제안을 초안으로 작성하고 사용자가 이를 수정하거나 승인할 수 있어 최종 결정권은 판매자에게 남습니다. 리워드 시스템은 퀘스트, 배지, 마일스톤을 통해 진행 상황을 추적합니다. 이 플랫폼은 리세일 행동에 대한 연구를 바탕으로 개발되었습니다. 순환 패션 참여를 가로막는 시간과 노력을 줄이는 것이 목표입니다.
The Recognition
About the A' Design Award 철상
Closet AI 리세일 커머스 플랫폼, 이 작품은 A' Design Award 철상 수상작으로, 잘 디자인된 창작물에 기대되는 전문적·산업적 요건을 충족하는 좋은 디자인에 수여되는 권위 있는 인정입니다. 철상 수상작은 창작자의 뛰어난 기술, 높은 전문성, 전문가다운 이해, 창의적 역량을 보여 줍니다. Closet AI 리세일 커머스 플랫폼, 이 작품은 높이 평가받고 감탄과 사랑을 받는 창작물로서 실용적이고 혁신적일 것으로 기대됩니다. 이 철상 수상 디자인은 업계 모범 사례를 통합하며 노하우와 재능으로 연결된 유능한 기술적 특성을 갖추고 있습니다. Closet AI 리세일 커머스 플랫폼, 이 작품은 철저함으로 존중받으며 삶의 질을 개선하여 세상을 더 나은 곳으로 만들도록 디자인되었습니다.
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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