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Closet AI Jukwaa la Biashara ya Bidhaa Zilizotumika by Ruoxuan Pan, Junjie Tang and Huixiang Chen

Closet AI Jukwaa la Biashara ya Bidhaa Zilizotumika by Ruoxuan Pan, Junjie Tang and Huixiang Chen is a highly esteemed winner of the very prestigious 2026 Tuzo ya Chuma ya A' Design Award in Usanifu wa Teknolojia ya Simu, Programu na Programu Competition Category.


ChumaSimu· 2026

Closet AI Jukwaa la Biashara ya Bidhaa Zilizotumika

by Ruoxuan Pan, Junjie Tang and Huixiang Chen

Tuzo ya Chuma ya A' Design Award Winner in Simu Category

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Verified Award Winner

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The Design

About Closet AI Jukwaa la Biashara ya Bidhaa Zilizotumika

Closet AI ni jukwaa la simu la mauzo ya nguo zilizotumika. Watumiaji hupakia picha za nguo, na programu hutengeneza aina, maelezo na bei zinazopendekezwa kulingana na data ya mauzo ya bidhaa zilizotumika. Wakati wa mazungumzo ya bei, mfumo huandaa mapendekezo ya majibu ambayo watumiaji wanaweza kuhariri au kuidhinisha, hivyo maamuzi ya mwisho hubaki kwa muuzaji. Mfumo wa zawadi hufuatilia maendeleo kupitia majukumu, beji na hatua muhimu. Jukwaa hili lilitengenezwa kupitia utafiti kuhusu tabia za mauzo ya bidhaa zilizotumika. Lengo ni kupunguza muda na juhudi zinazokatisha tamaa ushiriki katika mtindo wa mzunguko.

The Recognition

About the Tuzo ya Chuma ya A' Design Award

Closet AI Jukwaa la Biashara ya Bidhaa Zilizotumika ni mshindi wa Tuzo ya Chuma ya A' Design Award, utambuzi wenye heshima unaotolewa kwa miundo mizuri inayokidhi mahitaji ya kitaalamu na ya kiviwanda yanayotarajiwa kutoka kwa kazi zilizobuniwa vizuri. Washindi wa Chuma huonyesha ustadi mkubwa, utaalamu wa hali ya juu, uelewa wa kitaalamu na uwezo wa kibunifu wa waumbaji wao. Closet AI Jukwaa la Biashara ya Bidhaa Zilizotumika inatarajiwa kuwa kazi inayothaminiwa sana, kupendwa na kuenziwa, ambayo ni ya vitendo na bunifu. Muundo huu ulioshinda Tuzo ya Chuma ya A' Design Award unajumuisha mbinu bora za tasnia na una sifa za kiufundi zenye uwezo zilizounganishwa na ujuzi na kipaji. Closet AI Jukwaa la Biashara ya Bidhaa Zilizotumika inaheshimiwa kwa uangalifu wake na imebuniwa kutoa maboresho ya ubora wa maisha yanayosaidia kuufanya ulimwengu kuwa mahali bora zaidi.

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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