Closet AI Sethala sa Khoebo ea Thekiso Bocha ka Ruoxuan Pan, Junjie Tang and Huixiang Chen

Moralo oa Closet AI Sethala sa Khoebo ea Thekiso Bocha ka Ruoxuan Pan, Junjie Tang and Huixiang Chen ke mohlodi oa khau e hlomphehang haholo ya 2026 Moputso oa Tšepe oa A' Design Award Mokhahleong oa Tlhodisano oa Moralo wa Theknoloji ya Mehala, Diaplikeishene le Softwere.

TšepeMohala· 2026

Closet AI Sethala sa Khoebo ea Thekiso Bocha

ka Ruoxuan Pan, Junjie Tang and Huixiang Chen

Mohlodi oa Moputso oa Tšepe oa A' Design Award Mokhahleong oa Mohala

6,336

Mohlodi oa Khau ea Netefaditsweng

Netefatsa Boemo ba Khau bakeng sa #182338

Sheba ho A' Design Award Tokollo ya Boraditaba Baeche ya Moputso

Mebala

Moralo

Mabapi le Closet AI Sethala sa Khoebo ea Thekiso Bocha

Closet AI ke sethala sa mobile sa thekiso bocha ea liaparo tse sebelisitsoeng. Basebelisi ba kenya litšoantšo tsa liaparo, 'me sesebelisoa se hlahisa mekhahlelo, litlhaloso le litheko tse khothaletsoang ho ipapisitsoe le lintlha tsa thekiso bocha. Nakong ea lipuisano, sistimi e ngola litlhahiso tsa likarabo tseo basebelisi ba ka li fetolang kapa ba li amohelang, e le hore liqeto tsa ho qetela li lule li le matsohong a morekisi. Sistimi ea meputso e latela tsoelo-pele ka mesebetsi, libeche le maemo a finyeletsoeng. Sethala sena se ntlafalitsoe ka lipatlisiso mabapi le boitšoaro ba thekiso bocha. Sepheo ke ho fokotsa nako le boiteko tse nyahamisang ho nka karolo feshene e potolohang.

Kamohelo

Mabapi le Moputso oa Tšepe oa A' Design Award

Closet AI Sethala sa Khoebo ea Thekiso Bocha ke mohapi oa Moputso oa Tšepe oa A' Design Award, kananelo e hlomphehang e fuoang meralo e metle e finyellang litlhoko tsa porofeshenale le tsa indasteri tse lebelletsoeng ho lintho tse hlahisitsoeng tse entsoeng hantle. Bahapi ba Tšepe ba bontša bokhoni bo boholo, bokhethehi bo phahameng, kutloisiso ea litsebi le bokhoni ba boqapi ba baqapi ba bona. Closet AI Sethala sa Khoebo ea Thekiso Bocha e lebelletsoe ho ba ntho e hlahisitsoeng e hlomphuoang haholo, e ratoang le e ratehang, e sebetsang le e nang le mehopolo e mecha. Moralo ona o hapileng Moputso oa Tšepe oa A' Design Award o kenyelletsa mekhoa e metle ka ho fetesisa ea indasteri mme o na le litšobotsi tsa theknoloji tse nang le bokhoni tse amanang le tsebo le talenta. Ka lebaka la botlalo ba eona, Closet AI Sethala sa Khoebo ea Thekiso Bocha e tšoanelehela tlhompho mme e entsoe ho fana ka ntlafatso ea bophelo e thusang ho etsa hore lefatše le be sebaka se molemo.

Ka Mora Moralo

Sete ya Boraditaba

Litlhaku, ditho tsa sehlopha le lintlha tsa botekgeniki tse fanoeng ke moetsi wa moralo.

Boleng bo Ikhethang: 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.
Boholo le Phuthelo: 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.
Lithegi: 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
Theknoloji ya Tlhahiso: 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.
Phephetso ya Moralo: 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.
Dipatlisiso: 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.
Kgothaletso: 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.
Nako ya Projeke: The project began in Dec 2025 in Austin and is currently in advanced prototype development.
Tsamaiso ya Mosebetsi: 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.
Litho tsa Sehlopha: Ruoxuan Pan
Junjie Tang
Huixiang Chen
Litlotla tsa Setshwantsho: 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