Ruoxuan Pan, Junjie Tang and Huixiang Chen tomonidan Closet AI Qayta sotish savdo platformasi

Ruoxuan Pan, Junjie Tang and Huixiang Chen tomonidan yaratilgan Closet AI Qayta sotish savdo platformasi — Mobil Texnologiyalar, Ilovalar va Dasturiy Ta'minot Dizayni tanlov toifasida nufuzli 2026 A' Design Award Temir Mukofoti mukofotining yuqori baholangan g'olibidir.

TemirMobil· 2026

Closet AI Qayta sotish savdo platformasi

muallif: Ruoxuan Pan, Junjie Tang and Huixiang Chen

Mobil toifasida A' Design Award Temir Mukofoti g'olibi

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A' Design Award saytida ko'rish Press-reliz Mukofot nishoni

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Dizayn

Closet AI Qayta sotish savdo platformasi haqida

Closet AI — ikkinchi qo'l kiyimlar uchun mo'ljallangan mobil qayta sotish platformasi. Foydalanuvchilar kiyim rasmlarini yuklaydilar, ilova esa qayta sotish ma'lumotlari asosida toifalar, tavsiflar va tavsiya etilgan narxlarni yaratadi. Muzokara jarayonida tizim javob takliflarining qoralamalarini tuzadi, foydalanuvchilar ularni tahrirlashi yoki tasdiqlashi mumkin, shu tariqa yakuniy qarorlar sotuvchida qoladi. Mukofot tizimi topshiriqlar, nishonlar va bosqichlar orqali taraqqiyotni kuzatib boradi. Platforma qayta sotish xatti-harakatlarini o'rganish bo'yicha tadqiqotlar asosida ishlab chiqilgan. Maqsad — aylanma moda ishtirokiga to'sqinlik qiluvchi vaqt va mehnat sarfini kamaytirish.

Tan olinish

A' Design Award Temir Mukofoti haqida

Closet AI Qayta sotish savdo platformasi A' Design Award Temir Mukofotining g‘olibi bo‘lib, bu yaxshi loyihalangan ijodlardan kutiladigan kasbiy va sanoat talablariga javob beradigan yaxshi dizaynlarga beriladigan nufuzli e’tirofdir. Temir g‘oliblari o‘z yaratuvchilarining katta mahorati, yuksak ixtisosligi, mutaxassis tushunchasi va ijodiy salohiyatini namoyon etadi. Closet AI Qayta sotish savdo platformasi yuqori qadrlanadigan, hayrat bilan qaraladigan va suyukli, amaliy hamda innovatsion ijod bo‘lishi kutiladi. A' Design Award Temir Mukofotini qo‘lga kiritgan ushbu dizayn soha eng yaxshi amaliyotlarini uyg‘unlashtiradi va bilim hamda iste’dod bilan bog‘langan layoqatli texnik xususiyatlarga ega. Closet AI Qayta sotish savdo platformasi puxtaligi uchun hurmatga sazovor bo‘lib, dunyoni yaxshiroq joyga aylantirishga yordam beradigan hayot sifatini yaxshilashni taqdim etish uchun loyihalangan.

Dizayn ortida

Press-kit

Dizayner tomonidan taqdim etilgan kreditlar, jamoa a'zolari va texnik tafsilotlar.

Noyob xususiyatlar: 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.
O'lchamlar va qadoqlash: 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.
Teglar: 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
Ishlab chiqarish texnologiyasi: 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.
Dizayn muammosi: 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.
Tadqiqot: 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.
Ilhom: 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.
Loyiha muddati: The project began in Dec 2025 in Austin and is currently in advanced prototype development.
Ish jarayoni: 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.
Jamoa a'zolari: Ruoxuan Pan
Junjie Tang
Huixiang Chen
Rasm mualliflari: 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