Closet AI Platfòm Komès Revant pa Ruoxuan Pan, Junjie Tang and Huixiang Chen

Dizayn Closet AI Platfòm Komès Revant pa Ruoxuan Pan, Junjie Tang and Huixiang Chen se yon gayan ki gen anpil estim nan konpetisyon trè prestijye 2026 A' Design Award Fè nan Kategori Konpetisyon Mobil.

FèMobil· 2026

Closet AI Platfòm Komès Revant

pa Ruoxuan Pan, Junjie Tang and Huixiang Chen

Gayan A' Design Award Fè nan Kategori Mobil

6,336

Gayan Pri Verifye

Verifye Estati Pri pou #182338

Gade sou A' Design Award Kominike Laprès Badj Prim

Koulè

Konsepsyon an

Konsènan Closet AI Platfòm Komès Revant

Closet AI se yon platfòm revant mobil pou rad dezyèm men. Itilizatè yo telechaje imaj rad, epi aplikasyon an jenere kategori, deskripsyon ak pri sijere ki baze sou done revant. Pandan negosyasyon, sistèm nan prepare sijesyon repons ke itilizatè yo ka modifye oswa apwouve, kidonk desizyon final yo rete nan men vandè a. Yon sistèm rekonpans swiv pwogrè atravè misyon, badj ak etap enpòtan. Platfòm nan te devlope atravè rechèch sou konpòtman revant. Objektif la se redwi tan ak efò ki dekouraje patisipasyon nan mòd sikilè.

Rekonesans lan

Konsènan A' Design Award Fè

Closet AI Platfòm Komès Revant se yon ganyan A' Design Award Fè, yon rekonesans ki gen prestij yo bay bon design ki satisfè egzijans pwofesyonèl ak endistriyèl yo atann de kreyasyon ki byen fèt. Ganyan Fè yo montre gwo konpetans, espesyalizasyon wo, konpreyansyon ekspè ak kapasite kreyatif kreyatè yo. Yo atann Closet AI Platfòm Komès Revant pou se yon kreyasyon anpil moun estime, admire e renmen ki pratik e inovatè. Design sa a ki ganyen A' Design Award Fè entegre pi bon pratik sektè a e li gen karakteristik teknik konpetan ki lye ak konnesans pratik ak talan. Yo respekte Closet AI Platfòm Komès Revant pou jèntan li e li fèt pou bay amelyorasyon kalite lavi ki ede fè mond lan vin yon pi bon kote.

Dèyè Konsepsyon an

Dosye Laprès

Kredi, manm ekip ak detay teknik konseptè a bay.

Pwopriyete Inik: 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.
Dimansyon & Anbalaj: 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.
Etikèt: 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
Teknoloji Pwodiksyon: 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.
Defi Dizayn: 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.
Rechèch: 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.
Enspirasyon: 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.
Dire Pwojè: The project began in Dec 2025 in Austin and is currently in advanced prototype development.
Fliks Operasyon: 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.
Manm Ekip: Ruoxuan Pan
Junjie Tang
Huixiang Chen
Kredi Imaj: 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