FashionGram

Gallery

About

FashionGram is a digital wardrobe: users photograph what they own, mix outfits in a virtual fitting room, save looks to dates, and get AI suggestions for the one missing piece — instead of buying a third white blouse they already own. Live demo: https://fashion-gram.vercel.app Features (all working) - Closet with filters by category, color, season, brand, size - Add a piece from a photo (compressed client-side) - Fitting room: build outfits from closet pieces, save to a date & occasion - Looks calendar - AI "Complete the look": suggests up to 3 partner-shop items with reasons - Closet insights: color breakdown, duplicate detection, missing-category gaps - Social layer: timeline, explore public pieces, follow members, public profiles - Items can be flagged for sale / rent / exchange - Starter closet seeded on first sign-in so new users never see an empty app - Stop buying what you already own — the closet remembers for you The real asset: the data model Every user records their sizes (top / bottom / shoes), colors, brands and what they actually wear. That is the raw material for: - Size recommendation & returns reduction for fashion e-commerce - Affiliate / partner-brand revenue on "complete the look" - Anonymized trend data sold to brands The consumer app is the front door; the sizing data is the business. Tech stack TanStack Start, React, TypeScript, Tailwind, Better Auth, PostgreSQL (Kysely), deployed on Vercel. Clean migrations, tests, no secrets in the repo. Handover note Google/X sign-in currently runs through the original build platform's auth service; the buyer connects their own OAuth keys (a few hours of work). Email sign-in is built in. What you get - Full source code (GitHub repo transfer) - Database schema & migrations - Vercel deployment / handover support - Original product concept & monetization notes Status: pre-revenue, no users yet. Priced as a launch-ready product, not a business.