TryOn
AI-Powered Virtual Clothing Try-On — Designed, Built, and Published to the App Store
Download on the App Store →
Project Overview
TryOn is a consumer iOS app that answers a simple question shoppers have always asked: "How would that actually look on me?" A user uploads a few body photos once, then photographs any garment or full outfit — in a store, from a screenshot, or from their camera roll — and the app returns a photorealistic image of themselves wearing it.
This was a solo, end-to-end product build: native mobile frontend, cloud backend, AI image pipeline, payments, social layer, privacy/compliance tooling, and the full App Store submission and review process. It is live on the App Store today.
The Challenge
Virtual try-on is deceptively hard. It has to feel instant and magical while quietly handling some genuinely difficult problems — image generation quality, cost control, sensitive photo data, content moderation, and Apple's review bar for AI apps that process user photos.
- Believable results from a couple of casual body photos plus an arbitrary clothing image — no studio, no green screen
- Photo privacy — body photos are sensitive; users need clear consent and real control over their data
- Unbounded AI cost — generative image calls are expensive and easy to abuse without pacing
- App Store compliance — AI-content disclosure, per-use AI consent, user-generated-content moderation, and in-app-purchase rules
The Solution
TryOn pairs a polished React Native (Expo) app with a TypeScript/Node.js backend and a queued AI image pipeline built on xAI's Grok Imagine. The architecture keeps sensitive photos in a private store, gates every AI call behind explicit consent, and meters generation to keep costs predictable.
- AI Try-On Engine: Body and clothing photos are sent to xAI Grok Imagine and composited into a photorealistic result in 10–30 seconds, every result carrying a visible "AI-generated" badge
- Privacy by Design: Photos live in a private AWS S3 bucket served only through short-lived presigned URLs; the profile close-up photo is never sent to any AI service; users can export or delete all their data
- Layered Consent: A dedicated AI-processing consent modal names xAI / Grok Imagine and lists exactly what is and isn't sent before any photo is transmitted
- Monetization: StoreKit 2 with Apple App Store Server Notifications V2 — two auto-renewing subscription tiers plus consumable credit packs, with entitlement granted only after server-side, Apple-signed receipt verification
- Social Layer: A Discover feed of public try-ons with follow, block, report, and per-post privacy controls for content moderation
- Cost Control: A per-user job queue paces bursts of generations with a visible countdown, protecting against runaway API spend without blocking legitimate use
Technical Architecture
Key Results
Shipped a complete, monetized AI consumer app to the App Store — frontend, backend, AI pipeline, payments, and compliance — and passed Apple's review for an app that processes user photos with generative AI.
- Live on the App Store with auto-renewing subscriptions and twelve consumable credit packs wired through verified StoreKit receipts
- Privacy-first data handling — private S3 storage, presigned-URL access, full data export and account deletion built in for GDPR/CCPA
- Guideline-ready compliance — AI-content disclosure, dedicated per-use AI consent, and a full report/block moderation stack for user-generated content
- Predictable unit economics — a queue-based throttle paces expensive AI calls so cost scales with revenue, not with abuse
Want an App Like This?
TryOn shows what a single engineer can ship end-to-end: a native mobile app, a production backend, a generative-AI pipeline, real payments, and a successful App Store launch. If you have a mobile or AI product idea and want it built and shipped — not just prototyped — let's talk.