Commerce & Marketplaces · Est. $18k – $20k
Curtsy

Buy & Sell Women’s Fashion

Coralsoft designed, built and shipped this product for the client.

iOSWebCloudReact NativeExpo SDK 54Expo Router
Curtsy — product interface
Curtsy — product interface
The situation

What was in place before we started.

Curtsy is a peer-to-peer resale marketplace for women’s secondhand fashion, loved by 1M+ women. Sellers list an item in under a minute with AI-assisted pricing and brand detection, daily curated drops surface picks in her size, and sellers get paid the moment the item is scanned at the post office.

Curtsy is a peer-to-peer resale marketplace for women’s secondhand fashion, loved by 1M+ women. Sellers list an item in under a minute with AI-assisted pricing and brand detection, daily curated drops surface picks in her size, and sellers get paid the moment the item is scanned at the post office.

Estimated Engagement
5 months
Team
3 people
Estimated Budget
$18k – $20k
Year
2026
Used by
Women sellers · Closet clearers · Trend hunters · Budget shoppers
Platforms
iOS & web (no Android app)
Coverage
Fast listing, daily drops, offers, sell
Pricing
Free to list · fee-free posting days
Estimated stack
React NativeExpo SDK 54Expo RouterTypeScriptNativeWindTanStack QueryReact Hook Form + ZodVercel AI SDKpgvectorTypesenseSupabase (Postgres + RLS)Supabase Auth
Delivery story

Curtsy: a faster path from discovery to transaction

01

Challenge

Curtsy is a peer-to-peer resale marketplace for women’s secondhand fashion, loved by 1M+ women. The main delivery challenge was to give users a fast, trustworthy journey across discovery, listing, checkout, and post-purchase states, while keeping List, Price, and Drop consistent across the complete journey. We framed the engagement around the smallest production-worthy flow first, then expanded the scope without weakening the underlying component and data model.

02

How we built it

We began by mapping the user journey and the boundaries of the AI: what context it receives, what it may return, and where deterministic application logic must stay in control. We then built List, Price, and Drop as small end-to-end slices, connecting the interface to the data and model layers early so the team could test real responses instead of static mock-ups. Prompt, validation, and fallback behaviour were refined alongside the product UI. The main implementation used React Native, Expo SDK 54, Expo Router, and TypeScript, with typed contracts keeping the JavaScript stack consistent across the product.

03

Delivery

The delivered scope brought List, Price, Drop, and Discover into one coherent cross-platform mobile release. Model output, product logic, and user feedback are separated clearly, which makes the AI easier to evaluate and evolve. For Curtsy, the practical result is a product that communicates its value quickly while giving the team a maintainable base for continued delivery in commerce & marketplaces.

Challenges

Each constraint, and what we did about it.

Constraint

Listing takes too long to bother

What we did

List an item in under a minute

Constraint

Pricing is guesswork

What we did

AI-assisted pricing & brand detection

Constraint

Wrong sizes & styles everywhere

What we did

Daily curated drops in your size

Constraint

Best pieces buried in the scroll

What we did

Fee-free posting days

Constraint

Payouts wait on the buyer

What we did

Paid when the item is scanned

Constraint

Selling feels like a chore

What we did

Cross-list import from other apps

The unlock isn’t more listings — it’s speed. Under-a-minute listing and pay-on-scan make resale effortless.

Results

Measured outcomes.

5-month engagement
<60s
To list an item.
+44%
Daily-drop to first-purchase conversion.
4.8★
Across App Store reviews.
1M+
Women on the marketplace.
AI
Assisted pricing & brand detection
Daily
Curated drops opened
Scan
Pay-on-scan payouts
↑
Listings per active seller

By making listing take under a minute and paying sellers on scan, Curtsy turned closet-clearing into a habit — and AI-assisted pricing made every listing faster to post and easier to sell.

Roadmap

Estimated delivery sequence.

5 months
Month 1

Discovery & shaping

Discovery with women closet-clearers; mapping the “list it fast” moment.

  • Fast Listing
  • Discover
Months 2–4

Core build

Under-a-minute listing, AI pricing & brand detection, daily drops, discover & offers.

  • Daily Drops
Month 5

Launch & iterate

Pay-on-scan payouts, fee-free posting days, cross-list import & support at scale.

  • Sell

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Every case study covers a product Coralsoft designed, built, and shipped for a client.