Creator and commerce decision
Sneakmart
A small team or capable developer can reproduce a useful members-only storefront and checkout, but the product's value also relies on curated brand inventory, mobile app polish, member base and AI try-on which are not practical to replicate quickly.
Visit website↗Not priced
No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.
$100one-off36 h to build
$20/mo3 h/mo upkeep
No published price to break even against.
No open-source build does this yet
Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.
What a replacement has to do
- Provide a members-only catalogue of private-sale products, allow browsing and purchasing with membership gating and payments, and send order/launch notifications.
What it still won’t have
- Curated brand partnerships and exclusive inventory sourcing
- Mobile-app store presence and app-store UX polish
- Proprietary AI try-on feature (Ai.Fits) and advanced personalization
- Scale, marketing, and existing member base
What remains hard
- Product polish and ongoing maintenance
First-year cost
No published price
Sneakmart does not publish a price we could read, so there is nothing to compare against. What building costs is below.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a members-only private-sales web app using Next.js (React) + PostgreSQL (Supabase) + Stripe for payments, deployed on Vercel. Core features in scope: email/password auth and membership state, admin UI to create/schedule private sales and upload product metadata/images, public browse UI that shows member-only sales, Stripe checkout integration and order persistence, and transactional email notifications. Out of scope: mobile App Store submissions, building brand partnerships or sourcing inventory, advanced AI try-on/avatar features. Include error handling, input validation, and unit/integration tests for auth, checkout, and sales scheduling.
How we checked
How the score was reached
- Partly verdict base52
- 2 cited sources+1
- 3/3 assessment runs agreed+4
- Evidence score57
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.
How scoring works →Cited sources · 2
Every page the run actually retrieved.
- official productofficial-product
- official pricingofficial-pricing
Integrity checks
What held up, and what did not.
