Creator and commerce decision
Sellier
A competent developer can reproduce the core photo-processing pipeline (background removal + relighting + crop) using existing open-source projects and a small backend, but delivering the full polished iOS product, App Store presence, and UX polish that Sellier offers is more work; recommended to build a narrower workflow rather than a full clone.
Visit website↗Built by Benjamin | Product Builder, who ships 4 products in this index
Not priced
No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.
$100one-off60 h to build
$30/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
- 1) Remove background from an uploaded garment photo. 2) Apply studio lighting and selected visual style to the subject. 3) Crop/resize and pad to portrait 4:5 and export JPEG/PNG. 4) Mobile UI: photo capture, style selector, preview, and download/share. 5) Serverless inference endpoint to run image model(s) and return processed image. 6) Account/subscription stub (local unlock per-month free generation).
What it still won’t have
- Polished App Store presence and onboarding flows
- High-quality UI/UX and mobile polishing (animations, analytics, crash reporting)
- Proprietary models or any vendor-specific optimizations Sellier may use
- Marketing, brand trust, and integrated marketplace shortcuts (deep links tuned to Vinted/etc.)
What remains hard
- Product polish and ongoing maintenance
First-year cost
No published price
Sellier 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 minimal Sellier replacement: backend in Python/Flask (or FastAPI) deployed to a small VM or serverless functions, using an open-source background-removal model (e.g., repo: nadermx/backgroundremover) and an image-stylization step (Diffusers or lightweight relighting), store temporary images in S3-compatible storage, and expose a POST /process endpoint that accepts an image and style id and returns a 4:5 cropped JPEG. Build an iOS SwiftUI app that captures or picks a photo, calls /process, shows a preview, and allows download/share. In scope: background removal, relighting/stylization, cropping to 4:5, basic usage counting (1 free/month per device), error handling, and unit/integration tests for the API. Out of scope: payment provider integration, App Store submission assets, advanced UX polish, multi-user account management, or training new models. Require robust error handling, retries for inference calls, and test coverage for the API endpoints.
How we checked
How the score was reached
- Partly verdict base52
- 3 cited sources+3
- 3/3 assessment runs agreed+4
- Evidence score59
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 · 3
Every page the run actually retrieved.
- official productSellier · De belles photos. Plus de ventes.
- official productSellier pricing and features
- official productSellier pricing and features (subscription tiers)
Integrity checks
What held up, and what did not.
