Suggest brand, condition and price from sellers’ photos

Second-hand platforms identify brand, condition and price from sellers’ photos

Needs setupAI Act: no extra obligationsInspecting by cameraFashion & lifestyle, Retail & e-commerce

Fits: IT & software development · Sales · Customer service

Sellers upload photos and get category, brand, condition and a price suggestion pre-filled. Listings are created faster, are more complete and more comparable, and your team mainly checks the exceptions.

Is this for you?

  • You run a second-hand platform, a buy-back service or a shop with used fashion and many one-off items.
  • Listings are often incomplete, in the wrong category or unrealistically priced.
  • You have past sales data against which price suggestions can be measured.
First step today

Photograph three to five of your own used garments with no people in the picture: front, brand label, size and care label, signs of wear close up. Use the template below to have a listing pre-filled and check what the AI recognised correctly, what it invented and what it rightly left open.

How to go about it

  1. Define listing fields and condition grades
  2. Set up photo guidance in the seller app
  3. Collect checked listings as examples
  4. Test suggestions and set confidence thresholds
  5. Build suggestions into listing and approval
  6. Evaluate corrections and complaints regularly

Templates to copy

Try it now
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Analyse
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Plan the rollout
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Included in the training

The complete guide

  • 6 steps explaining exactly what to do
  • 3 proven templates to copy into your own AI
  • Safe use: data, checking, deciding, informing
  • Pitfalls, effort and how to recognise success

With the training you get all 430 guides for as long as your access runs.

See the trainingOne-off per person, no subscription

Same approach, other use cases

24 more use cases follow the pattern “Inspecting by camera”.

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MO-07 · Legal status 08.10.2026