AI app for operations · no coding needed
Shelf Photo Stock Counter
A single photo becomes an order and a waste log with photo evidence, cutting count time and guesswork in one pass.
Made for: Operations managers at multi-site cafe groups and small supermarket chains
What it does for you
The problem
Stock counts rely on clipboards and guesswork, causing waste and stockouts.
What it gives you
Approved supplier order and waste log with photo evidence
What you give it
Shelf photosPOS sales datasupplier catalogueweekday pars
How it works, step by step
- Recognise SKUs from label text, barcode, can shape or shelf position
- Count visible units per SKU from a single photo
- Compare counts against weekday pars and POS depletion rates
- Generate a draft supplier order with quantities and suggested lines
- Flag discrepancies where stock fell faster than sales explain
- Attach the source photo to every flagged line for review
What you see on screen
- Capture queue
- stock tally
- order draft
- waste review
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Shelf Photo Stock Counter with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Shelf Photo Stock Counter with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links1 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare21 KB
- prompt-vps.mdThe same build on your own server (Docker)21 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria11 KB
- demo/index.htmlThe working demo on sample data194 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
For operations managers at multi-site cafe groups and small supermarket chains, turn shelf photos, POS sales data and supplier catalogues into a draft supplier order with a waste flag list for approval. Address the recurring problem: stock counts rely on clipboards and guesswork, causing waste and stockouts. The value hypothesis is fewer missed deliveries and less waste; the pilot must establish whether that benefit is real.
Photograph shelves, confirm zone coverage, review recognition confidence, adjust counts where needed, review draft order, approve flagged waste lines, and send the order to the supplier. Start with shelf photos, POS sales data and supplier catalogue and finish with approved supplier order and waste log.
How the AI works
Use vision models to detect and count products, and language models to match recognised items to catalogue entries. Keep counts and par values in structured fields. Validate totals and order quantities through deterministic checks. A manager reviews flagged discrepancies and the final order before it sends.
Safeguards
Limit photo capture to authorised staff with timestamps and geotags. Require manager approval before any order sends. Do not auto-order without human sign-off. Keep a full audit trail of count adjustments and approvals. The system must not delete or override par values without an explicit manager action.
What to build first
One buyer: operations manager at a three-site cafe group. One use case: dry store counts. First two modules: photo capture and SKU recognition, plus draft order generation. Manual review of all flagged lines and order totals.
What it can connect to
POS systems for sales data, supplier catalogue feeds, and email or API for order submission. Start with a CSV export from the POS and a manual supplier order upload.
The screens in detail
Use a photo grid for capture status, a SKU-level count table with confidence indicators, a draft order with line-by-line adjustments, and a waste review panel showing flagged lines with the original photo. Let users approve or edit each line. Display par, usage and discrepancy for every SKU. In this product, the first view is capture queue, followed by stock tally, order draft and waste review.
