Smart retail audits
A field team checking shelves by hand, store by store.
smart retail audits
year >
industry >
fmcg
problem >
Shelf audits were manual, slow and inconsistent, and problems stayed on the shelf for weeks.
Field teams walked stores with checklists. Coverage was thin, the data was unreliable, and by the time a gap or a wrong price was reported, the sales were already lost.
what we did >
We built a mobile app where a photo of the shelf becomes a compliance report in minutes.
Computer vision counts facings, spots gaps, reads price tags and checks the shelf against the planogram. It works offline in the aisle and syncs when the connection returns.
result >
On-shelf availability is up across audited stores, and corrective action happens the same day instead of weeks later.
.
01
+11%
on-shelf availability
.
02
92%
detection accuracy
Questions
A company is AI-native when AI is part of how the product works and how the work gets done — not a feature added at the end. It changes what you build and how your team operates. We work that way ourselves, which is why we can tell you what it costs.
If you already know what to build, start with software. If you do not, start with consulting. Most companies start with a two-week assessment and move straight into a build.
One call. We look at your business, product and operations, then send a short written plan with scope, timeline and price. No questionnaire, no discovery deck.
An assessment takes two weeks. A first system usually runs in production within four to eight weeks. Larger programmes run as a monthly engagement.
Companies with a real operational or product problem — funded startups through to established mid-size companies. We are based in Portugal and work remotely across Europe.
