Retail / CPG
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Computer vision captures shelf reality across every store. AI scores deviations by dollar impact and routes corrections to the floor, so your team works on the gaps that cost the most.
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Most retailers cannot verify whether stores actually execute them. Manual audits sample a fraction of shelves days after a reset, and the gap between the plan and the shelf is where margin leaks. CINDE Store Intelligence closes that gap with three connected capabilities.
Computer vision captures shelf conditions across stores, replacing manual walks and spot checks. You see compliance scores by store, category, and section without waiting for the next audit cycle.
Not every deviation costs the same. AI scores compliance gaps by the revenue and margin at risk, so store teams fix the highest-value problems first instead of working through a generic checklist.
Shelf execution data feeds back to the assortment and space planning teams that built the planogram. When the same deviations repeat across stores, you fix the root cause in the plan, not just the symptom on the shelf.
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Computer vision captures shelf conditions at store level and scores deviations by financial impact. Instead of periodic manual audits that sample a fraction of the shelf, AI monitors continuously and routes corrective tasks to the floor, prioritized by the revenue at risk.
On-shelf availability measures whether a product is present and buyable. Planogram compliance measures whether products are in the right position, with the right number of facings, in the right sequence. A shelf can be fully stocked (high availability) but completely out of compliance with the merchandising plan.
Store associates or fixed cameras capture shelf images. Computer vision identifies every product, its position, and its facing count, then compares against the planned planogram. Deviations are scored and routed as tasks. This replaces the manual walk-and-checklist process, covering more shelves with higher accuracy and lower labor cost.
CINDE works with mobile capture. Store associates use a handheld device to scan sections during routine shifts. No fixed cameras, no WiFi dependency, no construction required.
