Smart Shelf Vision for Retail Analytics
Industrie- Manufacturiig Germany Berlin
Problem to Solve
A regional retail chain approached orionic with a recurring challenge: frequent stock misplacements and empty shelves in their stores led to lost sales and poor customer experience. Manual shelf checks were time-consuming and inconsistent, especially during peak hours, making it difficult for store managers to maintain accurate real-time visibility of inventory on the shop floor.
Our Solution
The orionic AI team developed a lightweight computer vision system capable of monitoring product shelves using standard in-store security cameras. The system was trained to detect empty spaces, misplaced products, and pricing label errors without the need for specialized hardware. Through a simple dashboard, store employees received instant alerts whenever a product was out of stock or incorrectly placed. The system was integrated with the retailer’s existing inventory management software, automatically triggering restocking requests and updating real-time availability data. By deploying the solution on the retailer’s local edge devices, orionic ensured full GDPR compliance and data security, avoiding the need to store or transmit customer images to the cloud.
Results & Effects
The pilot deployment across three stores demonstrated a 30% reduction in restocking delays and a 15% increase in on-shelf product availability. Store managers reported that the solution simplified daily operations and allowed staff to focus more on customer service rather than manual shelf monitoring. This project illustrated how a practical, cost-efficient computer vision system can deliver measurable business value - bridging AI innovation with tangible operational impact in everyday retail environments.