StockView uses computer vision technology running at the edge, to automatically detect gaps on store shelves. It also provides retailers with powerful insights and analytics into stock-out activities at both single-store and multi-store levels.
Powered by Microsoft Azure Stack Edge, it offers a scalable, flexible and cost-effective solution that brings the power of the Azure cloud platform down to the individual store, eliminating the need for costly and unreliable data transfers while offering a predictable and consistent TCO.
Reduce lost sales while improving customer experience
Product stock-outs lead to lost sales and have a negative impact on customer satisfaction and loyalty, yet store employees often lack visibility into stock-out occurrences. StockView’s computer vision AI provides an “always on” monitoring of store shelves to provide instant notifications to employees, letting them know when and where stock-outs are occurring.
Analyze stock-out data from single or multiple stores to understand patterns and improve processes
Retailers are typically challenged to adapt inventory levels to dynamic and localized market demands while lacking the ability to aggregate data across multiple stores to identify patterns and opportunities for process improvements.
StockView enables retailers to analyze store-level stock-out activities while also providing a variety of analytics capabilities to better understand stock-out patterns across multiple stores.
Ultimately, StockView empowers retailers to adopt a more proactive strategy to avoiding stock-outs, reducing their frequency by optimizing inventory levels and restocking actions before stock-outs occur.
Use AI running at the edge to scale across your stores in a cost-effective and predictable way
The distributed nature of retail requires a more agile, reliable and cost-effective manner in which to enable AI at-scale.
StockView leverages Intelligent Edge hardware and AI capabilities to provide inferencing power where it’s needed – in the store. Bandwidth and data transfer concerns are eliminated while costs are predictable and consistent, regardless of the scale to which StockView is deployed.