STOCKVIEW FOR RETAIL

Reduce lost sales and improve customer experience with AI-powered gap detection at the edge

StockView helps retailers reduce lost sales and improve customer experience by automatically detecting out of stock items on shelves.

StockView uses computer vision technology running at the edge to detect gaps on store shelves automatically. 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 (Total Cost of Ownership).

Benefits

  • REDUCE LOST SALES BY IDENTIFYING AND ADDRESSING STOCK-OUTS IN A TIMELY MANNER
  • ANALYZE STOCK-OUT DATA FROM SINGLE OR MULTIPLE STORES TO UNDERSTAND PATTERNS AND IMPROVE PROCESSES
  • LEVERAGE AI MODELS AT THE EDGE TO SCALE ACROSS YOUR STORES IN A COST-EFFECTIVE AND PREDICTABLE WAY
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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 “always-on” monitoring of store shelves to provide instant notifications to employees, letting them know when and where stock-outs occur.

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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 various analytics capabilities to better understand stock-out patterns across multiple stores.

Ultimately, StockView empowers retailers to adopt a more proactive strategy to avoid stock-outs, reducing their frequency by optimizing inventory levels and restocking actions before stock-outs occur.

StockView Architecture Diagram

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 way to enable AI at-scale.

StockView leverages Intelligent Edge hardware and AI capabilities to provide inferencing power where it is 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.

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