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Put self-checkout systems at the center of the retail AI revolution.

Few consumers around the world have missed the rapid expansion of self-checkout. Over 10,000 global retailers have installed self-checkout systems (SCOs), which promise to reduce retail labor costs and help customers avoid frustrating lines. According to Capital One Shopping Research, that number is expected to reach 24,000 by 2030 – and market penetration already stands at 96% within U.S. grocery stores. But there is a significant hurdle that stands in the way of self-checkout dominance: theft.

While 73 percent of consumers prefer self-checkout, with a staggering four-fold increase in shrink rate compared to staffed checkout, retailers are reevaluating the value of continued self-checkout rollout. The math is simple. Once the cost of increased theft and maintaining self-checkout areas exceed labor cost savings, it is difficult to justify keeping them around. Especially when restrictions that aim to combat theft begin frustrating the 73 percent of consumers who originally preferred self-checkout. Needless to say, this presents a significant challenge to self-checkout system OEMs.

Fortunately, the artificial intelligence revolution is underway and promises a new era of innovation and higher productivity. And self-checkout systems are no exception.

Neonode's versatile MultiSensing® computer vision platform provides advanced artificial intelligence features that address SCO pain points for retailers and end users alike. Leveraging synthetic data, anonymized data capture and best-in-class efficiency, the platform provides an advanced feature suite that runs on virtually any system – requiring only a single camera.