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This AI Tech Catches Shoplifters Before They Even Steal Anything

Veesion claims its system does not require the use of biometrics or the storage of personal data to pinpoint potential shoplifters.

This AI Tech Catches Shoplifters Before They Even Steal Anything
Veesion flags suspicious movements to store security.
  • Veesion's AI algorithm predicts potential shoplifting by recognising suspicious gestures in real time
  • The technology is deployed in 5,000 stores across Europe, Canada, and the US
  • The system works without biometrics or storing personal data and sends alerts via a mobile app
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A Paris-based artificial intelligence (AI) startup has developed an algorithm that can predict if a potential shopper is trying to steal items. Veesion claims to recognise gestures that can predict potential retail theft incidents, thereby preventing shoplifting from happening in the first place.

As per the company, its AI-powered technology is currently deployed in 5,000 stores across Europe, Canada and the US, having raised Rs 373 crore ($43 million) in a Series B funding round recently to further expansion.

Founded in 2018, Veesion says traditional surveillance systems offer little in the way of prevention, leaving most CCTV footage unwatched due to a lack of staff or resources. While big e-commerce firms have real-time analytics for fraud protection, the brick-and-mortar shops continue to lag.

"I happen to have an uncle in Paris that runs and operates three supermarkets, so I exactly know what shoplifting represents for retailers," Veesion cofounder Benoit Koenig told Business Insider.

Veesion claims its system does not require the use of biometrics or the storage of personal data to pinpoint potential shoplifters. The system integrates into existing store setups and is controlled through a mobile app that delivers real-time alerts to staff.

"The algorithm doesn't care about what people look like. It just cares about how your body parts move over time," Mr Koenig said.

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Deterrent for shoplifters

The system analyses the security footage, detects the shoppers, identifies their movements and recognises various objects such as merchandise, carts, baskets or bags. If a certain movement, such as unusual product handling or concealment, is deemed suspicious, the video clip is flagged and sent with additional details to the security team.

As per Mr Koenig, one of his US clients was able to cut their losses from the health and beauty section in half in the first three months of implementation. He added that the tech developed by his company can also help reduce employee theft, which is estimated to cost retailers as much as shoplifting does.

"It has an internal deterrent effect. They know there is an AI in the cameras, so they're going to be careful with what they do."

The company added that implementing the technology can also help reduce staffing needs as the entire process is automated.

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