In 2007, Alan O’Herlihy, who previously worked with large SAP facilities and retailers, set out to find a way to help retailers minimize “shrinkage,” or when a store has fewer items in stock than it has in inventory. registered. He decided on artificial vision as a solution to the problem and founded a company, never seento commercialize the technology.
Everseen, which uses computer vision to, among other things, try to prevent theft at self-checkout counters, announced today that it has raised €65 million (~$71.32 million) in a Series A round led by Crosspoint Capital Partners , a previous investor in the startup. The new funds bring Ireland-based Everseen’s total raised to nearly $90 million, which O’Herlihy says is going toward scaling the startup’s business with a roadmap “specific”.
“We are experiencing significant demand for our technology from retailers facing the double whammy of declining customer spend and increasing operating losses, including shrinkage,” O’Herlihy said. “The retail industry is also facing challenges such as labor shortages and labor cost inflation, making our technology even more valuable in addressing these issues.”
The decline in particular can be a blow to retailers’ bottom lines, to O’Herlihy’s point. In 2017, stores lost approximately 1.33% of revenue due to contraction, with an estimated total of $47 billion, according to the National Federation of Retailers.
Everseen uses a combination of ceiling-mounted cameras and computer vision software to theoretically reduce point-of-sale theft in brick-and-mortar stores. According to O’Herlihy, Everseen’s algorithms can detect and track objects (eg, SKUs) of interest, analyzing how they interact and recognizing “actions of interest” made by buyers and sales associates.
Beyond theft, Everseen claims to be able to “know” when items on a shelf are nearly out of stock and “flag processes that need immediate attention to help staff resolve issues, improve trends, and reduce variances.” Processing video of hundreds of millions of products and tens of millions of customer interactions every day, the platform can connect with a retailer’s existing tools, such as an order management system, to deliver near-time insights and analytics. real.
“All of these elements serve as input, allowing our solution to ‘nudge’ a customer to correct themselves or instruct a store associate to interact and help the customer in question,” O’Herlihy explained. . “Our goal is to stop and recover losses, enable retailer intervention, promote great customer interactions, and create seamless processes while improving the overall customer experience and positively impacting bottom line.”
Everseen has not always been successful in this mission. Workers at Walmart, once a major Eversen customer, said TechDigiPro in 2020 that the system often misidentified innate behavior as theft and failed to stop actual instances of theft.
In response to the allegations, Walmart said it made “significant improvements” to its Eversen system that resulted in fewer alerts overall. But the relationship between the two companies soured soon after. Everseen sued Walmart, alleging that the retailer had misappropriated the Irish firm’s technology and then built its own product similar to Everseen’s. (Everseen and Walmart were established in December 2021.)
It is difficult to measure the accuracy of any system without access to its backend. But history It has taught us that computer vision technology, especially technology designed to prevent shoplifting, is susceptible to bias and other failures.
Consider an algorithm trained to detect “suspicious” activity from a shopper. If the dataset used to train it was imbalanced, for example, it contained an overwhelming amount of images of black shoppers stealing, it would likely flag overrepresented shoppers more often than others.
In addition, some AI-powered anti-theft solutions are explicitly designed to detect gait on theft lanes (patterns of limb movements), among other physical characteristics. It’s a potentially problematic approach considering that disabled shoppers, among others, may have gaits that look suspicious to an algorithm trained on videos of able-bodied shoppers.
But assuming for the moment that Everseen is free from bias, there’s still the elephant in the room with every camera-based tracking system: privacy. In an email exchange, Crosspoint’s Greg Clark mentioned using Everseen’s technology to possibly capture purchase intent and behavior to “market to specific demographics”—a tricky prospect, to be sure.
I asked O’Herlihy how he treats customer data, including images he records of shoppers and store associates. He said Everseen defers to clients on data retention policies and, for what it’s worth, is “fully compliant” with GDPR.
Whether buyers, or partners, trust Everseen implicitly is another matter. But potentially thorny ethical issues don’t seem to deter customers from signing up for the startup’s services.
O’Herlihy says Everseen counts more than half of the world’s top 15 retailers among its customers, with deployments in more than 6,000 retail stores and over 80,000 checkout lines.
“The speed of adoption of this transformative technology increased during the pandemic as retailers looked for different ways to sell and shoppers looked for different ways to buy,” O’Herlihy said. “In terms of technology spending, we’ve seen a reallocation of budgets as challenges for retailers evolve, and addressing shrink is seen as a top priority in the industry…Everseen aligns squarely with current trends.”
In a general sense, it is true that retailers are embracing, or at least showing interest in, AI. TO recent KPMG’s survey found that 90% of retail business leaders believe their employees are ready and have the skills for AI adoption, while 53% agree the pandemic has increased their company’s pace of adoption .
Going forward, Eversen, no doubt under pressure from rivals like AI Guard and VaakEye – plans to expand its technology to sectors beyond retail, such as supply chain and manufacturing. The startup currently has around 1,000 employees at its headquarters in Cork, as well as centers in the US, Barcelona, India, Australia, and elsewhere.
“Starting with retail allowed Everseen to develop both a foundation and a library of computer vision AI use cases that are relevant to other adjacent industries,” O’Herlihy said. “Computer vision solutions are currently very siled and are aimed at solving specific problems. We are seeing increased demand for our platform as customers look to solve other problems across the retail store property.”