Earlier this year, Sam’s Club unveiled a new technology that uses computer vision and machine learning to allow customers to exit stores after the checkout process without an associate checking their receipt—a common practice at membership-only warehouse stores.
Now, the Walmart-owned chain is testing the technology at 10 locations, and there are plans to expand it to 600 by the end of the year.
But none of this would be possible without a key back-end technology known as “edge computing,” which gives individual stores the computing power to handle AI-powered functions such as seamless exit, Todd Garner, interim chief product officer at Sam’s Club, told Retail Brew.
Garner said the company started working on ways to make the exit process more seamless back in 2016, when it became clear that members were identifying it as their biggest pain point.
“As we looked at the data, we really tried to understand where our members still had pain, still had frustration,” he said. “What we found was that our exit process regularly emerged as one of the top areas of inconvenience for them.”
The launch of Scan & Go, which allows customers to scan and pay for items on their smartphones, was one solution designed to speed up the checkout process—though customers still had to present their receipts to an employee before exiting.
On the edge: The development of seamless exit technology didn’t start until late last year at Sam’s Club, in part because edge computing became advanced enough to make it possible. Garner described the tech as the infrastructural backbone of seamless exit.
Edge computing is a hybrid model of cloud computing that combines local servers (or those on the “edge” of a network) with central datacenters. Generally, the former handles the bulk of computing needs, and the latter is tapped only when necessary to minimize delays. Think of it like a backup generator in a power grid, but one that’s running all the time.
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What this means practically is that any given Sam’s Club store is packing some serious computational power. “The advancement of GPUs, or graphic processing units, has been absolutely critical to us, enabling the speed that was necessary to create that no-stop frictionless experience,” Garner said.
He explained that speed is crucial, because the whole process takes place in about three seconds, as customers pass under an archway equipped with computer vision that rapidly identifies items in their shopping cart and cross-references them with a digital receipt.
Garner added that edge computing also powers other in-store technologies such as point of sale and will be key for future technology advances as well.
Building a supercloud: The rollout of seamless exit highlights that Walmart’s new in-store technologies are underpinned by a years-long investment in back-end infrastructure. Back in 2022, the retail giant announced that it would be reducing its reliance on third-party cloud providers such as Microsoft and Google parent Alphabet by embracing edge computing.
Suresh Kumar, global chief technology officer at Walmart, wrote in a blog post at the time that the company had 10,000 “edge cloud nodes” in its network, and that the investment had saved between 10% and 18% a year in spending on cloud computing. He also stressed that new AI-powered technologies “wouldn’t be possible without cloud computing.”
“Bringing public, private, and edge clouds together in this regional approach, gives us the scale, flexibility, end-to-end visibility, and runway necessary to innovate for our customers and internal teams long into the future,” he said.