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Today, 97% of food shopping in America takes place in brick and mortar grocery stores.  Meanwhile, the leading complaint about grocery store shopping is excessively long lines at checkout.  In fact, the checkout experience has not been successfully updated since the introduction of the barcode reader over forty years ago.  Grabango’s mission is “to eliminate lines and save people time.”  We are honored to be fulfilling our mission and providing even more value with our newly announced retail partner, Giant Eagle Inc.    

Grabango’s platform has been deployed at a Giant Eagle retail location, and together we are optimizing the system in preparation for commercial service.  This partnership represents the first checkout-free technology partnership for a large grocery retailer (Top 20 U.S. Grocer according to Progressive Grocer, May 2019) for existing store locations in the United States.

Giant Eagle is an ideal development partner for multiple reasons.  First, the range of store sizes under one banner (3,000 sq. ft. GetGo convenience stores to Market District supermarkets > 100,000 sq. ft.) makes for an ideal proving ground for Grabango’s enterprise-class technology.  Second, Giant Eagle’s accomplished technology team firmly controls the technology that operates in their 474 retail locations and is capable of rapid deployment throughout the operation. These facts, in combination with both teams’ focus on improving the shopper experience, make Giant Eagle an ideal business partner. 

At the industry level, this announcement is not only an important first but a harbinger of many announcements to come in the retail-tech industry.  True, checkout-free technology eliminates lines at checkout, and it also unlocks a variety of customer-oriented, loss prevention, safety, merchandising and operational efficiency applications as well.  Grabango collaborates with its clients to thoughtfully apply technology to promote superior shopping experiences and a safer workplace that facilitates more store associate-to-shopper interactions.  

According to a recent Gallup Survey of 1,033 Americans, 81% of respondents shop in a grocery or other similar store at least once per week.  When considering the time savings and convenience potential for all of these shoppers, it’s easy to understand why so many of us are excited about introducing checkout-free technology to shoppers around the world. Today’s announcement was an important first step to achieving that vision and we could not be more excited about taking it with Giant Eagle.


PITTSBURGH, PA – July 16, 2019 — Today, Giant Eagle, Inc., one of the nation’s leading food, fuel, and pharmacy retailers, and Grabango, the leading checkout-free technology provider for existing brick-and-mortar stores, announced a first-of-its-kind partnership designed to create a no-wait checkout experience.

By partnering with Grabango, Giant Eagle strengthens its commitment to continually invest in the latest forward-thinking technologies to enhance the shopping experience for customers. Grabango’s enterprise-class platform is designed to operate across Giant Eagle’s multi-format footprint with checkout-free technologies providing the flexibility that Giant Eagle greatly values.

According to a recent study conducted by Forrester Research, waiting in the checkout line is the top complaint among US grocery shoppers. Giant Eagle and Grabango hope to provide a remedy for this consistent pain point through their frictionless solution.

With Grabango’s checkout-free technology, customers will enter the store and immediately start shopping as they normally would – without any hurdles, such as turnstiles or costly memberships. The more advanced checkout-free system automatically keeps a running total of the items each shopper selects.

Grabango’s platform has been installed at a pilot Giant Eagle location and multiple executions of the payment technology are being optimized, including an app-based solution and another that allows the customer to pay with any tender they choose. The solution does not use facial recognition technology but instead utilizes computer vision and machine learning to track shopped items. All data is anonymized to protect customer privacy.

“Giant Eagle is committed to advancing technologies that create an improved, stress-free shopping experience for our customers while still protecting their privacy,” said Giant Eagle’s Director of Corporate Communications, Dan Donovan. “In Grabango, we have found a partner who shares our commitment and who can help us bring this enhanced experience to life.”

“Giant Eagle has been a fantastic partner on this groundbreaking project,” said Will Glaser, Grabango’s CEO. “We are excited to be announcing our first checkout-free partnership with a major U.S. retailer. Together, we are offering a technology that is seamless and equitable for all.”

About Giant Eagle
Giant Eagle, Inc., ranked among the top 40 on Forbes magazine’s largest private corporations list, is one of the nation’s largest food, fuel and pharmacy retailers with approximately $8.9 billion in annual sales. Founded in 1931, Giant Eagle, Inc. has grown to be a leading retailer in the region with more than 460 stores throughout western Pennsylvania, Ohio, northern West Virginia, Maryland and Indiana.

For more information, visit www.gianteagle.com.

About Grabango
Grabango is the leading checkout-free technology service provider for existing, large scale stores. Grabango delivers a next-generation shopper experience and is the only enterprise-class, checkout-free solution on the market today. The Grabango platform includes a fault-tolerant, edge computing network that accurately processes millions of simultaneous transactions. The system places no limits on who can enter the store, what can be sold there, or how the shelving is configured.

Grabango was founded in 2016 by Will Glaser, former CTO and co-founder of Pandora Radio. The company has raised $18M to date from top venture capital firms and is headquartered in Berkeley, CA.

For more information, visit www.grabango.com.


Computer vision has long been just an esoteric field hidden at the depths of academic research. Scientists toiled to create mathematical algorithms that could extract meaning from the grid of light and dark pixels that make up an image. How can people look at these pixels and so easily distinguish between a cat and a toaster?

It’s easy to tell these images apart even though they’re both made up of nothing more than gray squares.

Recall that each pixel conveys nothing more than a single color; still, millions of them are generated by your phone’s camera every second. The combination of these pixels can describe literally anything the camera sees. Even a child’s eye can trivially integrate them to identify objects, but teaching a computer to do the same had been a significant computational challenge. Now that computers can see, the way people interact with things will never be the same.

Over the past decade, advancing computer platforms have finally unlocked the power in these techniques to catapult computer vision into the vanguard of modern societal change. Synergies at the intersection of machine learning and computer vision are the foundation upon which a major leap in technological capability is happening. The coming revolution will be as transformative as any we’ve seen so far.

Reaching “Peak Screen”
In the early days of computer science, only nerdy programmers used computers. Then, the invention of the application program welcomed in a broad range of business analysts, word processors, and video gamers. The always-on mobile internet, with its wide array of consumer products and everyday benefits, has finally brought the computer revolution to everyone. We love it so much that we’ve surrounded ourselves with more screens than any of those early users could have ever imagined. We interact with them at home, at work, in our cars, our pockets, and on our wrists.

The typical American spends 11 hours per day looking at a screen.
Image Source: Getty Images

We have reached the point of “peak screen” where screens are virtually always present and demanding our attention. Why so many? Because all these interfaces are necessary to communicate with our computers. Computing is such an integral part of how we conduct our everyday lives that we don’t realize how much time we spend telling our machines what to do, what we want, or what we just did.

Fortunately, the easing of this communication burden has already begun. It was led by early machine learning companies like Nest and Pandora. We no longer need to decipher the maddeningly complex programmable thermostat or painstakingly assemble the ideal playlist. I can simply say I want it a bit warmer right now and that I’m loving a particular song and appropriate algorithms hear me and adjust. These systems not only take literal action in the moment but go on to generalize my intent to improve the experience for me overall. Iterate a few times and life is good. The learning aspect of these systems allows them to intuit what I want without forcing a heavy burden to instruct them in detail. Greater meaning is conveyed through fewer instructions, which is undeniably a welcome advance.

Operating in the Background
Computer vision is accelerating this process. With it we’ll simply go about our lives, doing what we like, and the computers will quietly keep track. We’ll no longer need to instruct them affirmatively about what just happened because they’ll have seen it at the same time we did; and more importantly, be able to understand our intent. As computers can see more for themselves, the need for all those screens, keyboards, and indicator lights will recede.

Will it be difficult for us to adapt? No, these computer vision systems are passive; and inherently easy to use. Precisely because there’s no need to instruct them, there’s similarly no need to learn how to use them. Each of the last technological revolutions forced us to learn the new tools, to adapt to the new world, and to remake ourselves to fit in. This one is different, delightfully different. We’ll just do what’s natural and vision-based systems will manage the details.

The Rise of Automation
One common example of public automation is toll roads. Since the turn of the century, many toll booths across the country have been replaced by automated systems that “see” people drive by and understand that their intent is to use the road and pay the toll. This freedom would have felt impossible 20 years earlier but is now accepted and taken for granted by millions of motorists each day.

Automation will bring efficiencies to many parts of our everyday lives as computers fade into the background.
Image Source: Getty Images

Another example is the one that I work on, Checkout-Free Shopping. It uses computer vision to see what goes into your shopping cart so the cashier can know what to charge without having to scan every item’s barcode. Like with toll roads, this offers the consumer enormous savings in time and convenience. Much hyped, but probably still five to ten years away, are driverless cars. Also coming are automated parking meters, ticketless amusement parks, high-accuracy medical uses, and numerous industrial applications. Each has, or soon will, make our lives better and then quickly be taken for granted. Adoption will be swift as these systems simplify the experience by fluidly handling the technical bits.

New Freedom
Now that computers can see, the way people interact with things will never be the same. We are about to be freed from waiting in line, manually operating machines, and constantly entering obvious things into a computer. Past advances in computing have unsurprisingly led to more computers doing more things for us. Machine learning and computer vision is a part of that trend of increasing capability and will similarly lead to computers doing increasingly more. The ironic difference this time is they will not stand in front, demanding our attention, but in the background where they belong. We will be freed to interact as people and let the computers do the computing. This revolution will remove many of our screens and facilitate the rehumanizing of society.


Berkeley, Calif. – March 4, 2019 – Grabango, the leading checkout-free technology provider to existing brick-and-mortar stores, announced today that it has successfully migrated from Amazon Web Service (AWS) to a multi-cloud architecture with Microsoft Azure and Google Cloud Platform (GCP). The move responds to feedback from Grabango’s three Top 30 Grocery and one Top 10 Convenience Store customers that require strategic cloud connectivity that does not result in new revenue for competitors.

See full press release

Grabango’s customers are sophisticated companies that, in many cases, have already adopted multi-cloud strategies. This system architecture meets retailers’ load-balancing and uptime maximization objectives. Grabango’s own research shows that large retailers strongly prefer enterprise class technology solutions that provide these redundancy options.

“We listen carefully to our customers’ needs and invest in developing the most reliable solutions,” said Will Glaser, Grabango Founder and CEO. “The call to migrate off AWS and provide multi-cloud interconnectivity with their stores was clear and universal. This move further reduces risk and, we hope, shows our customers and potential customers alike that we listen and will act quickly to align with their priorities.”

Azure and GCP are industry leaders for reliability and embedded application functionality. Grabango constantly monitors its cloud vendor network and their price performance to provide the best service possible. Being multi-cloud builds further redundancy into Grabango’s platform while maximizing value for its corporate customers.

About Grabango

Founded in 2016, Grabango is the leading provider of checkout-free shopping technology for existing stores. Grabango technology delivers a next-generation shopper experience and is the only enterprise class checkout-free solution on the market today. The Grabango platform includes a fault tolerant, edge computing network that accurately processes millions of simultaneous transactions. The system places no limits on who can enter the store, what can be sold there, or how the shelving is configured.

See full press release

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