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The Spoon

Daily news and analysis about the food tech revolution

AI

Sony Sets up AI Unit to Work on Food

Sony announced this week that is has launched Sony AI, a new organization that will research and develop artificial intelligence specifically for games, imaging and sensors, and “gastronomy.” The new initiative will have offices in Japan, Europe and the U.S.

There aren’t many details around what exactly Sony will be working on, but Sony spokesman Shinichi Tobe told AlJazeera yesterday that “AI and robotics will not replace chefs. We are aiming to offer new tools to expand their creativity with AI and robotics.”

This isn’t Sony’s first foray into food. In April of last year, Sony teamed up with Carnegie-Mellon University to work on food robots. As we reported at the time:

Sony said they were starting off with food-related robots because the complexities involved with food could later be applied to a wider range of industries. Specifically, it cited the ability to work with fragile and odd-shaped materials, as well as the ability to operate a robot in small spaces.

AI and robots are like peanut butter and chocolate with AI being the “brain” for the robot “hands.” Things like computer vision, deep learning and synthetic data help form the AI so the robot can determine objects to grab and manipulate, etc..

Sony’s motivations may also be more societal in nature as the company’s home country of Japan is facing an aging population. Robots and other forms of automation could help with a potentially diminished labor force.

Food is a popular subject for robotics and AI researchers. Nvidia’s Lab in Seattle built a kitchen to train its robots to do everyday tasks. IBM partnered with spice company McCormick to use AI to develop new food products. And Korea’s Woowa Bros. hooked up with UCLA to work on food robots as well.

Something tells me we’ll be seeing more of these types of deal throughout next year.

French Nutritional Coaching App Foodvisor Raises $4.5M

Foodvisor, a nutrition assistant app that aims to help people eat better, announced today that it has raised $4.5 million from the VC fund Agrinnovation (operated by Demeter) along with other angel investors. With this round, Foodvisor has raised $5.3 million to date.

Foodvisor creates an AI-powered food diary that allows users to keep track of what they eat. The app uses a combination of computer vision and deep learning so that all a user need do is snap a picture of the food they are eating. Foodvisor can then identify the food on the plate, serving size and create a detailed nutritional report. Foodvisor says its app can identify 1,200 different food items and is constantly learning new ones.

The company says it will use the new money to accelerate growth in the United States where, the Foodvisor CEO makes a point to say in the press announcement emailed to The Spoon, that “70% of the Americans are overweight or obese.” Foodvisor says that currently 20 percent of its user base comes from the U.S.

They say that you lose weight in the kitchen and get fit at the gym. Keeping track of what you eat is a good first step for anyone looking to shed a few pounds and get healthier. Foodvisor isn’t the only app that uses your smartphone camera to help make food journaling easier. Bite.ai offers a free consumer app as well as an API that other business can tap into to for similar food recognition services.

Foodvisor offers a free app for iOS and Android as well as premium version that offers more personalized advice and recommendations for a monthly subscription that costs from $4.99 to $6.99.

Will Steve Easterbrook’s Departure Slow Down McDonald’s Tech Initiatives?

McDonald’s has fired CEO Steve Easterbrook after he engaged in a consensual relationship with an unnamed employee. The board voted on Friday to remove him, according to the Wall Street Journal. McDonald’s USA President Chris Kempczinksi was named the new CEO, effective immediately.

According to the WSJ, Kempczinksi noted he would maintain Easterbrook’s focus on tech, saying, “There isn’t going to be some radical strategic shift. The plan is working.”

Clearly, no sane executive in 2019 would reverse course on technology initiatives that could speed up and simplify restaurant operations while also meeting demand for delivery, convenience, etc. For McDonald’s, however, this executive shakeup could certainly slow the pace of change.

Under Easterbrook’s tenure, McDonald’s pursued an aggressive strategy around technology. In the last year alone, that included the acquisition of Dynamic Yield and subsequent rollout of the latter’s AI technology at McDonald’s drive-thru, buying up voice-tech startup Apprente and building a new tech innovation lab, expanding delivery with more third-party partners, and a heap of other developments that seem to land in the inboxes of us reporters every other day.

All this and more is part of McDonald’s Experience of the Future mandate for stores, an initiative that requires franchisees to update their store designs, invest in tools like self-order kiosks and new menu items (e.g., fresh beef), and curbside pickup.

Not surprisingly, McDonald’s franchisees have pushed back at these costly but not necessarily profitable changes. A recent Bloomberg article noted that “[Franchisees] object to the enormous costs of the project, which, for owners of several locations, can run into tens of millions of dollars, even with McDonald’s offering to subsidize 55 percent of the capital for the remodels.”

About a year ago, a group of U.S.-based McDonald’s franchisees formed the National Owners Association advocacy group to address some of these challenges. For example, franchisees were originally required to have their locations remodeled by 2020, a date that, after enough outcry, was pushed back to 2022 (albeit with caveats).

Easterbrook’s departure won’t stop tech innovation at McDonald’s. Nor should it. And to be clear, no one has officially yet stated any specific changes to the strategy. But the conversation around franchisee tensions has only grown louder in recent months, and under Kempczinksi’s leadership it’s possible McDonald’s could slow its pace on some of these developments or give franchisees more say in how to implement some of these initiatives without incurring some of their heavy costs. Meanwhile, McDonald’s has to somehow address its sluggish sales while still maintaining its edge over other QSRs, who are rapidly deploying self-order kiosks, AI in the drive-thru, and other high-tech solutions. Whether the chain can do that more effectively under Kempczinksi looks to be yet-another unanswered question in this ongoing McSaga.

KFC Hints at AI, License Plate Recognition for Drive-thrus

KFC is exploring technology that would automate the process of ordering and upselling items in the drive-thru, according to an interview the chain’s U.S. Chief Technology Officer Christopher Caldwell did with Nation’s Restaurant News this week. KFC’s strategy looks to be focused on AI technology similar to that of McDonald’s, whose digital menu boards speed up ordering and automatically recommend items to customers.

The news comes on the heels of KFC’s little-publicized launch of an in-house online ordering platform, which happened earlier in October and is clearly part of a larger push from the Louisville, KY chain to increase efforts around the digital restaurant experience.

While Caldwell said the new native online ordering platform is “exceeding expectations” in terms of customer response, improving and innovating on the drive-thru is crucial for KFC.

That’s hardly surprising. Speed of service at the drive-thru in general has steadily gone down over the last decade, with the average time in 2019 a good 20 seconds longer than the previous year. But drive-thrus still account for a huge percentage of sales at QSR chains. For KFC, they account for about 65 percent of sales, according to Caldwell. Using automation in the drive through could potentially minimize both mistakes that happen during the order-taking process in the drive-thru as well as the length of time a customer spends waiting.

Caldwell also said drive-thru technology could bump up check averages thanks to better personalization and suggestive selling — one of the key benefits McDonald’s has been touting with the Dynamic Yield AI technology it’s rolled out to thousands of drive-thrus of late. He also hinted at license-plate recognition in the future, where the system can scan a customer’s plate and immediately suggest that person’s favorite meal.

A number of other QSRs are now testing new technologies and methods to speed up service in the drive-thru. Chains like Dunkin’, Krispy Kreme, and Chipotle are adding lanes for mobile-only orders. Sonic piloted AI-powered menu boards earlier this year. Meanwhile, companies like 5thru and Valyant AI are partnering with QSRs to automate more of the process through AI.

KFC hasn’t actually deployed any of this technology to actual stores yet, though Caldwell told NRN that “there’s going to be no shortage of [KFC] franchisees that want to adopt and be a test partner” when that finally happens.

SKS 2019: Think of AI as Augmented Intelligence, and is the Future Just-in-Time Farming?

Artificial intelligence (AI) is a vague, slightly tech-y term that is overused by marketing departments trying to show some bona fides. But if you want some real insights on what artificial intelligence is and what it can do, then you should check out these talks that Chris Satchell of Zume and Erik Andrejko of Evolv (the venture arm of Kraft-Heinz) each did onstage at our recent Smart Kitchen Summit.

But before you can begin talking about AI you must understand the importance of data. Not just plenty of it or the right kind, as Satchell points out in his presentation. Before you can get into algorithms you need clean, tagged data that is centralized. He recommends that you don’t spread out your data teams across the company, and instead cluster them together to get the best results.

With your data organized and your models in place, then you can start to analyze and gain insights. For Zume, that means making the food supply chain more efficient. When we talk about last mile delivery, we’re actually talking about the last five or seven mile delivery. Zume is using predictive analytics to know ahead of time what food will be ordered, when and where. From that information they can place mobile kitchens directly in those neighborhoods to make the delivery process more efficient for the cooks, the couriers and the consumer.

Satchell wants to take this type of AI-based prediction up the food stack to improve supply chains and even create predictive farming. This type of just-in-time farming would help farmers understand what types of crops to grow and when in order to help reduce food waste.

As Andrejko pointed out in his talk, agriculture is already changing thanks to analytics and AI. Though Andrejko would like people to think of AI as “Augmented Intelligence,” not “Artificial Intelligence.” On the farm, this means that data and algorithms can be used to optimize how fertilizer is applied, using more on acres that need it and less where it doesn’t. Or with emerging fruit-picking robots that can use computer vision to automatically harvest at peak times for ripeness.

Andrejko also sees augmented intelligence at our kitchen tables, giving us more human connection at dinner time. Say you want to cook a butternut squash chili for dinner. Eventually you’ll be able to say that request to a voice assistant, which will break down the list of ingredients and place the order, which will be brought to your house via a self-driving delivery vehicle, which also uses AI to travel to your door.

These talks, along with the panel discussion with Satchell and Andrejko afterwards, are great deep dives into AI for anyone curious about the trendy term or for any company looking to add that arrow to their quiver. At least have the marketing department in your life check it out.

SKS 2019: How AI Will Reshape Food Markets

Domino’s Innovation Garage Doubles Down on GPS Tracking, Driverless Cars

Domino’s has wasted no time in ramping up its innovations since opening the doors on its Innovation Garage in August. And at an event held at the facility this week, the pizza chain-turned-tech company highlighted a couple of the top innovations it is currently working on.

Nation’s Restaurant News, who was at the event, reported on these developments, which are geared towards getting pizzas to customers’ doorsteps as fast and as seamlessly as possible.

GPS tracking technology topped the list of developments the company is working on. Earlier this year, Domino’s started testing its system that lets customers and stores track drivers in 27 company-owned locations around Phoenix, Arizona. The system allows customers to see their driver’s progress on a map and receive a notification when their pizza is just a couple minutes away. Store managers can also track drivers via a screen inside the store. Domino’s has said it will roll out this tracking technology to all U.S. stores by the end of 2019.

At the Innovation Garage this week, the company wouldn’t give data on how much GPS tracking improves the pizza delivery experience, but said Domino’s locations are seeing improvements and that more of them are adopting the technology.

Speaking of cars, the company also said at the event that it has finished its testing of autonomous delivery in Houston, TX, and is ready to officially roll the program out in that city. Domino’s piloted driverless delivery this past summer, teaming up with a company called Nuro, who makes a fully automated, low-speed vehicle about half the size of a regular car.

With Nuro, customers who select the “autonomous” option when ordering a pizza use a PIN to unlock the car when it arrives and retrieve their pizza.

For now, autonomous delivery via Nuro will be concentrated on the downtown Houston area. Domino’s didn’t say whether a larger rollout is planned for other parts of the city or the U.S. However, highlighting the struggles around rising labor costs and the struggle to find enough drivers, Domino’s Chief Digital Officer Dennis Maloney said at the event, “This is the future of our company.”

SKS 2019: IBM and McCormick Use AI to Make the Best Possible Barbecue Chips (and More)

Say you’re developing a new barbecue potato chip. You’re using spices from McCormick, which has not one, not two, but over 100 types of garlic flavoring. How do you decide which garlic(s) to use, and in which combinations, to make the best product for your target demographic?

That’s where artificial intelligence (AI) can help. Last year, McCormick, the largest flavor company in the world, went public with its five-plus-year partnership with IBM to build a flavor platform using machine learning. We dove deep into this partnership at SKS 2019, when The Spoon’s Chris Albrecht spoke with McCormick’s Chief Science Officer Hamed Faridi and IBM Principal Researcher Richard Goodwin about how AI can help make better, tastier products in less time and with fewer dead ends.

Check out the video below to watch the entire panel (it’s super nerdy and cool).

Hamed Faridi on the SKS 2019 stage. (Photo: The Spoon)

To whet your appetite, here’s a quick overview of what Faridi and Goodwin discussed in the session.

“The [CPG] iterating process is a very time-consuming, old system,” said Faridi during his onstage presentation. “But that’s the only thing the industry has.” All of that changed when Faridi was driving home and heard an NPR interview with a scientist from IBM’s Chef Watson, a program that develops bepsoke recipes based off of chemical flavor affinities (for example, leeks and chocolate.) Immediately, he was struck: this was the missing piece of the puzzle to develop better products in a smarter way.

Computers can’t taste or smell, so how do they know which flavors taste well together? That’s where data comes in. McCormick has kept all of its data from various flavor development processes and product experiments since the 1980s. IBM’s machine learning algorithms can take those data points and make suggestions about new ingredient combinations without having to go through all the trial, error, and staff training that a human R&D team requires.

The result is a 70 percent reduction in product development time and increased stickiness in the market. Faridi said that the IBM partnership is working so well they expect all of their labs will be using AI by late 2021.

This session was a fascinating look into how a flavor giant and a technology giant have teamed up to make better everyday products. Watch the full video below and get ready for more SKS 2019 content coming your way over the next few weeks!

SKS 2019: Case Study: McCormick & IBM Build an AI-Powered Flavor Platform

Spoonshot Launches its AI-Powered Crystal Ball for CPG Companies, Makes an Ashwagandha Prediction

If you’re in the consumer packaged goods (CPG) business and see a food trend popping up on Instagram or Snapchat, then you are probably already too late to act on it. At that point your company is reacting to what is already happening, rather than what will happen.

This is one of the main drivers of Spoonshot‘s new AI-powered flavor recommendation platform, which the company announced today. This online tool promises to combine data science, machine learning and food science to predict flavor combination trends and provide inspiration for new products for CPG companies.

According to the press release:

“…[Spoonshot’s] platform analyzes billions of diverse data points from over 900 sources in the domain of food. The technology focuses explicitly on long-tail data as stronger signal indicators of future trends are detected in this data. The types of data processed include scientific research, food communities, niche ecommerce portals, media platforms, and data on more than 7.8M CPG products, menus, and recipes.”

We got a chance to try out the new platform, which lets you search through three broad categories: Ingredient Networks, Startups Explorer, and Trend Trek.

Ingredient Networks lets you search ingredients for recommended flavor combinations and pairings. For example, when you search “banana,” it brings up what might be considered unusual recommendations like coffee concentrate and sunflower seed butter. But remember, what Spoonshot wants to do is surface flavors you probably haven’t considered. So bringing up something like chocolate or strawberries would be useless because you already know about them.

As such, each result in the Ingredient Networks search comes back with a novelty score, to tell you how widespread the flavor combination is already, as well as a flavor label to tell you how well those flavors go together based on food chemistry. It also shows you which products already use that flavor combination and any health claims like “gluten free.”

The Startups Explorer flips the search equation and lets you browse through the existing products, menus and recipes in its database to see what flavor combination are already in use.

Though Spoonshot developed this platform for primarily North American use, the Trend Trek feature will eventually allow you to take a trip around the world and pick a country to see what products and flavor combinations are popular elsewhere. Right now it only lets you “visit” Singapore, the UK and the United Arab Emirates.

As part of today’s announcement, Spoonshot said that its AI has created the blueprint for a new product, “an Ashwagandha (Winter Cherry) wellness drink, flavored with Jasmine Flowers.” This combination, the company says, is driven by consumer interest in the power of adaptogens to reduce stress and improve sleep. The company also released a report on how fruit and vegetable peels are an area, err, ripe for new uses and innovation.

Spoonshot has already been working with 40 companies during its closed beta, 15 of which the company says are billion dollar-plus businesses, including Cargill. Spoonshot offers access to its platform through different subscriptions at price points that the company did not disclose.

Using AI to power food recommendations is actually becoming a pretty crowded category. Other players in the space include Analytical Flavor Systems and Tastewise (which also predicted functional foods as an emerging area for CPG companies to focus on).

With all these options, I predict big CPG companies really won’t have an excuse for not getting ahead of the next big food trend.

FutureProof Retail to Add AI-Based Grocery Recommendations From Halla

FutureProof Retail, which provides mobile checkout technology for grocers, announced today that it will incorporate Halla’s AI-based product recommendations into its service.

FutureProof Retail uses mobile phones to create a line-free checkout process for supermarkets. Unlike other cashierless checkout solutions that install cameras and use computer vision to identify what you purchase, FutureProof moves everything to a whitelabeled app from the retailer on your phone. You scan barcodes to add items to your cart, and when you’re done, you hit a checkout button and a store employee does a quick check of your bag to make sure you aren’t shoplifting. You can see it in action in this video:

Express Checkout El Rancho Awareness Video from FutureProof Retail on Vimeo.

With today’s announcement, when people scan an item Halla’s recommendation engine will kick in to suggest a complementary product right there on the phone’s screen. So if you scanned a bag of Tostito’s chips, the app would recommend salsa. But Halla’s recommendations are also dynamic and adapt as you shop. As we wrote when the company raised $1.4 million in May of this year:

…if you are using a grocer’s app with Halla I/O built in, the app will serve up intelligent recommendations as you continue to shop online. Buy salt, it could recommend pepper. By salt and noodles and beef, and it might guess that you are making a bolognese and recommend tomato sauce.

Halla developed its recommendations based on data from anonymized grocery transactions to see what items are typically purchased at the same time, as well as restaurant and menu items (menu descriptions are, after all, typically a list of ingredients). Halla had initially started off making recommendations for restaurants as well, but pivoted away from that to focus on grocery.

It’s important to note that Halla will only provide one recommendation per item. “As of today our recommendations are focused on complementary products with one goal in mind, what is most likely to be purchased,” Halla Co-Founder and CEO, Spencer Price, told me by phone this week. Price said that this focus on a single product is important because shopping is a very emotional experience for people, and one that can’t be junked up with lots of pop-ups on a phone screen with lists to scroll through.

FutureProof works with Fairway Markets in New York and other regional grocery chains, though Price was unable to provide a timeline or location for where its recommendations will go live through this partnership.

Almost as important as the news itself is the fact that FutureProof has publicly named Halla as a partner. There are other AI-based food recommendation engines out there like Spoonshot and Analytical Flavor Systems, but they are pretty quiet about their clientele.

I’m not fully convinced about the broad adoption of FutureProof’s cashierless implementation. Manually scanning products and having a human check your bag before you leave a store seems to bring friction into a process that is supposed to be frictionless. Regardless, for those who do use it, FutureProof’s app requirement seems like a good vehicle for Halla’s technology because of its immediacy and visual cues. I imagine the company will look towards announcing partnerships with smart shelf displays like AWM Smart Shelf in the near future.

McCormick’s Hamed Faridi on How CPG Giants Can Leverage AI and Data to Stay Nimble

Anyone else remember having to rummage through the deep, dark recesses of your spice cupboard in search of a bottle of peppermint extract, or maybe some “rubbed sage”? That’s where the McCormick brand has lived for most of my life.

Which is why it’s so interesting to see the spice giant branching out to leverage AI and data to create new flavors, personalized spice blends and even a grill that plays music based on what you’re cooking. That’s a hell of a leap from taco-seasoning packets.

This new tech-y push is led by Chief Science Officer Hamed Faridi, who will be at the Smart Kitchen Summit (SKS) with Richard Goodwin, IBM lead researcher, discussing their recent collaboration and AI-powered flavor platform. We emailed Faridi a few early questions because October was too long to wait. (Buy your SKS tickets now, they are going fast!)

This interview has been lightly edited for clarity and grammar.

Lately McCormick has been combining flavor and AI, for example through its Flavorprint service and its partnership with IBM. Do you think this combination is a trend we’ll see more of?
Flavorprint service is provided by the Vivenda Corp. McCormick AI is currently under development via a partnership with IBM Research and is solely focused on new product innovation. We are assembling a database of 14,000 ingredients, over 400,000 formulations, millions of culinary recipes, and over a billion sensory and consumer data points loaded on a highly proprietary algorithm to be an inspiration partner for our product developers who are working in 20 labs located in 14 countries. It is a learning algorithm that becomes smarter and more innovative when receiving feedback from the developers using it on their daily product development activities.

What role do you envision large CPG companies such as McCormick playing in the future of food?
A lot. The large CPG should become more nimble and agile and respond quickly to the changing consumer taste, habit and experience. That is exactly what we have done in the past and will continue to do in the future.

In the coming decades our industry will be facing seismic changes. Among them is the unprecedented explosion of e-commerce that has disrupted the entire retail supply chain from end to end. The food industry will go through major M&A to stay competitive. The new generation of consumers, led by millennials, is forcing CPG companies to have a greater focus on transparency, natural and organic products, GMO, sustainability, and social responsibility.

Additionally, the information technology revolution will change almost everything we are doing today. Nutrogenomics and customized nutrition will transition from experimental to mainstream. And last but not the least, global warming, droughts, and loss of cultivable land and mass migration from rural to city centers are threatening all agriculture-based industries.

As the Chief Science Officer of McCormick, my number one responsibility is to turn all these seemingly insurmountable challenges into opportunities for accelerated growth, wealth creation, and competitive advantage. For example, e-commerce will provide unlimited shelf space which in turn will offer a platform for significant increases in new product introductions and mass customization. Advances in data analytics, artificial intelligence, and robotics will simultaneously make new product development better, faster, and cheaper. Potential loss of cultivable land lends itself to the exploration of aquaculture. There is never a dull moment in what I do day in and day out.

How does a large, established company like McCormick innovate and pivot to take advantage of fickle consumer trends?
By being committed to science-enabled innovation and acting nimbly.

What’s the one spice you couldn’t live without?
I love my cinnamon sprinkled over my breakfast every day. I never miss sprinkling black pepper, oregano and taragan on my salad for lunch and dinner. I love to have my tea with a dash of cardamom. My wife always adds a blend of turmeric, cinnamon, rosemary, cumin, and saffron to cooked rice she makes almost every evening that we eat at home.

Keep an eye out for more speaker Q&A’s as we ramp up to our fifth year of SKS on October 7-8 in Seattle! We hope to see you there.

Ai Palette Raises $1.1M in Seed Funding for its Food Trend Prediction Platform

Ai Palette, a Singapore-based startup that uses machine learning and artificial intelligence to predict trends for food companies, announced it has raised $1.45 million Singapore dollars (~$1.1M USD) in seed funding. The blog e27 reported the news first, writing that the funding round was led by Decacorn Capital with participation from the Singapore government’s SGInnovate and AgFunder as well as existing investor Entrepreneur First.

According to Ai Palette’s website, the company uses “Artificial Intelligence and Machine Learning to draw insights from millions of data points to identify consumer needs in real time and combine it with the brand personality to create winning food product concepts.”

Using machine learning and AI to help food and CPG companies capitalize on emerging trends is an already crowded field. Companies like Spoonshot, Analytical Flavor Systems, Tastewise and Halla all use various implementations of machine learning and AI in this capacity.

The goal for all of these companies is to speed up the R&D process for food producers. The sooner a food trend can be spotted, the faster the process can be to get it to market. Additionally, AI allows companies to suck up even more data to provide more granular predictions based on things like regional preferences, or even come up with new flavor combinations that might not ordinarily be tried.

Ai Palette says it will use its new funding to scale up development and grow out its customer base across multiple markets.

Standard Cognition Raises $35M Series B for its Cashierless Checkout Tech

Standard Cognition, one of a host of startups looking to bring cashierless checkout to the retail experience, announced today that it has raised a $35 million Series B round of funding. The round was lead by EQT Ventures fund, with participation from existing investors Initialized Capital, CRV and Y Combinator. This brings the total amount raised by Standard Cognition to $86.1 million.

Standard Cognition retrofits retailers with Amazon Go-like grab-and-go capabilities. Using computer vision and artificial intelligence, it keeps track of items shoppers take from the shelves and automatically charges them via mobile app when they exit the store.

With this Series B round, Standard Cognition now has a far bigger warchest than the other players in the cashierless checkout space, which breaks down as follows:

However, the one thing Standard Cognition doesn’t have right now is a publicly named customer. Standard Cognition opened its own proof-of-concept store in San Francisco last year, and according to today’s press release, “The company has signed several retail customers and is deploying for two already in multiple locations, with scheduled go-live dates in Q3 and Q4 of this year.” But Standard Cognition has to name names.

This is a fairly common scenario: most startups making cashierless checkout solutions can’t actually name their actual customers right now. In fact, the only two that have done so at this point are Grabango with Giant Eagle and Trigo Vision with Shufersal in Israel. The reluctance of retailers to officially announce a partnerships is understandable as they typically move slowly with such technology implementations, wanting to make sure they pick a solution that can scale appropriately.

The cashierless checkout sector is still wide open, and with today’s big raise, Standard Cognition has the money to withstand the competition.