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The Spoon

Daily news and analysis about the food tech revolution

artificial intelligence

Will AI Make For Better CPG Products? These Startups Think So

While the overall food tech market has seen a contraction in funding in 2022 as venture investors become more cautious, one area of companies that seems to continue to raise interest is those that leverage ML and other forms of AI to power CPG decision-making, product development, and core ingredient development.

Over the past couple of months, we’ve seen a bevy of startups raise funding, announce new products and tout their platforms for AI-powered CPG. Here are just a few examples:

NotCo

This week, NotCo, a Jeff Bezos backed startup with roots in Chile, announced a $70M Series D on a $1.5 Billion valuation. The funding will be used to launch the startup’s B2B business where it will open access to its AI platform to other CPG brands to accelerate plant-based CPG product development. The B2B platform launch comes after the company announced a new joint venture with Kraft Heinz earlier this year under which they have already launched plant-based versions of Kraft’s cheese slices.

StarDay Foods

StarDay, a startup which bills itself as a ‘next-generation food conglomerate’, just launched its third CPG product, a gut-friendly seasoned rice product. The company’s ‘Starday Insights Machine’ uses  natural language processing, machine learning models, testing capabilities, and analytical insight tools to “identify and predict trends, derisk our investments, and speed up the product development process”. The company has raised $4 million in seed funding.

Verusen

Verusen’s approach to leveraging AI is to use it to help other CPGs create more resilient supply chains. The company claims it has created $30 million in “working capital optimization” for a global CPG brand (which it doesn’t name). Verusen says its platform “leverages artificial intelligence (AI), deep learning, data harmonization, and decision support to help global brands control risk, attain supply chain resiliency, and improve economies for their operations.”

Fractal AI

Fractal has created a CPG and retail-focused AI platform called Asper AI, which the company claims “unifies demand planning, sales and distribution, inventory planning, and pricing and promotion.” Fractal says its ‘autonomous decisioning platform’ can help CPG and retail companies achieve “10%+ potential growth opportunities in financial performance and more than 50% in the automation of decision-making.”

SymphonyAI

SymphonyAI has what it calls a “end-to-end, integrated AI-powered merchandising, marketing, and supply chain solutions for retailers and CPG manufacturers” which it recently used to help German retail giant Metro GMBH to optimize its SKU mix and find retail shelf space efficiencies for its Romanian storefronts.

Shiru

Shiru is building a B2B business for CPG brands who want to create plant-based meat and dairy alternatives. The company’s Flourish platform utilizes machine learning to mine a proprietary database with the goal of developing plant-based functional ingredients.

The interest in utilizing new approaches for CPG product development, supply chain optimization and ingredient discovery comes at a time of upheaval for the broader industry. Supply chain worries, persistent inflation, global geopolitical instability, and rapidly changing consumer tastes have all made modeling the future a much more difficult task, adding pressure on CPG brands and their retailers to shorten product development and planning cycles.

While it’s worth asking how many of these startups are utilizing true “artificial intelligence” or simply capitalizing on the desire among brands to re-configure their development process, there’s no doubt that leveraging the rapidly maturing and powerful AI technology that has reached the commercialization stage will be a trend that only intensifies in 2023.

Watch Nala Robotics’ Robot Chef in Action

A restaurant that can serve millions of different dishes, is open 24/7, and doesn’t close on holidays sounds like a dream, right? After three years in the making, Nala Robotics has made this dream a reality with its fully automated robot kitchen that opened on November 11th in Naperville, Illinois.

The first automated restaurant/kitchen by Nala Robotics is called One Mean Chicken, and it serves wings and fried chicken. It is manned by multiple robots powered by artificial intelligence and machine learning, which do not need human intervention to function. Without the need for humans, Nala’s restaurant can operate throughout the day and night, on holidays, and without social distancing considerations.

Watch this video to see the robots preparing food:

Introducing Nala - a multi-cuisine AI based robotic chef capable of making over 2000 dishes a day.

Recipes can be uploaded by the user to the recipes catalog, and the robots can learn to make any dish within just a few minutes. This easily gives restaurant concepts the opportunity to offer multiple cuisines under one roof.

Nala’s use of articulating robotic arms to do everything from prep, cook, and more while handling a variety of cookware and utensils is reminiscent of Moley’s chef robot, which the UK-based company announced general availability for last year. Unlike Moley, Nala is exclusively targeted for commercial foodservice applications, whereas Moley is targeted both towards high-end residential installations in addition to commercial applications.

According to Ajay Sunkara, the founder and CEO of Nala Robotics, “Being AI-powered, the robotic chef gets better and better every single day. The more it cooks, the more it’s going to learn and master these recipes.”

Restaurants around the country have been facing major labor shortages in 2021 due to the aftermath of the pandemic, and over 25 percent have reported that they are struggling to hire line cooks. Automated kitchens like Nala, and others such as Mezli, Spyce, and Cala may prove to be a viable solution to these ongoing shortages.

Nala Robotics will soon open two more restaurant concepts in the same location as One Mean Chicken (in Naperville’s Mall of India). The next to be launched will be Nala’s Thai 76 (Thai food) and then Surya Tiffins (South Indian food). In 2022, Nala plans to open 10 restaurant locations, and then 100 locations by 2024.

IBM Partners With McDonald’s, Acquires McD Tech Labs to Automate Drive-Thru Orders

Over the summer, McDonald’s announced that it was trialing automated ordering at 10 Chicago, Illinois locations. Now, it appears that we will be seeing automated ordering at more locations sooner than later. Today, IBM announced that it has partnered with McDonald’s to continue to develop automated drive-thru orders and acquired its proprietary McD Tech Labs. The financial details of the acquisition were not disclosed.

McDonald’s acquired Apprente, a voice technology company, in 2019, and shortly after developed McD Tech Labs based on Apprente’s tech. This technology uses artificial intelligence to process drive-thru orders and then sends the order to the kitchen, where it is fulfilled by staff.

What is the benefit of using an AI-powered ordering system? In the trial run at the Chicago locations, McDonald’s found an 85 percent accuracy rate with orders and about 20 percent of orders needing staff assistance. AI can also help reduce customer wait time and free up employees to assist elsewhere in the restaurant.

In addition to the acquisition of McD Tech Labs, IBM will assist in the continued development of the Automated Order-Taking (AOT) technology and work on additional languages and dialects.

Consumers have traditionally voiced a certain degree of hesitancy in interacting with artificial intelligence. However, in Datassential’s AI & Menus report, it found that 43 percent of consumers found voice ordering technology unappealing initially, but after experiencing it, 68 percent were satisfied with the tech.

McDonald’s operates nearly 14,000 locations throughout the U.S, and it was not disclosed when a large rollout of the AOT technology might occur. IBM stated in the press release that it will help the quick-service chain accelerate the deployment of the AOT technology across different markets.

Ai Palette Raises $4.4M USD for Trend-Predicting Tech

Singapore-based Ai Palette announced today that it has raised $4.4 million USD in an oversubscribed Series A round. The round was co-led by Exfinity Venture Partners and pi Ventures, with participation from Anthill Ventures and return investors VC AgFunder and Decacorn Capital. This brings the company’s total funding to $5.5 million USD.

Ai Palette uses machine learning and artificial intelligence to help CPG and food companies predict consumer trends as they emerge. The company’s first product is called Foresight Engine, which can track a trend’s future trajectory, consumers driving it, and its maturity. The machine learning platform recognizes 15 different languages and can process data from various sources including images.

It is estimated that approximately 10,000 new CPG products are released each year, and within two years, 85 percent of these products will fail. Staying ahead of trends can help companies differentiate from competitors, directly target consumer preferences, and time product launches.

The use of AI and machine learning can help identify trends early, and speed up the R&D process. In turn, this can help food companies bring their product to market faster. Besides Ai Palette, several other companies offer trend-predicting services including Tastewise, Spoonshot, Halla, and Analytical Flavor Systems.

Besides emerging trends, these services can additionally predict taste preferences in different regions of the world. For example, Ai Palette analyzed 1.2 billion data points to track beverage trends in the U.S., Canada, India, and Southeast Asia during the summertime. It was found that in the U.S., the use of acerola cherry in juice drinks has experienced a year-over-year growth rate of 254 percent.

Ai Palette will use its new capital to expand its customer base outside of Asia, recruit new data science and engineering talent, and develop new product lines.

Sama Provides the Data to Fight Food Waste and Power Cashierless Checkout

When we talk about artificial intelligence (AI) in food tech, it’s often about the end result: Cashierless checkout, crop assessment, autonomous vehicles, etc. But one thing that these solutions and any other using AI need is is good data. Sama is a company in the good data business, and it has built a platform that provides training data that other companies can use to speed up the development of their AI models.

I spoke with Wendy Gonzalez, CEO of Sama, this week by video chat. She outlined some of the food tech use cases for her company’s technology, such as fighting food waste. “If you’re in a restaurant or hotel, catering service. A lot of that food gets wasted,” Gonzalez said. Sama is working with a company called Orbisk that provides a device for commercial kitchens that uses computer vision to analyze the food being thrown away. For example, if Orbisk sees a lot of mac and cheese is being tossed because no one is taking it, that kitchen can know not to make as much of it, and by extension save money by ordering less of the ingredients to make mac and cheese. (Winnow is another company that takes this same approach.)

For its part, Orbisk had a thousands of images of different types of food for its system to recognize. Sama came in and provided structure and taxonomy to that data. In other words, Sama labeled all the images of mac and cheese accordingly to train Orbisk’s AI to automatically recognize mac and cheese. The result, according to Sama, is that Orbisk’s system can reduce food waste in commercial kitchens by as much as 70 percent.

Gonzalez said that Sama’s system is also being used in other fields like cashierless checkout. In that setting, Sama is helping train those computer vision systems to recognize packaged goods, which is more complicated than people think. A cashierless checkout system needs to not only recognize a package of Oreos, but a package of Oreos in different lighting conditions, different angles or when the view is partially blocked. Sama provides all of that data.

Sama is also being used to train AI systems on early crop disease detection, automated crop harvesting, and soil condition monitoring.

Sama is among a number of players in the data space including AI.Reverie, which uses synthetic data to create images virtually to train AI models, and Nvidia, which is also using synthetic data to train robots to navigate around a kitchen.

As AI plays a bigger role in our everyday lives, there will be a growing need for more good data to train those AI systems. And the end result is that we’ll all be talking about good data more often.

McDonald’s Drive-Thru Plans Need to Factor In Franchisees

The big to-do in the drive-thru lane of late is news that McDonald’s is testing automated ordering at 10 locations in Chicago, Illinois. 

The tech is based on an acquisition McDonald’s made in 2019 of voice-tech company Apprente. Through it, intelligent systems, rather than human beings, take the drive-thru customer’s order and send it to the kitchen for fulfillment. At an investor conference last week, McDonald’s CEO Chris Kempczinski said the company is seeing 85 percent accuracy on orders, with only about 20 percent of orders across the 10 stores requiring human intervention.

While Kempczinski is confident we’ll see voice-ordering at all McDonald’s drive-thrus in the next five years, he added that consumers shouldn’t expect to see it widespread as soon as next year. “There is a big leap between going from 10 restaurants in Chicago to 14,000 restaurants across the U.S. with an infinite number of promo permutations, menu permutations, dialect permutations, weather — I mean, on and on and on and on,” he said at the conference.

Separate from the technical feats the system must accomplish, there is also a huge number of franchisees to consider in the process of a wide-scale implementation. There are currently 38,000 McDonald’s operating across roughly 115 countries. The majority — 93 percent — are franchisees. Getting them onboard may be no small feat, either.

Disputes over technology have created tension between McDonald’s and its franchisees for years now — going all the way back to when some franchisees argued against having to offer Uber Eats to customers. The latest disagreement between the two groups concerns a $423-per-month fee corporate has been charging franchisees to cover a $70 million lag in outstanding technology fees. The National Owners Association (NOA), a group of McDonald’s franchises that formed a few years back, has gone as far as suggesting it create a technology cooperative to give owners more control over technology-related decisions. Ernst & Young is currently conducting a third-party audit of the fees in question.

All of which is to say, now may not be a great time to attempt a major rollout of what will probably be a costly system. How costly voice ordering will be for franchisees is unclear just yet, but it would presumably require setup and maintenance costs at the very least. And as we saw with McDonald’s Dynamic Yield acquisition, implementation, and eventual downgrade, not all new tech brings a justifiable amount of return on investment for franchisees. 

Labor also presents some urgent items to consider. 

While automating drive-thru ordering via a system like Apprente’s could aid in the current struggle against the current labor shortage, franchisees will still have to spend time and money training their employees to use the tech and work alongside it. In many cases, that means training them to learn when to not get involved.

At the investor conference, Kempczinski said one learning from the existing 10 implementations of the new tech was training crew to “not want to jump in” as soon as there is a question or pause from the system. “We’ve had to do a little bit of training of ‘just keep your hands off the steering wheel, let the computer do its work,’” he told investors, adding that it took time for crew members to learn to “trust” the technology. 

While McDonald’s hasn’t officially confirmed this, it’s likely franchisees would be in charge of training for the above. That in turn would mean operators and manages must first get comfortable with the tech themselves. And, given the high rate of turnover in QSRs, this could potentially eat up a lot of time if a manager were continually having to train new hires.

Many see the digitization of the drive-thru as essential. The drive-thru lane has become progressively slower over the years. The pandemic didn’t help that latter point, since lockdowns turned the drive-thru into one of the main order channels for restaurants, making overall wait times even longer. Other QSRs, including Chipotle, KFC, and Burger King, have all announced plans to make their drive-thrus more high tech to speed up wait times and improve order accuracy. Clearly McDonald’s needs to compete. This time around, though, it also needs to make sure it thoroughly considers its franchisees’ needs in the process.

More Headlines

Presto Launches a Bundle of Tech Tools to Help Restaurants Reopen With Fewer Staff – Restaurant tech platform Presto today launched a new product bundle it says is meant to help restaurants keep their operations up-to-par in the midst of the ongoing labor shortage.

Tesla May Soon Open Its Own Restaurant – Tesla has filed a trademark under restaurant services, which suggests the automaker may be finally working to realize its dream of combining its charging stations with an old-school drive-in restaurant.

Yum China’s New Program Will Teach Digital Skills to Children in Rural Areas – Yum! Brands spinoff Yum China is investing in more digital education for underserved areas. 

McDonald’s Testing AI-Powered Drive-Thrus in Chicago

McDonald’s has started testing out drive-thrus that use artificial intelligence systems, rather than humans, to take orders. CNBC reported yesterday that the new automated drive-thrus are in use at 10 Chicago McDonald’s locations.

The new system is based on the voice platform built by Apprente, which McDonald’s acquired in 2019. According to McDonald’s, restaurants using the system are seeing an 85 percent order accuracy rate, with only about one-fifth of orders requiring human intervention.

AI-powered drive-thrus can reduce customer wait times and allow restaurants to shift its in-store workforce. A computer that understands natural language is always on and available to take orders. It could also be tied in with other automated systems that know a customer’s purchasing history to automatically make recommendations. With improved understanding accuracy, a restaurant would no longer need a dedicated person to take (or confirm) a drive-thru order, allowing more people to do more customer service or expedite orders.

McDonald’s CEO Chris Kempczinski told Alliance Bernstein’s Strategic Decisions conference that a big issue ahead for the AI-powered drive-thru is scaling. CNBC reports Kempczinski as saying “Now there’s a big leap from going to 10 restaurants in Chicago to 14,000 restaurants across the U.S., with an infinite number of promo permutations, menu permutations, dialect permutations, weather — and on and on and on.”

The Apprente acquisition appears to be working out better than Dynamic Yield, which McDonald’s also acquired in 2019. Dynamic Yield generated automated menu recommendations based on factors like weather, and was supposed to be integrated into self-service kiosks and drive-thrus as well. However, this tech didn’t yield the results McDonald’s was looking for and in March of this year The Wall Street Journal reported McDonald’s was looking to sell part of Dynamic Yield.

While McDonald’s Apprente acquisition may have pre-dated the pandemic, last year certainly accelerated the need for enhanced drive-thru technology as dining rooms were forced to shut down. In a February 2021 survey, BlueDot reported that 91 percent of respondents said they had visited drive-thrus the previous month and that long wait times were a “dealbreaker.” Most major QSRs have been doubling down on their drive-thru capabilities to meet this demand, adding capacity and building restaurants around takeout rather than dine-in.

In addition to adding AI assistants, McDonald’s has previously said that it will add other features to its drive-thru such as express lanes for digital orders and conveyor belts to carry food out to customers.

Kempczinski also told the conference that McDonald’s is also exploring ways to automate parts of the kitchen such as the grill or fryer. However he said any such move in the back of the house is still a more than five years out as the technology is too expensive right now.

Food Tech News: Google AI Cake, Chipotle’s Bitcoin Giveaway and Robot Food Delivery

Welcome to the first Food Tech News round-up of April! This week we have news on a cake created by Google artificial intelligence, Kiwibot hitting the streets of Santa Monica, Ember’s new travel charger, and Chipotle’s bitcoin giveaway.

Google artificial intelligence created a cake recipe in partnership with Mars Wrigley

Google Cloud engineers created a machine learning model that uses hundreds of existing baked good recipes to develop a completely new recipe. The result was a “Cakie” (a cake and cookie hybrid) and the components of what makes a cake and cookie were generated with artificial intelligence. For the partnership with Mars Wrigley UK, Maltesers (chocolate-covered malt balls) were incorporated into the recipe to create the first-ever “Maltesers AI Cake.” Google trends revealed that “sweet and salty” was a top search trend, and the cake recipe used a buttercream frosting infused with Marmite. Earlier this year, the same machine learning model was used to create two totally new baked good recipes, the “Cakie” and “Breakie”.

Kiwibot and MealMe partner for food delivery in Santa Monica

MealMe, an app that compares prices and times of food delivery services, and Kiwibot, a teleoperated robot service that delivers food, have partnered to deliver food in Santa Monica. On April 1st, the companies began delivery for Blue Plate Taco and Red O Restaurant on Ocean Ave. Kiwibot’s robots provide contactless food delivery, and so far 100k deliveries have been completed in Berkeley, Los Angeles, San Jose, Denver, Taipei, and Medellin,

Ember launches car charger to keep beverages warm on the road

Ember, the creator of the self-heating coffee mug, has created a car charger to keep Ember Travel Mugs warm all day. The Ember Travel Mug is capable of keeping a beverage warm for three hours, but now it can be plugged directly into a car charger for an all-day charge. The car charger costs $49.95 on Ember’s website.

Photo from Chipotle

Chipotle hosted a giveaway of free burritos and bitcoin

For National Burrito Day, Chipotle partnered with the founder of Coil, Stefan Thomas, to giveaway $100,000 worth of Bitcoin and $100,000 in burritos. To win, contestants had 10 chances to guess a six-digit code. The giveaway only lasted for nine hours on April 1st on BurritosOrBitcoin.com. Update: I tried, and did not win.

Honeycomb.ai Helps Those with Allergies Eat at Restaurants Through AI

Vancouver, Canada-based Honeycomb.ai opened up its artificial intelligence (AI)-based web app this week to help diners with food allergies and specific diets navigate restaurant menus. The first version of the service is currently available for users in the U.S., Canada, and Australia.

From Honeycomb.ai’s website, a user can select from 29 different allergies or dietary preferences (only two filters can be picked at the same time). Then, after selecting a specific city, the website populates restaurants in the area and menu items that are acceptable based on the selected criteria. I spoke with Honeycomb co-founder Tamir Barzilai by phone this week to learn more about how the company’s algorithm functions. Tamir said the Honeycomb.ai team spent four years training the algorithm to learn what menu items are typically acceptable for different allergies and dietary preferences. Using the name, category, description, and any available metadata of a restaurant menu item found online, the algorithm is able to predict what ingredients will be found in it.

Tamir said that the algorithm is able to do about 90 percent of the work, but there is still some information that needs to be entered manually by the restaurant. After the algorithm makes its predictions, a restaurant must sign up on the Honeycomb platform to verify the accuracy of those menu predictions and add in additional ingredients that the algorithm may not be able to pick up on. For example, if a dish was cooked in butter, but the restaurant’s menu description does not directly state this, so a restaurant would add this to the database for a more complete breakdown of ingredients. Additionally, restaurants can add Honeycomb.ai’s plug-in feature directly to their website to help users find menu items suitable for their diets.

In the U.S., it is estimated that around 32 million people experience food allergies, while 36 percent of Americans follow some type of specific diet. In addition to Honeycomb.ai, there are various companies taking different approaches to make dining out with a food allergy or dietary preferences a more streamlined process. SevenRooms, a company focused on back-of-house restaurant tech, enables restaurants to track customer data to remember important things like food allergies and preferences. Nima, producers of handheld peanut and gluten detectors, conducted gluten and peanut tests on dishes at major restaurant chains and created a map of all “Nima-tested” restaurants.

Honeycomb.ai is currently available as a website and iOS app. The iOS app will be updated with a new version shortly, and the company will also be launching an app for Android in the next few months.

MyFitnessPal Adds AI Scanning Technology to iOS for Tracking Calories

MyFitnessPal this week announced the launch of its new AI-powered scanning feature that automates some of the process of identifying and tracking the ingredients in a user’s food items. The company has partnered with Passio, which provides computer vision for companies through its AI platform, to develop this new feature.

If you’ve ever tried using a food tracking app or website, you’ll know what a pain it is to enter every single ingredient of each meal and snack you consume. With MyFitnessPal’s scanning feature, a user selects the Meal Scan feature in the app, then holds their phone’s camera over the food. The AI scanning tool is able to identify the food, both the type and the amount of it, through the combination of Passio’s food recognition technology and MyFitnessPal’s massive database of 14 million foods.

This feature can help users avoid having to search for each ingredient and food within the database, but it is not yet fully automated. After scanning the food, the user must confirm the foods and amounts the app has identified. After confirming, calories, fat, protein in the food is calculated and this information will be automatically added to the user’s food diary.

That being said, using computer vision for tracking food can still save a user a lot of time, and MyFitnessPal is not the only company using something like this. Bite.ai is another company that has a free food tracking app, and it uses a similar technology that applies computer vision to identify food that is then added to the user’s food diary.

MyFitnessPal’s scanning technology is currently available on iOS, and it will be made available for Android phones in the near future. The MyFitnessPal app is free, but only those who are premium members for $9.99/month will have access to the scanning feature.

Ukko Raises $40M to Fight Food Allergies and Develop its Good Gluten

Ukko, a biotech company that uses artificial intelligence (AI) to develop food and therapeutics that fight food allergies, announced today that it has raised a $40 million Series B round of funding. The round was led by Leaps by Bayer (the impact investment arm of Bayer), with participation from Continental Grain Company, PeakBridge Ventures, Skyviews Life Science and Fall Line Capital. Existing investors including Khosla Ventures and TIME Ventures, the investment fund of Marc Benioff, participated as well.

This brings the total amount of funding raised by Ukko to $47.7 million dollars. According to the press announcement, the new funding will allow Tel Aviv, Israel-based Ukko to enter into clinical trials for its investigational therapeutic for peanut allergies and, more relevant for our purposes, accelerate development of the company’s proprietary gluten.

Simply speaking, Ukko uses its AI platform to analyze patient data to map how an allergen triggers a reaction in the body. With that information, Ukko breaks down the gluten protein to its component level and gets rids of the bad parts that cause allergic reactions. It keeps the good parts. Ukko then creates this new good gluten either by genetically modifying wheat plants or fermenting yeast (or some other applicable base cell) to grow it in a bioreactor.

The result, Ukko Co-Founder and CEO Anat Binur told me by phone this week, is a gluten that stretches and bakes and has all the biophysical aspects of gluten, and can be eaten by people with gluten sensitivities and celiac disease. This, in turn, means that gluten-sensitive people don’t need to sacrifice quality when enjoying different types of baked goods.

At least, that’s the plan. Binur said that some of the company’s new funds will go towards clinical trials of its gluten and getting the product through all the safety protocols and to the point of commercialization.

Once Ukko’s gluten reaches the commercialization stage, Binur said that there are a number of options for how it comes to market. Ukko could sell its own gluten, which could be added to gluten-free starches (like almonds or rice). Alternatively, the company could sell its own gluten flour as an ingredient to food companies and restaurants/bakeries, or create its own line of branded gluten-free flour to be sold on store shelves. Or Ukko could pursue some combination of all three.

By one estimate from Grand View Research, the gluten-free products market was valued at $21.61 billion in 2019, and projected to grow at a CAGR of 9.2 percent through 2027. So there is plenty of market opportunity just in gluten for Ukko.

But Ukko’s platform can be applied to any food allergy. As noted, the company is developing therapuetics for peanut allergies, but Ukko’s tech could be used for dairy allergies, soy allergies, egg allergies, etc. Creating replacement foods from the ground up that have the same nutrition and behave like the original could help alleviate a lot of sickness and save lives.

Gardyn Aims to Make At-Home Vertical Farming Small, Simple, and Stylish

Thanks to disruptions in the food supply chain, panic-buying sprees, and the general uncertainty of the times, growing food at home seems like a pretty good idea of late. Trouble is, many consumers don’t have the know-how to cultivate their own leafy greens and other produce in the backyard. Even those who do often lack adequate space.

A company called Gardyn is addressing both of those issues with an at-home vertical farming system that requires minimal input from the user and can easily fit inside a small apartment if need be. The idea, as Gardyn founder and CEO FX Rouxel explained to me over the phone last week, is to make growing food in one’s own home as simple and straightforward as possible. To do that, the company has built a farm that relies on AI to do much of the heavy lifting in terms of monitoring and maintaining an edible crop of food. Or as Rouxel said, “The system is managing everything for you.”

Gardyn’s system is made up of two parts: a compact vertical tower, which can grow as many as 30 plants, and an accompanying app powered by an AI assistant named “Kelby.” Users only have to order seeds and “plug” the seed pods into the vertical towers. The system automatically circulates water and nutrients to the plants, while Kelby monitors plant growth and sends reminders when it’s time to add water to the garden or harvest the plants. 

Right now, available crops from Gardyn’s site include mostly leafy greens and herbs, some flowers, cherry tomatoes, and jalapeños. Customers can also use their own seeds if preferred.

The system uses what Rouxel calls “a hybrid of different hydroponic technologies,” including the deep water method and aeroponics. (The company brands its approach as “hybriponics.”) By themselves, these different methods have certain limitations in the at-home setting. Deep water, where plant roots are fully submerged in nutrient-enriched water, requires a lot of space. Aeroponics is a great setup for outdoors, but once indoors it requires lighting, which gets expensive very quickly. Gardyn pulled elements from both to create a system that takes up only two square feet of space and doesn’t require any extra hardware. “Within just two square feet, you can produce a lot of food,” says Rouxel, adding that Gardyn’s units have produced “over 25,000 pounds of produce” during the last few months.

That quest to grow a lot of leafy greens in a small amount of space is an area with plenty of competition these days. Farmshelf recently unveiled its first-ever farm for the home, and companies like Rise Gardens and Agrilution (the latter recently bought by Miele) also offer promising solutions for the consumer space.

And while historically, investment in vertical farming has mainly gone towards the industrial-scale indoor farms (think AeroFarms), at-home farms are fast becoming a lucrative area. Investors, Rouxel explained to me, see traditional agriculture as a risky business that’s less insurable because its success is in part dependent on the weather outside. With climate change triggering more extreme weather, investors will look more and more to alternative solutions in controlled-environment agriculture.

“I am absolutely convinced we are going to see in the coming two years a total disruption in the way we grow things,” he says. Chiefly, that will be growing the food in much closer proximity to consumers, whether through at-home systems like Gardyn’s, in-store farms at grocery retailers, rooftop gardens, and high-tech greenhouses. “In future we’re going to have a spectrum of solutions,” Rouxel noted.

Getting these vertical farms closer to consumers and in their own homes will require bringing the price of the machines down. At the moment, Gardyn’s system is roughly on par pricewise with other systems out there that can realistically feed a family of four: $799 for the base model all the way up to $1485 for the “Plus” model.

Rouxel is aware that the cost is still too high for many consumers. “We don’t want this to be only for well-off people,” he told me. “It’s important that we find ways that anyone can afford this.”

Many companies, including Gardyn, offer financing options on their farms now. And more investment dollars going into the space in the future could mean companies have the time and space to innovate on ways to make their system cheaper for the average consumer.

While pricing remains a question, one thing that’s certain is that at-home vertical farming is on the path to becoming a regular part of the kitchen, rather than just a trend. “What we want is to develop solutions that will quickly change the way people access food,” said Rouxel. “We won’t solve everything, that’s for sure, but we want to be part of the solution for how we shape food.”