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Daily news and analysis about the food tech revolution

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Spoonshot Launches Free Version of its AI-Based Flavor Pairing Tool

Spoonshot, which uses artificial intelligence (AI) to uncover novel flavor combinations, has launched a free version of its tool that is accessible to anyone. Spoonshot CEO and Co-Founder, Kishan Vasani spoke about the new level of service at The Spoon’s Food Tech Live event earlier this week.

Up to this point, Spoonshot’s platform has been a B2B play, meant for CPG companies and foodservice operators looking ahead to see what the next food and flavor trends might be. As we wrote last year when Spoonshot raised $11 million:

To get ahead of the curve, Spoonshot’s platform examines data from across a vast number of food-related sources including online menus, food science, CPG ingredients and online food communities. Spoonshot runs this data through its proprietary machine learning and AI algorithms to help companies identify existing and novel flavor combinations.

The key word here is “novel.” When you enter a flavor like “banana” into Spoonshot’s Ingredient Network tool, the service brings back a number of potential flavor combinations and scores them based on novelty. Combining banana + chocolate is common, but combining banana + aloveera juice is something that probably hasn’t occurred to most people and a combo that Spoonshot says will be tasty.

Armed with this novel combination, a restaurant or CPG company could go about building a new product that will appeal to consumers.

Launched at the start of the new year, Spoonshot’s new free tier of service now allows anyone to try its AI platform out (pricing starts at $99/month). Chances are good that most of us in our everyday lives don’t need enterprise-grade artificial intelligence to uncover novel flavor combinations. But aside from being a fun (and free) little distraction for everyday chefs, it could also be useful for small CPG or restaurant owners that don’t have R&D budgets to expand their offerings.

Tastewise Launches Its AI-Powered Food Prediction in the UK

Tastewise, which uses AI to predict consumer food trends, announced today it has launched its platform in the UK and added more localized data to help restaurants and food producers in that region better anticipate consumer eating habits. According to a press release sent to The Spoon, Tastewise has integrated data from 183,000 restaurants and delivery menus, over 2.8 billion social interactions, and 1.2 million online recipes from the UK into its platform.

The Tastewise platform, which launched in February of 2019, helps CPG companies better predict food trends through artificial intelligence (AI). It analyzes consumer touchpoints (think Instagram photos and online recipes) to find not just what foods consumers are eating right now but also their deeper motivations for choosing those foods. When we spoke about a year ago, Tastewise CEO Alon Chen used the example of sauerkraut to illustrate the point: 

“Right now, according to [Chen], it’s a popular food, but the trend is less about raw cabbage and more about the process behind it, which is fermentation . . . Food companies analyzing data via the Tastewise platform can see such data and consider how they might implement fermentation into their offerings.”

Tastewise counts Nestlé, PepsiCo, General Mills, Dole, and other major CPGs among its customers. With today’s launch, UK-based food businesses will also be able to utilize the platform to get more real-time insights into consumer food behavior, which is a must in these pandemic-stricken days, according to Tastewise: “The pandemic has made it clear that it’s imperative to have your finger on today’s pulse each time a decision is made,” Chen said in today’s press release.

Speaking of which: along with the news of its UK launch, Tastewise also released a new report on UK consumer food trends during the pandemic so far. Among them:

  • Sustainable foods are rising 52 percent in popularity year over year, though health and fitness are motivating this trend, not environmental concerns.
  • UK demand for meal kits is up 200 percent.
  • CBD is fading in popularity.

Tastewise is not a sensory platform a la Spoonshot or Climax Foods. However, it is similar in that it leverages AI to help companies bring in-demand products faster by sinking less money into traditional R&D. And given the upheaval the pandemic has caused across the food system, both CPGs and foodservice companies will be leveraging more AI in the future to keep costs down by offering their customers the most relevant items possible. 

Spoonshot Raises $1M for its AI-Powered Flavor Trend Prediction Service

Spoonshot, a company that uses AI to predict new and different flavor combinations, announced today that it has raised $1 million in Seed funding. The round was led by SRI Capital and brings the total amount of funding for the company to $1.8 million.

The thesis behind Spoonshot is that companies looking to develop the next big thing in food need to look ahead. If your company only watches what is trending now, by the time it gets a product into market, that trend will already be over or commonplace.

To get ahead of the curve, Spoonshot’s platform examines data from across a vast number of food-related sources including online menus, food science, CPG ingredients and online food communities. Spoonshot runs this data through its proprietary machine learning and AI algorithms to help companies identify existing and novel flavor combinations.

The company launched its Ingredient Network product last October. At the time, we wrote:

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.

I spoke by phone this week with Kishan Vasani, Co-Founder and CEO of Spoonshot, and he said that the company has taken its Ingredient Network to the next level with its new Concept Generator.

Whereas Ingredient Network was more about exploring different flavor combinations and possibilities, the Concept Generator is more concrete. CPG companies can come to the service with a set idea in mind, like say, a cookie with blueberry as the main flavor. The Concept Generator then takes that information and returns with a blueprints of different blueberry cookies with different flavor combinations as well as all the ingredients that would go into making it.

Spoonshot’s tools are available at a unique time, given the pandemic. The lockdowns have people eating at home more and doing quite a bit of snacking. Giving CPG companies tools to quickly create new types of comfort foods could be quite appealing.

Vasani said that Spoonshot will be using the new money for marketing, something the company hasn’t really done up to this point, as well as hiring out its team.

How Will the Black Swan of COVID-19 Impact Data Used in AI-Based Flavor Prediction?

In order to build an effective artificial intelligence (AI) platform, you need good data. Data feeds the algorithms that go into the AI; the better your data the better your AI system will function.

In the food tech world, there are a number of startups like Spoonshot, Analytical Flavor Systems and Tastewise have built intricate AI platforms that use tons of different data to help big CPG companies identify and predict culinary and flavor trends.

But what happens when a big catastrophic black swan event occurs like, oh, I don’t know, a global pandemic, which changes the eating and buying patterns of almost everyone on the planet all at once?

For instance. In February, it was easy to buy flour and yeast at your local grocery store. Fast forward to March and suddenly store shelves were empty and you had to resort to making your own yeast. Around that same time, instead of pictures of fancy restaurant meals, social media accounts were flooded with pictures of homemade bread.

Food predicting AI systems uses data points like restaurant menus, social media mentions and consumer purchasing patterns to determine future trends. But everyone didn’t start making sourdough bread at home because it was suddenly fashionable. It was because everyone was stuck inside.

How then, will AI systems handle this shock to the data system? Sheltering in place won’t last forever (knocks on wood), and who knows how long people will actually make their own bread. The popularity of it now is an aberration, does this mean that the data surrounding it is no good? Is bread making today indicative of anything other being bored or does it foretell a bigger trend?

To get a better sense I reached out to both SpoonShot and Analytical Flavor Systems to see how they are incorporating this massive disruption to our eating patterns into their own prediction process — and got two very different answers.

SpoonShot’s AI uses more than 3,000 sources across 22 data sets including menu, social and pattern data. Kishan Vasani, Co-Founder & CEO of SpoonShot, didn’t seem to think that COVID-19-induced eating changes would impact his company’s predictive capabilities at all. “Algorithms shouldn’t be overly sensitive to black swan data,” he said, “If you think about it, AI essentially means having enough relevant and appropriate data to process and predict.”

In other words, if your AI system is worth its salt, you should be able to weather big changes like this. “Everything goes back to the data and data sources,” Vasani said, “Menu data is significantly slowed down, but that’s compensated for with cooking platforms.”

On the other hand Jason Cohen, Founder and CEO of Analytical Flavor Systems, thinks the pandemic and subsequent lockdowns are a big deal. “Companies will say, ‘no no no, we can make predictions,'” Cohen said, “I do not believe that. This is the most rapid and intense change to consumer behavior since World War II.”

Cohen believes that with quarantines already in place for more than 60 days, new habits will definitely have formed. People will still be baking bread at home. What’s important is to meet this new data where it lives, literally.

Up until the pandemic, Analytical Flavor Systems used a 50 person panel of tasters as part of its data collection. This panel would come into the office to try various on-market foods. But since lockdown, the company has moved entirely to at-home testing. “In addition to CPG products, we are asking them to taste profile their homemade bread and soups,” Cohen said, “The point is we need to see those flavors, aromas and textures they are exposing themselves to.”

Cohen doesn’t think that past data is invalidated, but rather that data needs to be collected before during and after this crisis. Something which I think Vasani would agree with.

The thing about predictions now is that we won’t know if they were accurate for a long time. SpoonShot looks out 18 months and is even considering pushing that out to two years.

Hopefully we’ll be able to eat bread at a restaurant again by then.

The Age of The Personalized Food Passport is Coming, Says Spoonshot CEO

It seems impossible for giant CPG companies working with thousands of retailers to make individualized products. But according to Kishan Vasani, CEO of Spoonshot, a startup that predicts emerging food trends, there’s still a way for these giant companies to mimic the effects of personalization in their wares.

How, exactly? To get the whole story you’ll have to come to Customize, our Feb 27th in NYC all about breaking down the impact of personalization on the food system. We did, however, ask Vasani a few questions recently about how he defines personalization, its wide-reaching effect, and how big CPG companies can capitalize off of individualization. He also explains his vision for the future in which we’ll all have a “food passport” which restaurants can use to tailor our meals.

Check out the Q&A below then grab your tickets to Customize here (pstt — use code SPOON15 to get 15 percent off).

Tell us a little bit about what Spoonshot does. 
Spoonshot is on a mission to power genuine agile innovation to the food and beverage industry. Our intelligence details emerging market and consumer needs by transforming long-tail, open information from diverse, authentic data sources. We connect these disparate data sets via our proprietary food science-infused algorithms to deliver personalized insights, predict trends, and identify innovation opportunities. 

How can large CPG companies, which have to work on a massive scale, create products that are personalized to consumers?
Firstly, it’s important to clarify what personalization really means (to me). To some it could mean customization (e.g., add blue cheese to a burger). To others, it might be about packaging that has your name on it. I firmly believe that personalization is about implicitly understanding an individual’s needs and desires. 

Today it’s not economically possible to create unique products for individual preferences, but CPG companies can create the same effect by having a deep understanding of evolving and emerging trends and innovating exactly against those growth opportunities. Of course, greater agility and efficiency is required at every stage of the product development cycle by employing the relevant technologies. 

Ask most CPG executives what the next big food trend is going to be and they will probably name a trend that is well established like plant-based [protein] or CBD. But ask them what’s [after that] and they won’t be so sure. There needs to be significantly more efforts to anticipate consumer needs, and perhaps the largest brands have the economic power to even shape consumer tastes. Too often they fail to exercise this — in contrast to the tech industry, which has been much more successful in pushing innovation upon consumers. iPhone, anyone? 

What’s the biggest challenge facing food personalization, specifically within the CPG space?
The biggest challenge to personalization within the CPG space is the way in which data has historically been used and continues to be or not be employed:

  • Over-reliance on (yesterday’s) sales data for decisions related to tomorrow’s innovation. 
  • The lack of use of large, external and diverse data sets. Instagram and Pinterest are not the answer; at best they are just a small part of it.
  • The internal data silos, especially in larger businesses who are potentially sitting on data gold and don’t even know it.
  • The slow adoption of new data and technology frameworks, particularly by R&D professionals.

How do you think that personalization will play into consumer dining and shopping habits over the next five years?
Personalization will play a central role across the consumer food landscape over the coming decade. 

Take personalized recommendations as one use case. Consumers have been used to personalized digital experiences for many years now thanks to leading tech companies like Amazon, Netflix, and Pandora. Yet somehow online food ordering lagged behind. We launched a personalized recommendation engine for online food platforms back in early 2017, but the market wasn’t quite ready. Fast forward two years and McDonald’s acquires Dynamic Yield to do exactly this, and today, the demand for personalized recommendations has never been higher. But this is just one way in which personalization will dominate the industry. 

We believe that there will be a “food passport” for every consumer so no matter where you eat, the business producing your food will know everything about your taste preferences and will have the ability to tailor your meal accordingly. There would be some interesting applications in terms of having a digital record of an individual’s consumption, and how health insurance providers might price their plans based upon this data. 

Since healthy eating is an established trend, consumers will increasingly demand personalized nutrition in restaurants as well, where science and technology can dictate what food is right for us — not only for weight management but, more importantly, to manage our overall health and wellness. 

Another innovation in personalization could be the emergence of (mobile) handheld scanners that help consumers identify allergens, nutrients, and ingredients in their food and provide them with a breakdown of the amounts of sugar, acidity levels and vitamins present in dishes,  as well as highlight potential allergens warnings.

Join us in NYC on February 27th to hear Vasani speak more about how CPG companies are leveraging personalization (and lots more). Use code SPOON15 to get 15% off your tickets now.


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.

Tastewise is the Latest Startup to Use AI for B2B Flavor Recommendations

Surprisingly, my eight-year-old’s current favorite toy is one of those old Magic 8 Balls that “predict” the future. Granted, most of his questions revolve around acquiring some Lego set, but he, like so many of us, want more certainty in our future.

Tastewise is a new startup that launched yesterday with a technology that aims to help restaurants and CPG companies better predict food trends using data and artificial intelligence (AI). According to the press announcement, “The platform analyzes billions of critical food and beverage consumer touchpoints to discover people’s real-life interactions with food including over 1 billion food photos shared every month, 153K restaurant menus across the US and over 1M online recipes.”

So Tastewise is looking at all those food pictures people are Instagramming and Tweeting about to see what is hip with the kids. It can also parse different ways items are described. For example, it will know that hamburgers, burgers and sliders are all basically the same thing. It takes all of this information and runs it through its algorithms to recommend new products on both a national and local level (what’s cool in Brooklyn may not be cool in Omaha).

I spoke with Co-Founder Alon Chen by phone, and he told me that with Tastewise, his clients can simply type in a food item like “hummus” and the software will crunch all the data and report back results of not only flavor information (ingredients people are adding to hummus), but also how people are using hummus (not just as a dip, but also as a spread).

Tastewise is offered as a SaaS product, and while specific subscription plans are being worked out, Chen said that they will always offer a free tier of results and a premium version for $299 a month. Exactly what results and insights are available to premium subscribers has yet to be determined.

The flavor-prediction sector is certainly hot like sriracha (though Tastewise says Zhoug is the next sriracha), as there are a number of other B2B players already in the market. Spoonshot and Analytical Flavor Systems both use AI to help companies predict and act quickly on food trends. Even spice company McCormick enlisted IBM’s Watson to help determine what tastes are on the horizon.

When asked about his competition, Chen said that Tastewise “is not a sensory platform.” Rather, his company is looking at what people are saying and the actions they are taking around food to develop consumer insight and intelligence that reflect what is happening and predict what specific foods and flavors will become hits.

Tastewise has raised $1.5 million in funding and has five employees. With CPG companies and restaurants all looking for any kind of edge over their competition, it doesn’t take a Magic 8 Ball to see that Tastewise has picked the right sector. Now we just need to see if it can beat out all the competition.

Dishq Rebrands as Spoonshot, Acquires Brisky

Personalized food recommendation engine Dishq announced today that it has rebranded as Spoonshot, and that the company has acquired India-based startup, Brisky.

During a phone interview, Spoonshot CEO Kishan Vasani told The Spoon that there were a couple of reasons for the re-branding. First, everyone outside of India pronounced the company’s name wrong (present company included). Evidently you weren’t supposed to pronounce the “q” in Dishq — it was supposed to be said “dishk.”

On a more serious note, the new moniker is also a clever, food-base play on “moonshot,” the big, bold initiatives ambitious companies undertake. Vasani said the name better reflects his startup’s mission. “We’re not a one product company,” Vasani said.

To that end, Spoonshot announced today that it has acquired fellow India-based startup Brisky (terms of the deal were not disclosed). Brisky provides restaurants with a way to gather feedback from consumers in a private, real-time way. Participating restaurants can ask customers to opt-in to use Brisky. If customers do, they receive a text message with a link to a mobile browser where they can rate their experience at that restaurant directly to the establishment, rather than just blasting it out on social media.

Brisky also allows restaurants to check in on customers via SMS mid-meal to see how things are going. This may seem strange for U.S. restaurant goers, but Vasani said that handing over a phone number to a restaurant is more common in India.

The Brisky team will continue to operate independently and will scale that product (it’s in 100 locations in India), but it will also provide another data pipeline to feed Spoonshot’s algorithms. As we’ve written before, Spoonshot is a B2B service that combines behavioral and food science data into its machine learning platform to predict what food you will like. Spoonshot’s service can be embedded into places like self-serve restaurant kiosks or even food delivery apps. Getting direct personal customer sentiment about meals via Brisky will help enhance Spoonshot’s recommendations. Spoonshot will be piloting Brisky up in Canada next before it makes its way down to the U.S.

Based in Bengaluru, India, Dishq Spoonshot has raised $560,000 in venture funding and has just completed it’s run at TechStars Farm to Fork accelerator.