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Daily news and analysis about the food tech revolution

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A Week in Rome: Conclaves, Coffee, and Reflections on the Ethics of AI in Our Food System

Last week, I was in Rome at the Vatican for a workshop on the ethical and social implications of artificial intelligence and automation in our food system.

The workshop was part of an ongoing three-year NIH-funded project focused on the ethics of AI in food. It took place at the Vatican’s Pontifical Academy for Life, the same institution that played a pivotal role in 2020 in getting Microsoft, IBM, and others to sign the Rome Call for AI Ethics, a cross-sector commitment to develop AI that “serves every person and humanity as a whole; that respects the dignity of the human person.”

I was invited to provide an overview of AI in the food system to help set the stage for the day’s conversations, which featured Michelin-starred chefs, Catholic priests, journalists, authors, and professors specializing in ethics, artificial intelligence, and more. I walked through some of the developments I’ve seen across the food system—in agriculture, next-gen food product development, restaurants, and the home. As I wrote recently for The Spoon, today “every major food brand has made significant investments — in people, platforms, products — as part of the AI-powered transformation.”

I posed questions like: What happens when AI dictates what we eat? Or if it engineers the “perfect sandwich”—something so addictive it floods demand and strains supply chains, as Mike Lee has imagined? What does it mean when a company builds a proprietary food AI trained on global culinary data? Does that dataset become the intellectual property of one corporation? And if AI can tailor nutrition down to the molecule, who controls those insights?

These are not just technical questions. They’re questions with deep implications for humanity.

One thing was clear throughout the day: everyone in the room recognized both the promise of AI as a tool for addressing complex challenges in the food system, and the risks posed by such a powerful, society-shaping technology. Among the questions raised: How do we balance the cultural and inherently human-centered significance of food—growing it, preparing it, sharing it at the family dinner table—with the use of AI and automation across kitchens, farms, and wellness platforms?

Above: The signed Rome Call for AI Ethics

As some attendees expressed, there’s a growing concern that the “soul” of food—its role in connection, tradition, and creativity—could be lost in a world where AI plays a central role.

For obvious reasons, being at The Vatican and in Rome at this time was a bit surreal, as the two days of the workshop and the Vatican came during the same week that the College of Cardinals gathered to select the next Pope after last month’s passing of Pope Francis.

As we wrapped up our discussions, the Conclave began. And just as I was leaving Rome, white smoke rose from the chimney of the Sistine Chapel, signaling that a new pope had been chosen.

In his first address, Pope Leo XIV made it clear that he is thinking deeply about AI’s role in society, so much so that he chose his name in homage to a previous pope who guided the Church through an earlier technological upheaval.

“… I chose to take the name Leo XIV. There are different reasons for this, but mainly because Pope Leo XIII, in his historic encyclical Rerum Novarum, addressed the social question in the context of the first great industrial revolution. In our own day, the Church offers to everyone the treasury of her social teaching in response to another industrial revolution and to developments in the field of artificial intelligence that pose new challenges for the defence of human dignity, justice and labour.”

Also present at the workshop was our friend Sara Roversi, founder of the Future Food Institute. The Spoon and Future Food Institute co-founded the Food AI Co-Lab, a monthly virtual forum where experts across disciplines explore the intersection of food and AI.

Sara, Tiffany McClurg from The Spoon, and I grabbed coffee at a small café in Rome to reflect on the workshop and what it means for our ongoing work. We launched the Food AI Co-Lab in early 2024 as a space to gather our communities and talk through how AI is impacting the food system. So far, much of the conversation has focused on education—helping people understand what AI is and how to thoughtfully implement it in their organizations.

But we all agreed: the world has changed rapidly since we began. Nearly everyone is now seriously considering how to integrate AI into their companies, institutions, or personal lives. And so, the Co-Lab needs to evolve too. Our hour-long sessions, often featuring guest speakers, have been great for tracking innovation, but now it’s time to elevate the conversation. Ethics. Labor. Equity. Sustainability. These aren’t side topics—they’re central to how AI will shape the future of food.

If the world feels more chaotic than ever, one thing is certain: we need to prepare for faster, more unpredictable change. At the first workshop two years ago, most attendees were just learning about AI. There was plenty of fear about a runaway system invading the food chain.

Today, there’s greater recognition that AI is inevitable and that it can be a powerful tool for solving some of the food system’s most complex problems. There was even a bit more optimism this time.

But above all, there’s a clear understanding that we still have a long road ahead to strike the right balance: embracing AI as a tool while preserving what makes food so deeply human, so critical to our culture, communities, and shared existence.

You can learn more about the Food AI Ethics project led by Cal Poly at San Luis Obispo [here]. If you’d like to join us for future Food AI Co-Lab events, you can sign up via our LinkedIn Group or The Spoon Slack. We’ll keep you updated on upcoming events and speakers.

How ReShape is Using AI to Accelerate Biotech Research

“Biology is so complex, it’s like the most complex piece of technology in the entire world,” said Carl-Emil Grøn. “There’s nothing that’s remotely close. You start from one cell and then you grow into a Michael Wolf who’s now hosting a podcast together with me. That is crazy when you think about it.”

When this former single-cell turned human podcaster caught up with the CEO of ReShape Biotech this past week on The Spoon Podcast, Grøn’s excitement over the miracle of biology and biotech was palpable. But he made it clear that wasn’t always the case. In fact, when he first saw his university friends building a tiny robot for a biotech professor, he told them it was a waste of time.

“I was sure this was not something anybody would need,” Grøn recalled. “But then I started getting a little bit curious about it.”

That curiosity eventually led him to co-found Reshape Biotech, a Copenhagen-based startup that’s automating the slow, manual processes still common in biological research. While new technologies like automation and AI have transformed fields like software and transportation, Grøn saw that many biotech labs were still stuck in the past.

“We have self-driving cars and AI tools that can do crazy things, but biotech workflows look kind of like 1990.”

Reshape’s platform combines robotics, computer vision, and machine learning to help food and biotech companies run hundreds of thousands of lab experiments. The ReShape system uses cameras to monitor petri dish experiments, running AI-powered image analysis on mold growth or bacterial reactions, and helping researchers rapidly test natural preservatives, food dyes, and more. This means research that once took months or years can now be done in days or weeks.

“We have this one company that used to do between like 800 and 1000 experiments per year,” Grøn said. “Whereas with our platform, they’re running more than 450 thousand every single year. So you get this like complete step change difference in how much you can actually do.”

That kind of increase in throughput is becoming more critical as food companies face new pressures, whether that’s from consumers demanding clean labels to a new administration looking to restrict artificial ingredients.

“Nowadays, they (food companies) are going to have to do it right,” he said. “When regulatory pressure comes to push, you have to do it.”

Grøn believes the companies that embrace AI and automation today will have a major advantage tomorrow.

“If we do this well, these companies will be set up to basically take the lead on developing new products in the future,” he said. “They will be the ones who have the data that’s necessary to make AI models that actually work.”

As a startup, Grøn says ReShape is focused on getting their tools into the hands of big players like Unilever and Nestlé, but long-term he has a broader vision, which is to open up the world of biotech data to help make companies big and small more productive.

“My dream, maybe one day, is to open source all of this data and just make it available to the world,” he said. “Because I do think the world needs something like this.”

Grøn was vague on when exactly that would happen, as he said first he has a few constituencies (like his investors) which he needs to serve first. But over the long term, he’s excited about the possibilities.

If you’d like to listen to my full conversation with Grøn, you can click play below, or find it on Apple Podcasts, Spotify, or wherever you get your podcasts.

The Future of Biotech Discovery in the Age of AI

Next-Gen Fridge Startup Tomorrow Shuts Down

Fridge startup Tomorrow will not live to see another day.

Last week, founder Andrew Kinzer cited the difficult funding environment for hardware startups and the headwinds around the uncertainty in tariffs in a post on LinkedIn.

I knew this would be a massive challenge. Consumer hardware is notoriously difficult, and solving shelf-life extension would require a scientific leap. I understood then that I could swing and miss, but I always felt that if I did, I could still be proud I gave it a shot.

In the end, though, timing is everything. Right now — maybe more than at any point in the past decade — consumer hardware is a tough sell for investors, and fluctuating tariffs only add more risk to the equation.

The company’s website also features a going-out-of-business message, citing the same reasons Andrew did in his post and thanking those who helped out along the way:

After much consideration, we’ve made the difficult decision to shut down Tomorrow.

When we set out to build a next-generation fridge—one that could extend the life of your fresh produce, reduce waste, and help make healthier eating easier—we knew we were taking on an ambitious challenge.

Unfortunately, the current climate for consumer hardware—especially for capital-intensive, science-forward products like ours—has made it incredibly difficult to bring something like this to life.

Though we won’t be moving forward, we’re deeply proud of the work we did and grateful for the community that rallied around our vision.

To everyone who signed up, supported us, or offered guidance: thank you.

When I first covered Tomorrow last year, I was admittedly excited to see a new company take a shot at reimagining such a moribund category. How we store food hasn’t seen nearly as much innovation around how we grow, cook, shop and make food, and so any new startup taking a shot was a good thing as far as I was concerned.

It’s hard to say whether Tomorrow would have succeeded if they had been able to raise funding, in part because I’m not sure exactly what the company’s key technology differentiation was. That’s because the company kept their product details close to their vest, pointing to its intention to keep fresh food fresher longer, leveraging AI and other technologies when asked about specifics.

I can also say I’m not surprised by the reasoning behind the shutdown. Hardware is a hard category to build a business in normal times. Throw in tariffs, which would no doubt complicate the supply chain and manufacturing strategy of a refrigerator startup, and significantly raise the final price of the product. Creating an entirely new product in this space almost becomes a fool’s errand, at least in the current environment (which is also probably why raising funding for this company proved extremely difficult).

From Starday to Shiru to Givaudan, AI Is Now Tablestakes Across the Food Value Chain

Back in the early days of the cloud computing revolution, my former employer, GigaOM, hosted perhaps the biggest and most influential conference on the topic called STRUCTURE.

One of the phrases that has stuck with me from those days is “data is the new oil,” which I heard declared from the STRUCTURE stage more than a handful of times. At the time, big data technologies were leveraging machine-learning-driven analytics tools to create new correlations and insights from disparate datasets faster than ever before. Those who controlled the data — and could mine it effectively — wielded enormous power.

Now, nearly two decades into the cloud era and three years after the AI “big bang” sparked by the launch of ChatGPT, those early days seem almost quaint by comparison. New AI-powered tools and companies are emerging every day. While much of the “data is the new oil” rhetoric back then felt like spin, today we’re seeing real, transformative progress, especially in new product development.

Food is no exception.

Take the news from Shiru this past week. The company, which uses AI to sort through plant-based food building blocks, announced that it had scaled its first AI-discovered products: OleoPro and uPro. These new approaches to identifying proteins — particularly oleogel structurants (structured fat systems) — are designed to support large-scale production.

As Shiru CEO Jasmin Hume put it:

“This moment is a turning point not just for Shiru, but for the food industry. Even though oleogels have been explored for years (there are over 500 publications on them in the last decade), commercially scaled examples have been elusive — until now. Our AI platform helped us identify the right proteins, but that was only part of the story. Our team then engineered a scalable and entirely new process for producing those proteins with the precise performance attributes required to succeed in real-world formulations.”

But it’s not just next-generation ingredient discovery. New CPG brands are also using AI to decipher early consumer signals and connect the dots before anyone else can launch the next big product. One example is Starday, a startup that recently raised $11 million. Starday uses AI to sift through millions of data points from social media feeds, surveys, point-of-sale data, and more to identify emerging opportunities in food that could lead to future hits.

“Imagine if you had 10,000 consumer insights folks that are watching every video on internet, typing up what’s being said, tagging it, and then kind of building these regression models around how these trends are happening,” said Starday CEO Chaz Flexman in a recent interview with The Spoon. “We’re trying to do that on steroids. We take in about 10 million pieces of content every week, which is very significant.”

In the early big data heyday, companies could look at things like trending tweet mentions. Today, companies like Starday are able to dive into video content, extract context much faster, and build predictive intelligence to guide new product development.

Shiru and Starday are just two examples making headlines recently about how AI is reshaping the food industry. Others are innovating across different parts of the food value chain — from manufacturing optimization (Keychain) to intelligent automation (Chef Robotics), all the way back to the farm with companies like Agtonomy.

Even century-old flavor companies are getting into the act. This past week, Givaudan announced Myromi, a handheld digital aroma delivery device that leverages an AI platform called ATOM.

In short, AI is enabling both startups and established players to move much faster.

And they’re going to have to. In the current MAHA moment in the US, companies are urgently reevaluating ingredient lists and being forced to replace ingredients like food dyes and sugars. This new urgency is adding to what many had already been doing as they see climate change slowly but surely impacting how and what they can source for their products.

Back in 2010, there was a lot of talk about using big data to create better products, but no one was seriously using AI to build food products at that point (heck, Watson, after all, hadn’t even become a chef.) Today, every major food brand has made significant investments — in people, platforms, products — as part of the AI-powered transformation.

In other words, if data is the new oil, it’s now clear that AI is the engine of innovation that is accelerating and driving change across every part of the food system.

Join Us Today as We Discuss How Artificial Intelligence Will Impact Culinary Creation

Admit it: you’ve probably played around with making recipes using AI. At this point, most of us have.

If you’re like me, the early results were… rough. But over time, general-purpose LLMs have become surprisingly good at whipping up recipes. Still, there’s a long way to go before AI becomes a true sous chef in our kitchens, and plenty of questions remain about where this is all going.

To help us explore what’s next in this month’s edition of our Food AI Co-Lab, we’re joined by two people who’ve been working at the intersection of AI and cooking for nearly a decade: James Briscione and Lav Varshney, co-creators of Chef Watson—the world’s first culinary AI. Their latest project, CulinAI, is an AI-powered app designed to create personalized meal plans.

Want to join the conversation, ask questions, and see where AI cooking is headed? Register for today’s Food AI Co-Lab here.

ClearCOGS Raises $3.8M its AI-Powered Forecasting Software That Helps Restaurants Reduce Waste

AI-powered restaurant forecasting startup ClearCOGS has raised $3.8 million in an oversubscribed seed round led by Closed Loop Partners, with participation from Myriad Venture Partners and Hearst’s Level Up Ventures. The funding includes $2.3 million in new capital and the conversion of $1.4 million in pre-seed investments. The company’s software provides predictive analytics to assist operators in making decisions around food prep, ordering, and staffing, with an emphasis on reducing food waste and improving operational efficiency.

Company CEO Matt Wampler told The Spoon that he came up with the idea of ClearCOGS during the pandemic. He’d been being laid off and was exploring coding and analytics, when he discovered his cousin who ran a Jimmy John’s franchise was still using a decade-old Excel forecast. Wampler wondered if AI could help create a better predicitve forecasting tool, and before long he had teamed up with Osa Osarenkhoe to build a solution that uses machine learning and time-series forecasting that currover 100 million data points a day.

When ClearCOGS participated in our first virtual Food AI Summit a couple of years ago, Osa and Matt had started experimenting with leveraging large language models (LLMs) like those from OpenAI to create an interface for their forecasting tool. I asked Matt how those experiments with LLMs had gone.

“We did a whole big thing with it… It didn’t go well,” said Wampler. “And it wasn’t from a technical standpoint. It was from the standpoint of the restaurant brands we were talking to… they were like, ‘Look, my general manager can either just get on and play with your AI bot and it’ll tell them, or you can just send it to them? Just send it to them.’”

Wampler said the LLM interface wasn’t the problem. It was just that operators didn’t want to interact with it at all. Instead, they just wanted the answers delivered to them, simply and directly, through email and integrations with solutions from Toast or SevenRooms. This experience reaffirmed Wampler’s belief that proprietary forecasting (and not LLM-powered conversational AI) is where ClearCOGS can deliver the most value.

“LLMs are kind of a commodity at this point. Proprietary data sets are what really matters… You still have to be able to provide a fundamental business value before that AI is really helpful.”

While many platforms offer dashboards or raw analytics, ClearCOGS focuses on delivering direct, decision-ready insights to restaurant managers. This is central to how he differentiates the company:

“If you’re a brand, you probably have 20 or 30 questions that you have to answer every day… We go really deep on those and provide a systematic way of delivering those to your operators every day.”

With the new capital, ClearCOGS plans to accelerate its product development and customer acquisition efforts, with an emphasis of better positioning itself in the food service sector. The company currently serves a customer base of 100 brands in four countries, and Matt says they plan to continue building a lean team, prioritizing automation and AI over headcount.

Food Assembly Robot Startup Chef Robotics Raises $43M Series A as it Reaches 40 Million Meal Milestone

Chef Robotics has raised $43.1 million in a Series A round to accelerate deployment of its AI-powered food assembly robots, the company announced today. The funding brings the San Francisco-based startup’s total capital to over $65 million, including equipment financing. Avataar led the round, with participation from Construct Capital, Bloomberg Beta, and others.

Founded in 2019, Chef Robotics is building what founder and CEO Rajat Bhageria calls an “AI platform for food.” Rather than building a single-purpose robot, Chef’s system is designed to work in diverse food production environments—learning and adapting through software to new tasks like portioning, topping, or filling.

When I first got a peek at Chef’s system last year, I was intrigued because the company had struck a balance that seemed to elude many food robotics startups. While startups in this space seemed to make either high-volume solutions with limited customizability or use off-the-shelf robotic arms that aren’t made for true high-production, Chef has built a flexible and scalable robotics platform that can be customized for any number of high-volume food production environments.

That’s because while many robotics companies focus primarily on hardware, Chef’s approach centers on a software layer that enables “Embodied AI”—giving physical robots the intelligence to operate autonomously in real-world conditions. Chef’s system combines a robotic arm with AI models trained on millions of real-world examples. These models, powered by production data from early customers like Amy’s Kitchen and Fresh Prep, allow the robots to generalize across new ingredients and dishes. To date, Chef Robotics has helped assemble over 40 million meals.

From the company’s announcement: When we thought about starting with restaurants, we ran into the chicken and egg problem – to enable robots that are flexible enough to add value, we need a highly capable AI, but to get a highly capable AI, we need real-world training data from the customer sites…. Thus, we decided to initially deploy robots in high-mix (read as highly flexible) food production and manufacturing environments where Chef could partially automate a food operation and thus add value in production to customers without requiring 100% full autonomy from the get-go. We built Chef’s systems on modern advancements in AI to make them highly flexible and adaptable enough to “pick” and plate almost any ingredient, no matter how it’s cut, cooked, or grown; this makes them an ideal solution for assembling or plating food.  

The new capital will support scaling up deployments and building out Chef’s sales and marketing teams. The company is currently active in the U.S. and Canada, with plans to expand into the UK next year.

The Food & Retail AI Rollup Continues as Crisp Buys Shelf Engine

Crisp, a New York-based retail data company, has acquired Seattle-based startup Shelf Engine. Founded in 2016 by Stefan Kalb and Bede Jordan, Shelf Engine specializes in using machine learning to optimize ordering processes for perishable goods, with the goal of reducing costs and minimizing food waste. The platform is now in use across more than 7,000 stores. Terms of the acquisition were not disclosed.

Shelf Engine was one of the earliest adopters of AI technology in food retail aimed at reducing waste and optimizing fresh food ordering. Kalb, who launched a food distribution business at 23 and holds degrees in actuarial science and economics, developed the idea during a 2014 ski trip with his friend and engineer Bede Jordan, a former Microsoft HoloLens developer. The pair questioned why food industry processes and systems remained outdated:

“Could we create a platform that enables retailers to buy food and eliminate significant waste? Could we create a platform that eliminates redundant busywork between vendors and retailers? Could we create a more perfect marketplace?”

These questions led Kalb and Jordan to develop a product designed to drive the food industry towards greater efficiency through technology.

Kalb reflected on the deal on LinkedIn:

“What started as a side project with my good friend Bede turned into a platform that’s now in over 7,000 stores across the U.S., helping reduce millions of pounds of food waste. It’s been eight years of wild highs, humbling challenges, and so much growth.”

Crisp plans to integrate Shelf Engine’s advanced algorithms into its commerce platform. The company believes the integration will help its retailer customers optimize in-stock inventory, improve shelf management, and drive revenue in an increasingly margin-sensitive retail environment.​

“Joining forces with Crisp allows us to scale our proven technology and deliver greater value to retailers and their supplier partners,” said Kalb. “Together, we will set a new standard in forecasting and inventory management, helping our customers thrive even in challenging market conditions.”​

This news is yet another in a series of acquisition announcements for early pioneers who are building technology leveraging AI to optimize different parts of the food value chain. Earlier this month AI Palette was gobbled up by trend forecaster Global Data, and before that Spoonshot was acquired by Target. Like other buyers in these deals, Crisp provides predictive intelligence software and services and is buying Shelf Engine to improve their AI insights capabilities.

Unlike these previous deals, Crisp and Shelf Engine focus more on retail and supply chain commerce optimization, which is one of the areas that is seeing the greatest leaps forward in productivity and cost-reduction. My guess is Afresh, which is similar to Shelf Engine and remains independent following its $115 million in series B funding in 2022, may also be one of the next companies gobbled up as bigger software and supply chain players look to add AI capabilities to their products.

Bridge Appliances Deploys Egg-Making Robot at First Customer

Five years ago, the cofounders behind Bridge Appliances stood in line at a busy breakfast cafe. As minutes ticked by, frustration turned into inspiration. They wondered: What if the preparation of eggs could be automated? That simple question led to the creation of OMM, a countertop egg-making robot. Now, half a decade later, the Bridge team is back in a coffee shop, deploying their robot for their very first commercial customer, Beantrust Coffeebar in Beverly, Massachusetts.

Bridge cofounder Connor White recently described spending the past two months embedded at Beantrust, collaborating closely with owner Erik Modahl and his team. According to White, working alongside baristas, listening to customers, and absorbing the café’s unique culture and operational flow allowed Bridge to tailor OMM’s integration precisely to Beantrust’s specific needs.

As I wrote last year, OMM cooks two eggs in roughly two minutes, enabling Beantrust to serve around 60 eggs an hour. White notes they’ve already seen promising results, with the new sandwich lineup boosting average ticket values by 15%. Currently, one in five customers chooses to add a freshly made sandwich to their coffee order (and that number continues to climb).

This marks a significant milestone for Bridge, which raised $2 million in seed funding from Steve Papa, one of Toast’s earliest investors, in 2021. Moving forward, Bridge is likely to see more growth among small coffee shops or similar establishments that lack full kitchens or grill cooks but still wish to offer breakfast. However, they will need to raise considerably more funding to scale effectively, or they could be a potential attractive acquisition candidate for a company such as Middleby.

The Spoon Discusses The Current State of AI Workflows With AI for Humans’ Gavin Purcell

In this latest edition of the Spoon Full of AI Podcast – the podcast where I talk to leaders who are using AI to transform their business (in food and beyond), I catch up with AI for Humans host Gavin Purcell to discuss the rapid advancements and complexities emerging in artificial intelligence. We talk about Google’s new Studio AI platform and its potential as an all-in-one solution for content creation, and we both have reservations about Google’s use of an older image generation model (Gemini 2), highlighting its limitations compared to newer versions like Gemini 3.

AI Studios? with Gavin Purcell

Gavin talked about the transformative shift from traditional file-based computing to generative AI, as noted in Nvidia CEO Jensen Huang’s recent keynote. He make a great point talking about how this will be difficult for mainstream adoption, where users expect simplicity akin to social media sharing, yet AI tools remain complex and imperfect.

We both talk about our frustrations with current AI workflows, where we compared the cumbersome nature of local models like Comfy UI to more streamlined platforms such as Ideogram and MiniMax. In the end, we both want a unified, user-friendly AI platform but recognize that technical and creative challenges remain significant hurdles.

We also discuss who we predict will be winners in the AI platform space (no spoilers!), so make sure you listen to see who we pick!

You can watch the full video above or click play below, or find this podcast in Apple Podcasts, Spotify or wherever you find your podcasts.

Marine Biologics Debuts SuperCrudes, the ‘World’s First Programmable Biomass’

This week at Future Food Tech, Marine Biologics will showcase its technology—a platform that digitally maps the biochemistry of seaweed and its properties – which the company claims has created what is the world’s first programmable biomass.

According to the company, its proprietary cheminformatics platform, MacroLink, maps the molecular compositions of seaweed and stabilizes them into customizable, liquid-based macroalgae solutions called SuperCrudes. SuperCrudes, which are liquefied blends derived from seaweed harvested from specific geographic locations, are analyzed to document their mineral, protein, and carbohydrate compositions. This process allows Marine Biologics to benchmark each product similarly to how oil refineries grade petroleum based on extraction origin.

The company was founded by former crypto industry executive Patrick Griffin, who told Wired he transitioned from crypto to building a platform that could digitally understand seaweed after a surfing accident caused him to reevaluate his priorities.

Ironically, the accident reignited his enthusiasm for the ocean. Griffin recognized a gap in the climate resiliency market concerning fundamental building materials. Even if all other global climate resiliency efforts—such as vehicle electrification and renewable energy investments—were successful, products would still be largely built upon plastics or other petroleum-based materials.

“The chemicals and materials that we use today are, by and large, built on petroleum,” Griffin says. “It’s the last piece of the puzzle you’ll really have to chip away at to make a significant impact.”

Griffin believes his company can substantially reduce the costs and variability traditionally associated with bio-based sourcing by standardizing seaweed extracts into reliable and predictable ingredients.

The broader macro-trend of computational biology is one we’ve been following closely here at The Spoon. Examples include using AI to accelerate pathways toward gene-edited seafood or tracking startups like Shiru, which aim to build food input discovery engines by mapping food’s biological building blocks. Marine Biologics’ technology is particularly intriguing because it closely connects to a specific natural biomass that has previously struggled to gain traction in consumer products—both food and otherwise—due to limited understanding and internal expertise within larger CPG brands.

With this coming-out party for its Macrolink platform, the California-based startup is hoping to change all that, at the same time becoming both a formulation platform as well as a provider of inputs (SuperCrudes) to CPG brands looking for more sustainable inputs.

AI-Powered CPG Trend Forecaster AI Palette Gets Gobbled Up

AI Palette, a company that uses AI to help CPG brands anticipate consumer tastes ahead of market trends and better predict new product success throughout their lifecycle, announced today it was acquired by market research company GlobalData.

AI Palette launched within the last decade alongside a cohort of startups—including Analytical Flavor Systems, Tastewise, and Spoonshot—that began utilizing machine learning and big data analysis tools. These tools enabled CPG brands to move away from traditional product ideation and surveys, uncovering hidden insights more rapidly through AI. Like many similar startups, AI Palette started talking up their generative AI bona fides over the past couple of years.

“The integration of AI Palette supercharges our ability to help CPG brands innovate smarter and faster,” said Mike Danson, CEO of GlobalData Plc. “Together, we are setting a new standard for AI-driven intelligence in the consumer space.”

In some ways, this deal resembles Spoonshot’s acquisition a little over a year ago, when legacy market intelligence provider Target Research Group acquired the AI startup. GlobalData Plc, which places greater emphasis on pure data analytics than Target, is a company that has grown primarily through acquisition. From what I can see, AI Palette represents GlobalData’s first pure-play AI company deal.

With most major food-brand CTOs currently exploring—or being directed—to leverage AI, it seems likely that acquisitions of vertically specialized platforms will continue over the next 12-24 months. Consultancies and market intelligence providers will probably lead this trend as incorporating AI into intelligence toolsets becomes essential to maintaining relevance..