PlantJammer's flavor "neural network".

What are you going to have for dinner tonight? Maybe a big bowl of cheesy pasta (me), a reheated plate of leftovers, or, for the more ambitious, sous vide steak? Some people don’t need to put any pre-planning into their evening meals; they can just throw together whatever’s lingering in their pantry and crisper drawers, improvising with what’s on hand. For others who aren’t comfortable riffing in the kitchen or who don’t have time to grocery shop for a particular recipe, dinner is often something requiring little-to-no effort and decision making. That can mean meal delivery kits with pre-portioned ingredients, or, more likely, takeout.

Vegetarian recipe-generating app PlantJammer is out to help those with low kitchen confidence who want to cook healthy meals and reduce their food waste. The app creates custom recipes for users based off of whatever ingredients they have in their kitchen—then walks them through how to go from recipe to meal, step by step.

The app is able to do all of this thanks to AI, which maps out ingredients’ elements based on their aromas, creating a sort of flavor fingerprint. They then use the aromatic profiles to draw links between seemingly disparate ingredients, suggesting to the user which foods would go well together. In this way, PlantJammer hopes to gamify cooking with plant-based foods, making vegetarian cooking less of a chore and more of a convenient, efficient way to create a meal.

PlantJammer isn’t the only app using AI technology to suggest new flavor combinations. There’s Foodpairing, a tool which also finds and analyzes compatibility between different ingredients, which Haase turned to during his initial forays into cooking. However, while Foodpairing seems to aim its services at food industry professionals looking to create innovative and unexpected dishes, PlantJammer is a tool intended to help home cooks find their sea—er, kitchen—legs.

In fact, PlantJammer originally came about because the founder, Michael Haase, needed help throwing together plant-based meals for himself. Before founding the Copenhagen-based company in 2016, Haase worked consulting on sustainability and resource management at McKinsey and Danish biotech company Novasymes.

A few years ago Haase decided to work towards making his eating habits more sustainable by doing two things: stop wasting food, and eat less meat. He wanted to learn how to improvise in the kitchen, making use of any lingering produce before it went south—but he also didn’t want to spend 10,000 hours learning how to intuitively cobble together a delicious meal.

So what does an ex-consultant do? First, they collect data—lots of it.

“I decided to bootstrap that learning, so I turned to my background in econometrics,” Haase said. He took the neural network model, the workhorse of AI, and applied it to cooking. “I collected the intelligence of thousands of years of humans learning to cook and used that as a data set to create patterns and, ultimately, build a landscape of taste.” This analytical tool can look at big data and find patterns to determine which aromas—and thus, which flavors—will work well together.

As Haase describes, it, the neural network is a sort of color wheel for taste. At the center of the wheel is salt. On top of that the app must balance four components that, at least according to Haase, every good recipe needs: acidity, umami, crunchiness, and mouthfeel (oil). You can add balancing touches on top, like spiciness, too. This technology can lead to some surprising pair-ups. For example, Haase claims that bananas and zucchini are a match made in heaven—one I have yet to sample.

As of now, PlantJammer has a neural network of 3 million recipes and 1000 ingredients.

While the PlantJammer model gets really granular (mapping all 148 aromas in asparagus), they also generalize—quite a lot, in fact. “We say that, at the core, there are only 9 recipes in the world, and then there are infinite variations on those recipes which we can modularize,” said Haase. Judging from the PlantJammer app, these recipes include quiche, salad, pasta, and soup—a list that, as expected, generates some pushback for both what is included and what it doesn’t. But Haase isn’t one to adhere to tradition, especially in the kitchen. “Who says you can’t put curry in the risotto? That’s one learning of management consulting: just because people have been doing something one way, doesn’t mean it’s the only way to do it—or even the best way.”

I decided to put PlantJammer through the test and take a spin through its app (currently available only through their website).

A prototype of the PlantJammer app.

When you first open the app, you are met with a selection of suggested recipe templates ranging from Roasted & Toasted Soup to Asian Quiche to A Freestyle Pasta. If those templates aren’t for you, you can create your own recipe and just “Jam.” Never one to be pinned down, I decided to freestyle and was led to a new page by a tiny eggplant in shades playing the saxophone (his name is Eddie). From there, the app prompts you to select 1 to 3 ingredients from each of 4 categories: bulk (vegetables and plant proteins), splash (vinegar, citrus juice and oil), boost (chilis and aromatics), and topping (herbs, nuts, and other garnishes).

I selected chickpeas and broccoli from the bulk category, and the other columns immediately rearranged themselves, placing the AI-generated best pairings for my selections at the top. I selected tahini, harissa, and sunflower seeds, then threw in some yogurt for good measure. After I’d made my choices, I was led to a customized 6-step recipe that told me how to transform my selected ingredients into a finished dish: Chickpea Salad. The name itself was somewhat bland, but I was impressed with how detailed the recipe was; it gave clear cooking times for each ingredient and made each step seem simple yet doable. More importantly, it sounded like the end result would taste good. 

PlantJammer still has room for improvement, though, if it’s aiming for mainstream acceptance—especially within an American audience. Some of their ingredients are confusing to decipher (“soy bean sauce” and “artichoke hearths”), and then there’s the fact that users are limited by the ingredients options given. What if I have a can of lima beans, which isn’t on the PlantJammer list, but no chickpeas, which are? An experienced cook would know to go ahead and substitute one for the other, but the app is geared towards a more novice audience, who might not feel as comfortable with ingredient riffing.

Kinks in the system aren’t the only hurdles that PlantJammer is facing. Haase admitted that some potential angel investors decided to pass on the startup because the app purposefully doesn’t include meat in its ingredient list. And they never will. For Haase and his team the choice to bypass meat is crucial to the company mission to promote sustainable eating habits.

And they might have gotten lucky with their timing. Plant-based proteins are having a moment, racking up funding and huge social followings. While PlantJammer situates itself as separate from the processed, lab-made meat and meat alternatives of Silicon Valley, if it succeeds, it will probably be in part thanks to their efforts. By making plant-based diets and cultured meat not only acceptable but admirable and—dare we say it—cool, companies like Memphis Meats and Impossible Foods are paving the way for other startups in the meat-alternatives sphere. Though it’s an app, not a product, PlantJammer can only succeed if it has a hefty client base willing to eat vegetarian meals for at least for a few nights a month.

PlantJammer isn’t the only app bringing modular cooking—or cooking with dynamic recipe templates—to consumers. Connected cooking platform Innit (which celebrity chef Tyler Florence spoke about at last year’s Smart Kitchen Summit) recently launched an app similarly creates recipes built on whatever users have in the fridge. However, while PlantJammer starts from scratch and shifts its suggested ingredients based on consumer inputs, Innit uses recipe templates which users can customize and tweak. It seems modular cooking is a trend we’ll be seeing more of. In today’s world of customization and AI leveraging in the kitchen, it might be the way we’re moving.

“We want to make cooking convenient, not a compromise. That way, we can hopefully make a lot of people change their habits,” said Haase. Banana and zucchini stir-fry it is, then.

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