Picture the vegetable garden in your backyard — or, if you’re like this reporter, imagine you have a backyard, and that you have planted a vegetable garden in it — and that you have offered some of those vegetables to your neighbor.
“Great,” the neighbor says, “I’m having a dinner party in three months’ time, and I need six tomatoes to make my famous tomato soup. They must all be an acceptable size, have no discoloration or diseases and be equally ripe. I’ll be over in exactly three months to pick them up.”
Sounds stressful, right? Now imagine that your neighbor is your sales rep and their dinner guests are supermarkets from all over the country. Instead of six tomatoes, they need several tons of them — but to the same exacting specifications. And instead of a single tomato plant, you’re in charge of a 1.5 million square-foot greenhouse packed with millions of tomato plants.
Commercial fruit and vegetable growers do this sort of thing day in, day out. They predict a crop’s timing and yield months in advance, and then manage a huge amount of variables — humidity, temperature, CO2 levels, light, labor and disease to name a few — to deliver on those promises.
It’s exhausting work.
Today, a Seattle startup announced a $7.5 million funding round for its artificial intelligence technology designed to boost a commercial grower’s powers of prediction and ability to keep their promises.
You had to make one change in your recipe and then wait three to six months to figure out if it worked. Now, we can tell you in 12 hours.”
Pioneer Square-based iUNU (pronounced “you knew,” named after the ancient Egyptian city of light) is the company behind LUNA, a platform that uses computer vision to analyze images from fixed and mobile cameras within a greenhouse and measure crop health and growth rates.
“The metabolic rate of plants and leaves tells you almost everything you need to know about the health of the plant,” co-founder and CEO Adam Greenberg told Built In Seattle. “When you get multiple pixels per millimeter, you can measure growth rate and you can give a grower a day-over-day analysis. That used to be crop cycle-over-crop cycle.”
“You had to make one change in your recipe and then wait three to six months to figure out if it worked,” he said. “Now, we can tell you in 12 hours.”
LUNA’s cameras essentially give a Google Earth-like view of an entire greenhouse every few hours, and then the company’s computer vision technology scans for anomalies like discoloration or slowed growth rates.
Greenberg, who grew up around greenhouses and previously worked for Amazon, said this gives certainty to growers, who traditionally spend their days looking over the plants and taking notes on anomalies to identify potential problems.
Greenberg said iUNU, which Built In Seattle featured as one of its 50 Startups to Watch in 2018, is not trying to replace human growers with automated systems.
“There are fewer and fewer growers in the world today, and there has been massive growth in greenhouse square footage worldwide,” he said. “We don’t believe that the grower is going to be replaced — that’s not how we’re building this. This is about making a really good grower more scalable, more efficient and able to attack all their problems.”
Greenberg said the company will use the funding to work on the scalability of its processes and add to its headcount. The company currently employs around 35 people, most of whom work in Seattle, with offices in San Francisco and San Diego.
“We are really blessed in that we get to help people eat healthier, fresher, better tasting, better quality food,” Greenberg said. “People feel good about working on this problem.”
San Francisco-based firm BootstrapLabs and Columbus, Ohio’s NCT Ventures led the round.
