Country club groundskeepers have long performed golf course reconnaissance on foot or cart, but now agriculture intelligence company Taranis is seeking to apply its three-layered aerial imaging and AI technology to maintaining crisp fairways and nattily trimmed greens.
Taranis uses satellite, plane, and drone imagery to monitor growing conditions and report problem areas before they worsen. The Tel Aviv-based company began working with farmers on high-volume commodity crops such as corn, cotton, sugarcane, soybean, wheat, and potatoes. They count clients in the U.S., Canada, Brazil, Argentina, Russia, Ukraine, and Australia.
The company is now working with one golf-course consulting company based in the U.S. and hopes to expand its business in the sport. The ultra-high resolution planes can scan a farm quickly, with each pixel representing roughly 10 centimeters. The drones are even more precise, touting a resolution of one-tenth of a millimeter per pixel. Taranis’s website notes “We can count beetles on the leaf!”
“It’s the same resolution as the human eye working in the field,” said Taranis co-founder and CEO Ofir Schlam, referring to the drone pictures. “We can see a golf ball with details. The more interesting detail in this respect is the crop health. We’re looking at leaf damage, decaying areas, and usually much before you can see it with the plane imagery.”
Estimates of annual golf course maintenance costs range from $800,000 (Club Benchmarking) to $1.2 million (Golf Course Industry) per year. Taranis, hopes to aid course superintendents in being more judicious and efficient in how they deploy resources by better understanding course health. The technology also draws on data from weather stations to help determine when conditions might make plants susceptible to certain diseases. This can lead to more preventive measures than reactionary ones.
The software platform helps create a dashboard of filters, allowing users to layer data and create zones for turf management. A mobile app allows a groundskeeper to walk the course and see Taranis’s scan-generated health index while at that same rough location.
Taranis’s founding team has backgrounds in AI, fintech, and virtual reality. Last year, the company acquired Mavrx, which specialized in ultra high-resolution imagery, and in November, Taranis closed a $20 million Series B round. In December, John Deere selected Taranis as one of three launch partners for its new Startup Collaborator program.
After collecting three years’ of data from farms, Taranis trained its deep learning algorithms to not only identify issues but also to offer remedies. Given that foundation, Schlam said he expects the software to need about one year to do the same for golf courses.
“In other crops where we’ve already had multiple seasons of a lot of data captured, we’ve already trained the software to give a recommendation, whether it’s a specific type of weed or a specific insect or disease,” he said. “If there’s overlap to the golf course industry of the same weeds, insects, or diseases, our algorithm can pick up on that automatically. But, probably, there are some different use cases as well.”
Schalm hails from the fourth generation of farmers in Israel that grew cotton, wheat, and bananas. Before technology existed, crop spraying decisions were predicated on educated hypotheses more than concrete data. Taranis enters to fill that void for fellow farmers and now for golf clubs, too.
“For crops, usually we look at the grass as a weed, and here, maybe different types of grass could be a weed relative to the original grass they want to maintain on the golf courses,” Schlam said. “There are differences, but much of it is the same building blocks.”