Farms produce a lot of data. From machines to irrigation systems, farms generate a lot of information that could be helpful to both them and the companies that serve them. Traditionally this data has been siloed across different formats, making it hard to read and build off of. Leaf is trying to change that.
New York-based Leaf is looking to build the Plaid of farm data, co-founder and CEO Bailey Stockdale told TechCrunch. The company takes a farm’s unstructured data, standardizes it, and loads it into an application programming interface (API). This allows Leaf customers, who range from crop insurance providers to agtech startups, to better utilize and build off the data. Customers pay for the service based on how many acres their data is harvested from.
Stockdale said he got the idea for the company in 2018 when the manager of his family’s farm told him that to decide which day would be best to plant seeds, he would go out at 6 a.m. to stick a thermometer into the ground. If it read 70 degrees, they would plant the seeds, if it didn’t, they wouldn’t. The anecdote stuck with Stockdale.
“Agriculture, it is a funny industry; it is simultaneously extremely sophisticated and totally antiquated,” Stockdale said. “My family has had a farm in Illinois for over 100 years. In that time, a lot of things have changed but some things haven’t.”
He said his first idea was to implement some technology to help the farm choose which crops to plant and when. He knew the farm had loads of data from their tractors and decided to start there, but the data he found, while plentiful, was incredibly difficult to decipher. He was curious how other tech companies were able to make any use of it.
“I just started calling people and asking them, ‘How do you do this?’ And no one had a good answer,” Stockdale said. “I said, ‘OK, maybe it is time to go find something else to do.’ There is no way anyone can break into this infrastructure; maybe it would be interesting to solve this. If I build this infrastructure layer so they can build these other use cases on top of it, there is a huge range of use cases that need this data.”
So Stockdale pivoted and Leaf was launched. He said building the product was tedious, as they had to reverse engineer each data file type separately. Leaf started selling in mid-2021 and now works with more than 80 companies, including agriculture giants like Bayer and Syngenta.
The startup just raised a $11.3 million Series A round. Stockdale said that despite the company’s traction, it took a few months of pitching to find investor interest because not many people understood just how bad the farm data problem was. But after four months, Leaf found its people. The round was led by Spero Ventures with participation for existing investors, including S2G Ventures, Radicle Growth and SP Ventures, among others.
Stockdale said Leaf is going to put the money toward building out a commercial go-to-market team. He added that he’s been on all of the sales calls for the last six months and that just isn’t sustainable anymore. Leaf will also use the capital to continue improving the product to better respond to new use cases from their customers.
One area is improving the quality and accuracy of the data; some of Leaf’s customers are looking to use it as input for AI prediction models surrounding things like when to plant which crops and where or how much they should treat a field with certain fertilizers based on prior years’ data. Leaf also has customers looking to go end to end with their data on Leaf, removing a cloud provider like AWS, something that Stockdale said the company wants to offer.
“Agriculture is a really interesting industry in itself because of the paradox of high sophistication and zero sophistication,” Stockdale said. “It’s great to get in with a lot of these customers and get started; now that we are rolling, we are kind of embedded. It’s a great industry and bringing something new to market is a little bit of a big bet. [Leaf is] an API in a fairly antiquated industry but it’s working.”