Farms generate a lot of data. From machinery to irrigation systems, farms generate a ton of information that's useful to both the farms themselves and the companies that service them. Traditionally, this data has been siloed in different formats, making it difficult to read and organize. Leaf is looking to change that.
New York-based Leaf is looking to build a Plaid for farm data, co-founder and CEO Bailey Stockdale told TechCrunch. The company will take unstructured farm data, standardize it and load it into application programming interfaces (APIs). That will allow Leaf's clients, which range from crop insurers to ag tech startups, to better use and build on their data. Customers will pay for the service based on the number of acres the data is collected on.
Stockdale says the idea for the company came about in 2018 when his family's farm manager told him he would go outside at 6 a.m. and stick a thermometer in the ground to determine the best day to plant seeds. If it read 40 degrees, he'd plant the seeds; if it didn't, he wouldn't. The anecdote has stuck with Stockdale.
“Agriculture is a strange industry; it's incredibly sophisticated and completely outdated at the same time,” Stockdale says. “My family has been farming in Illinois for over 100 years, and a lot has changed in that time, but some things remain the same.”
The initial idea, he says, was to introduce technology that would help farms decide which crops to plant and when. He knew that farms had a lot of data stored from their tractors, so he decided to start there, but while the data he found was rich, it was very hard to decipher. He was curious to see how other technology companies could leverage it.
“I just started calling people and asking, 'How do you do this?' and nobody gave me a good answer,” Stockdale says. “I said, 'Okay, maybe it's time to look for something else.' Nobody has a way to penetrate this infrastructure. This could be interesting to solve. If we build this infrastructure layer so that we can build other use cases on top of it, there are a whole range of use cases that need this data.”
So Stockdale pivoted and started Leaf. Building the product was tedious, he said, because it required reverse engineering each data file type individually. Leaf began selling in mid-2021 and now works with more than 80 companies, including agriculture giants like Bayer and Syngenta.
The startup just raised $11.3 million in a Series A round. Despite the company's traction, Stockdale says it took months of pitching to get investors interested because not many people understood how serious the farm data problem was. But four months later, Leaf found its people. The round was led by Spero Ventures, with participation from existing investors including S2G Ventures, Radicle Growth and SP Ventures.
Stockdale said Leaf plans to use the funding to build out its commercial go-to-market team. He added that for the past six months, he's been on all of the sales calls, but that's no longer possible. Leaf also plans to use the funding to continue improving its product to better serve new use cases from customers.
One area is improving data quality and accuracy. Some of Leaf's customers are looking to use the data as input for AI predictive models that, based on historical data, tell them what crops to plant when, where, or how much of what fertilizer to apply to a field. Leaf also has customers who want to manage their data end-to-end on Leaf, rather than using a cloud provider like AWS. Stockdale says that's what the company wants to offer.
“Agriculture is a really interesting industry in itself because it has this contradiction of being highly sophisticated and unsophisticated,” Stockdale said. “It's been great to engage with so many customers and get the business going. Now that the business is taking off, I'd say we're kind of established. Agriculture is a great industry and bringing something new to the market is a bit of a big gamble.” [Leaf is] It's a pretty outdated industry API, but it works.”