Tech permeates pretty much everything we do today, though most of us only experience the user-facing side of it. And while every app or program is hoping to tackle some major pain point or another, there are countless digital nuts and bolts that have to be put in place in order to help that software run smoothly behind the scenes.
By now, nearly every major industry has digital infrastructure solutions in the form of application programming interfaces (APIs) to help developers build interoperable software and apps.
Farming is no exception.
Los Angeles-based startup Leaf came out of stealth earlier this year with an API designed to make it easier for anyone to transfer data between hundreds of agriculture data sources through its one simple integration.
The funding process was relative smooth sailing for the startup despite Covid-19, according to CEO Bailey Stockdale. Helping the deal along was the immediate understanding among the investor syndicate about Leaf’s technology and the problems it hoped to solve.
“We sat down and they understood everything we said about APIs, food, and agriculture,” Stockdale told AFN.
“We’ve really focused on keeping industry-specific investors for this round, especially as we continue to grow and partnerships are so important to us. We have a development office in Brazil so it was also nice to bring SP Ventures into the round as well.”
Leaf plans to use the new funding to grow its team and to make the developer experience using its API as frictionless as possible. To do this it’ll bring in people with tech backgrounds in other industries – like recently appointed head of product Brandon Mensing, formerly of enterprise search company Elastic and data analysts Sumo Logic. He wrote about his journey in a blog post shortly after joining Leaf.
Making the switch from the mainstream tech sector to agrifoodtech was an easy decision for Mensing.
“I became cynical in some ways. There are all these brilliant people working on making ad targeting just a little bit better, but there are not enough people working on making food better,” he wrote.
“That’s what led me to really fall in love with the hypothesis [of Leaf]. It’s developer-focused and it’s trying to enable developers to bring about that change to make our food system better.”
When AFN spoke with Leaf in February this year about its launch, Stockdale said its biggest challenge would be obtaining buy-in from as many tech and service providers as possible. If only a handful of companies signed on to let Leaf access their APIs, then it would hardly have enough traction to go the distance.
Fortunately, buy-in has not been a problem.
Since launching, Leaf’s API has been used to build and expand a wide range of agrifoodtech platforms, including farm management software, lending and financing products, agronomic recommenders, food traceability apps, equipment maintenance forecasters, and marketplaces for land, inputs, and carbon credits, among others.
As demand has increased rapidly, so have the number of customers and potential avenues it can explore. Having too many opportunities is a champagne problem for any startup, but it also presents unique challenges.
“Obviously, we stay very focused on building products that work for everyone. We have to say no a lot to specific requests of existing functions, of looking into other industries too early, like indoor ag data,” Stockdale said.
“We say, ‘maybe in a couple of years.’ We have a lot of work to do outside first.”
When it comes down to it, however, Leaf’s medium is farm data. Applying it to other canvases isn’t necessarily as difficult as one may think. Stockdale offered machine operations data as an example: Whether a user is a lending operation wanting to track management on the farm, or an outcome-based pricing function that wants to validate on-farm activity, the back-end processes may not be so different.
Leaf’s primary challenge moving forward is overcoming the technical difficulties that come with developing APIs. It’s part of the reason the startup is so motivated to recruit the right people with deep expertise; it’s also why it is yet to see serious competition, according to Stockdale.
“There have been so many attempts at solving this problem and it is such a large problem. Most of these attempts have taken a business-level approach to solving it like big partnerships,” he said.
“There are plenty of standards for each type of data. At the end of the day, everyone has their own flavor for how they implement those standards. The groups get very political and no one is really taking a developer-first, product-centric approach. That’s how we are doing it.”