Only a decade ago, farmers in the US were collecting data on just 33% of available farmland. By 2023, that figure had shot up to over 70%. Over 40% of farmers now say that data has a major influence on their farm management decisions, up from just 10% in 2017.
This increase in data collection and use has boosted yields for the industry. But it has also presented a new issue of data management and reconciliation.
A lack of interoperability – which enables different systems to work together efficiently – is a big challenge and hindering the ability of the sector to benefit from the wealth of data generated in modern agriculture.
It can cause various issues such as data inconsistency and data fragmentation (where data from various sources such as farm machinery and weather sensors is stored in different formats or silos, making it difficult to access and use). It can also prevent data sharing and collaboration between different companies in the value chain resulting in lost opportunities for innovation and profit.
The interoperability problem
Overcoming these interoperability issues is therefore seen as vital to unlock the full potential of digital agriculture and facilitate more efficient, sustainable, and productive farming practices.
APIs (application programming interfaces) are attempting to solve the problem. But these have often lacked speed and quality.
An API is a set of rules and protocols that enables communication between different software applications. Leaf, which has just closed a $11.3 million series A round, and raised a total of $18 million in venture capital, claims to have created a single unified API where companies can easily access all their data.
In the past, says the company’s co-founder and CEO G. Bailey Stockdale, ag players attempted to build massive data infrastructure to manage and reconcile all of the weather, irrigation, imagery, tractor, and other data they were collecting.
Not only did this process require a substantial investment, it also took hundreds of hours of engineering resources and development time to build, operate, and maintain. With a single API, now they can focus on building new value with the data instead of building and maintaining messy integrations and data translation infrastructure.
Manual data entry for companies is expensive time consuming
Leaf was founded in 2018 “in response to feeling the pain of connecting agriculture data while attempting to build agronomy tools for his family’s farm,” said Stockdale.
Leaf’s customers include banks and insurers, input providers, biotechs, retailers and food companies. They collectively manage over one billion acres and require field operations and boundary data, irrigation details, weather, imagery and grain cart information.
“The companies are now reaching a scale where their manual data entry or in house data processing pipelines are not working anymore or becoming cost prohibitive,” said Stockdale.
“Leaf makes it easy and accessible for these companies to retrieve data from any farm in a single, consistent format so they can focus all of their effort building new value for their customers.”
A benefit that insurance companies are now offering to customers, for example, is insuring only the planted area of a field instead of the full property tax boundary. “They can determine the planted area by pulling in the planting data from the machines used to plant the field,” explained Stockdale.
“But the issue is that each machine stores the data in a different way and format. Leaf helps these companies access and translate the data, and then determine the planted area of each field for every season automatically.”
Leaf can help agronomy companies, meanwhile, retrieve active season and previous season data so they can analyse previous applications and yield results and then make the best recommendations for the current season with the current season data.
But who owns the data?
With data ownership a significant concern for farmers, Leaf never takes ownership of the data, and it is never made available to other users or accounts on Leaf without explicit permission.
“We believe that if farmers don't own and control their data, then it is unlikely that the promise of digital technology will be realised,” Stockdale stated.
How can digital ag deliver real impact?
The future of precision agriculture and data-driven farming practices hinges on two areas, he told us: data quality and workflows.
“We're building additional data cleaning and data quality tools so that customers can further prepare data from downstream workflows, such as AI, agronomy and carbon models on Leaf.
“Leaf will ship a complete environment where customers can run their own workflows on Leaf,” he added. “This allows companies to not only retrieve consistent, standardised data, but also run additional transformations, cleaning, analysis, and processing so that the output is customer-ready. Output can include data in a custom database schema, PDF reports, the results of a carbon model, field risk score, and more.”
New products in the offing
The fundraise, which was led by early-stage VC firm Spero Ventures, will allow Leaf to expand its product offerings and partnerships. “We're investing in shipping new products,” Stockdale said.
“Our upcoming products will offer new ways for companies to use Leaf including running end to end workflows on Leaf without needing to do any additional data processing on their side. We're also releasing a number of new data cleaning and quality tools that will further help companies using Leaf to package their data for analytics, AI models, and more.”
“We see Leaf as a driving force in agricultural technology, enabling agricultural service providers to deliver value to farmers on a broader scale," said Andrew Parker, general partner at Spero Ventures.
