AI in Farming: The Hidden Opportunity for Coops

Jan de Vries · 2026-05-28

Small farms generate a constant stream of highly valuable data on pest outbreaks, treatment outcomes, climate effects, and soil responses. But after the season ends, those insights are lost. It doesn't have to be this way, says AI agricultural venture Greenda. Spain is Europe's leading citrus producer, supplying oranges, mandarins, lemons, and other fruits to markets across the continent. But the local agricultural cooperatives that grow your favorite citrus have a hundred responsibilities. They need to maintain consistent crop outcomes across thousands of small, geographically dispersed farms, provide farmers agronomic support, and ensure regulatory compliance — all at the same time. In practice, that means a small number of agronomists working for these coops operate under increasing pressure. They're expected to monitor, advise, and document decisions across hundreds of plots at once. That model is starting to strain. ### The Real Problem: Scattered Data and Hidden Trends Recognizing this squeeze, the Greenda team spoke to hundreds of farmers and visited both coops and plots. Here's what they heard, again and again. First, field coverage is structurally limited. Agronomists simply can't physically visit all farms at the frequency that pest and disease dynamics require to act preventatively. Monitoring becomes reactive rather than continuous, often based on sample visits instead of full visibility. Second, administrative and compliance burdens are on the rise. With upcoming regulatory shifts like the EU's digital farm notebook requirements, agronomists spend more time documenting decisions and treatments — and less time in the field where those decisions originate. Third, coordination is fragmented. Farmers often report issues through WhatsApp, phone calls, or other informal channels. Information is scattered across conversations, spreadsheets, and memory. That makes it tough to detect patterns across regions or synchronize interventions between neighboring plots. Agronomists and coop managers describe a recurring pattern: valuable field information exists, but it's not structured in a way that can be reused across seasons or aggregated across farms. Over time, that leads to predictable inefficiencies practically everywhere: overuse of pesticides, inconsistent treatment timing, and preventable crop losses that only become visible at harvest. In other words, there's plenty of scattered signals and data — but systemized intelligence is few and far between. And it's a problem that's inherently solvable.  ### How Greenda Builds a Coop-Wide Intelligence System Munich-based startup Greenda has innovated a workflow and data layer designed to sit between farmers and agronomic expertise. It solves this crucial problem for coops — and by extension, for our entire food supply system. Here's how it works: Farmers can submit simple photos of a crop issue through a WhatsApp-like app. The system helps structure incoming information using AI-assisted analysis, while a certified agronomist reviews each case before any recommendation is returned. That's an excellent feature — but what happens on the cooperative side is what makes it interesting. Instead of fragmented incoming messages, coops receive structured, traceable cases that can be prioritized, compared, and tracked over time. Agronomists can see where issues are emerging, how severe they are, and where intervention is most urgent. This transforms the workflow from individual troubleshooting into coordinated field management. > "Greenda's ambition is to be the platform that defines what good looks like for coops. Imagine territory-level intelligence that makes it possible to manage 400 plots with the same quality of attention you'd give 40. Zone-level pest maps, early outbreak signals, automated documentation — the kind of system that turns scattered data into actionable insights." — Chadi Nemer, CEO of Greenda ### Why This Matters for the Future of Food Here's the big picture: coops that adopt this kind of system don't just save time. They build a growing repository of structured, seasonal data. Over years, that data becomes a strategic asset. It helps predict outbreaks before they happen, optimize treatment timing, and reduce chemical use — which is better for the environment and for the bottom line. For agronomists, it means less time on paperwork and more time doing what they do best: helping farmers grow healthy crops. For farmers, it means faster, more accurate advice when they need it most. And for consumers, it means a more resilient, transparent food supply chain. The opportunity is hiding in plain sight. The data is already there — it just needs to be captured, structured, and put to work.