I have spent time walking farms in Maharashtra and standing in the middle of vast regenerative operations in North America. Different geographies, different crops, different economic realities — and yet, one problem was always the same: the farmer, the input company, the processor, and the financier were all operating from different versions of reality. Decisions were made on intuition, paper, and seasonal memory.

That is the world farm data platforms are beginning to dismantle. And what is coming next is far more transformative than most people in agriculture — or business — yet appreciate.

We are moving from data collection to decision intelligence. The early promise of agri-tech was instrumentation — put sensors in the soil, drones in the sky, apps in farmers’ hands. That was necessary, but it was also just the foundation. The real shift now is from capturing data to making it useful across an entire value chain, in real time, with accountability built in.

Connective tissue

Think about what that means practically. When a World Bank-supported programme deployed across dozens of villages covering thousands of acres, the bottleneck is never the intervention itself — it is the inability to track, verify, and learn from what is happening on the ground. When a large agri-input company wants to understand whether its advisory is actually changing crop outcomes, it cannot answer that question without longitudinal, geo-tagged, verified farm-level data. When a food processor needs to assure a global retailer about provenance and growing practices, a third-party audit PDF is no longer sufficient.

Farm data platforms are becoming the connective tissue that solves all three of these problems simultaneously. And the ones that will matter are not the ones that just digitise the farm — they are the ones that connect farm activity to supply chain compliance, to ERP systems, to sustainability reporting frameworks, to carbon accounting. The platform that wins will be the one that makes a single field observation useful to ten different stakeholders.

There is also a sustainability dimension that is still underappreciated. We have engaged with farms ranging from community agriculture in rural India to large-scale regenerative operations across tens of thousands of acres in North America. In both contexts, the demand for verifiable, measurement-based sustainability data is accelerating. Regulators want it. Off-takers want it. Investors want it. The question is no longer whether agriculture must measure its environmental impact — it is who builds the infrastructure to do so credibly.

Operating system of future

The platforms that will define the next decade of agriculture are those that treat data not as a record of the past but as the operating system of the future. That means building for agribusinesses — not just farmers — because scale and accountability are only possible when the enterprise layer is involved. It means being framework-agnostic on sustainability, because DMRV standards are still evolving. It means designing for interoperability, because no single platform will own all the data.

India, in particular, sits at an extraordinary inflection point. With digital public infrastructure for agriculture beginning to mature, and a massive agri-input and food processing sector hungry for better decision-making tools, the opportunity to build world-class farm data platforms here — and export them globally — is real and time-bound.

Agriculture is one of the few sectors where digital transformation is still in its first chapter. The platforms being built today will determine who eats, what they pay, and whether the planet can sustain the next generation of food production. It is what the data already tells us — if you know how to read it.

The author is Founder & CEO, Khetibuddy 

Published on May 2, 2026