Farmdar is an agritech that uses AI and space technology to create crop insights at scale. These insights are not only highly accurate, but also designed to be actionable by agribusinesses across the world, to enable better decision-making through robust data and AI insights.

Farmdar helps agribusinesses, and agricultural organizations such as sugar mills, input companies like fertilizer, seed and crop protection businesses, and food companies, plan better and, grow better by transforming satellite and field data into actionable intelligence.

Headquartered in Singapore, with offices in Thailand, Pakistan and Brazil. Farmdar operates globally, with teams and customer deployments across APAC, Latin America and Africa.

Farmdar combines multiple types of satellite data, weather data, soil data, field data, and proprietary AI models to create actionable crop intelligence at scale.

Farmdar consistently achieves 90–95% field-validated accuracy across crop identification, yield prediction, harvest monitoring, and weekly crop monitoring insights.

Yes. Farmdar’s technology is built for scalable, multi-country deployment and has analyzed 500 million+ acres using AI and satellite-based analytics.

CropScan provides large-scale crop intelligence, helping agribusinesses optimize planning, pricing, procurement, and supply chain decisions through accurate crop data.

YieldPro enables field-level crop monitoring, helping farmers and agribusinesses optimize inputs, increase yields, and reduce waste through precise, data-driven insights.

AgriChain helps agribusinesses digitize farming operations and enables financial institutions to provide fair financing to farmers through structured field and operational data.

CropScan delivers large-scale crop data including hectarage estimation for multiple crops simultaneously, yield prediction, sowing time analysis, harvest monitoring, detecting water bodies, barren land, available arable land and historical comparisons.

YieldPro enables field-level monitoring through historical productivity zone mapping, germination monitoring, plant health and stress monitoring, nitrogen uptake reporting, irrigation scheduling and soil organic matter comparison.

AgriChain digitizes farm operations through field data logging, boundary mapping, workflows, approvals, and media uploads, supporting structured farm management. The Firebird module effectively delineates fields and creates digital boundaries using AI with a very high accuracy of 98% and can be deployed across vast areas.

Pricing depends on scope, geography, product modules selected in the enterprise subscription, data frequency, and customization requirements.

After establishing contact with Farmdar through the many channels available (click here), the first step is a use case assessment with Farmdar’s Business Team. We understand that Farmdar’s technology may be a new piece of an organization’s digital transformation puzzle, and therefore, the focus in the early engagements is to make sure we understand the problem at hand, and ensure our solution really can address the problem. For us, real-world impact is the end goal. Next, there is the step of requirements gathering, and after a brief commercial exchange, Farmdar’s globally trained Customer Success teams will onboard and lead the customer and their organization through the technology deployment process throughout the year. Our mutual success lies in ensuring that customer teams become fluent with our technology and platform, and customer specific training programs may also be rolled out.

Farmdar combines AI, satellite technology, agronomy expertise, and prioritises customer success to deliver actionable intelligence at scale, rather than isolated data or tools.

Farmdar provides an enterprise solution and acts as a technology partner (and often training and capacity building partner) to leading agricultural businesses, enabling impact, digital transformation and AI adoption across operations.

Farmdar is on a mission to become the world’s most trusted crop insights platform. How we think and execute is built on actionable innovation, customer-centricity, and excellence at scale, ensuring that AI insights are practical and usable in real-world operations.

Farmdar uses a combination of proprietary machine learning and deep learning models trained on millions of ground data points, satellite data from +200 constellations, weather, soil, and field data to generate crop intelligence.

Farmdar’s AI provides insights such as:
Crop identification and classification
Yield prediction
Sowing and harvest detection
Plant stress and nitrogen analysis
Productivity zones and irrigation requirements