Normalized claim
Cost: 30% decrease
Farmers achieving up to 30% cost savings by reducing seed, fertilizer, and water inputs.
Agrobit, an Argentinian agtech company, collaborated with Microsoft to create an AI-powered, Azure-based platform for agriculture that is transforming both wine production and general crop farming in Argentina. The system integrates sensor data, drones, and satellite imagery with machine learning algorithms to deliver tailored recommendations on sowing, watering, fertilizing, and harvesting for more than 50 different crops. The approach has involved working with small and medium-sized farmers, local cooperatives, and vintners, notably in the Mendoza region. Utilizing the platform, growers can optimize their agricultural inputs and scenarios, including adapting to government regulations and climate shifts. This allows them to plan for different seasons, manage budgets, and access expert advisories via a simple app that works with or without internet connectivity. Technology adoption, supported by Fecovita’s cooperative, has led to notable productivity increases, water savings, and enhanced traceability, even among older or remote farmers. The digital transformation is cited as demystifying technology for farmers, enticing new generations into agriculture, and making Argentina’s producers more globally competitive. The solution is bringing advanced agronomy and AI data science techniques to democratize smart farming and sustainability in regions often left behind by previous technological advancements. Farmers report cost savings, reduced input usage, and increased efficiency. The regional impact includes higher yields, sustainable water use in the face of a decade-long drought, and the ability to maintain cultural and intergenerational continuity on family farms.
Reported outcomes
−30%
costCost savings
Strategic outcomes
Normalized claim
Cost: 30% decrease
Farmers achieving up to 30% cost savings by reducing seed, fertilizer, and water inputs.
Normalized claim
Cost: 10% decrease
Significant increases in productivity and optimization (up to 10% water savings for some farmers).
No explicit deployment-stage evidence found.
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Sensor data (in-field and remote), drone and satellite imagery are ingested into the Azure-based platform, which leverages Azure FarmBeats for data integration and machine learning to generate agricultural recommendations. The solution integrates mobile and desktop applications for actionable advice and remote monitoring, collaborating with co-operative agronomists and digital support teams.
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