Case studies

We teamed up with a Swiss agri-tech innovation startup to build a platform that uses satellite images, radar data, and machine learning to give farmers a clear view of their crops. The system applies machine learning for crop yield prediction and optimization, while also spotting weeds early and estimating sugar content, giving farmers actionable insights through AI solutions for sustainable and resource-efficient farming, helping boost harvests and reduce resource waste. Our client is a Swiss AI farming startup focused on improving farming using advanced technology. They use satellite and drone images to monitor fields and predict things like crop yields and the sugar content in sugarcane. By analyzing these images, they help farmers better understand the condition of their crops, identify weeds, and see if a harvest has been completed in certain areas. They committed to advancing AI-powered precision farming by combining satellite images, agriculture data analytics, and environmental information to help farmers make better decisions.