OneSoil and Rainbow Weather launch AI-powered hyperlocal rainfall forecasts for farmers

Precision agriculture company OneSoil has partnered with Rainbow Weather to introduce AI-powered hyperlocal rainfall forecasting for farmers, aiming to help growers better manage weather-related risks and optimize field operations.

The new feature, called Hyperlocal Precipitation Forecast, has been integrated into OneSoil’s digital farming platform and provides short-term rainfall predictions for specific field locations. Using machine learning models trained on radar, satellite, and atmospheric data, the system forecasts precipitation probability and intensity within a four-hour window for exact coordinates. Farmers can monitor cloud movement and anticipate rainfall for individual sections of fields, whether in Europe, Africa, or other agricultural regions.

The launch comes as extreme weather events continue to increase worldwide. According to the companies, extreme weather causes approximately €28 billion (about USD 32 billion) in annual losses for farmers across the European Union, equivalent to around 6% of total agricultural production. OneSoil said access to highly localized weather data is becoming increasingly important as unpredictable rainfall can disrupt planting schedules, reduce yields, and undermine crop protection efforts.

Stepan Zulynskyi, chief executive officer of OneSoil, said short-term weather forecasts are particularly valuable for operations such as fertilizer application and crop spraying, where unexpected rainfall can wash away inputs and require costly reapplication. The company said more than 15,000 farmers are already using the new forecasting feature each month.

Alexander Matveenko, co-founder and chief executive officer of Rainbow Weather, said growing climate volatility is increasing demand for precise weather intelligence. In addition to forecasting upcoming rainfall, the technology provides access to historical precipitation data, helping farmers plan fieldwork and make more informed agronomic decisions.