96% of Africa’s smallholder farmers (who comprise 60% of the population) rely on rain instead of irrigation for farming. But Africa’s rainfall has declined more than 100 mm annually since the 1970s, requiring farmers to be extremely precise with when and how they farm. To guide planting, fertilising and harvesting, they rely on traditional weather forecasts, which are typically too broad for the small land areas they are farming. As a result, their yields often fall well below the world average. Additionally, farmers typically overpay for household and farming supplies by 20-30%, affecting their ability to maximise profit and maintain their livelihoods.


SunCulture combines intelligent hardware, IoT, big data and neural networks to help farmers practice precision agriculture. Their AgOptimized app collects soil and weather data from soil sensors in the ground, local and METAR weather stations and meteorological satellites. AgOptimized uploads the data to Azure IoT Hub where it’s analysed against historical climate models using machine learning. The app then gives farmers detailed forecasts for their plots, as well as recommendations for planting, irrigating, fertilising and pest control to maximise yields at a lower cost. The farmers can also order farming supplies from SunCulture partners through the app’s marketplace, which offers items at fair prices and provides farmers with economically empowering financing options.

How SunCulture uses Azure

SunCulture uses the following Azure services:

  • Azure Event Hubs and IoT Hub ingest and display IoT time-series data from AgOptimized weather, irrigation, fertiliser and pest sensors.
  • Azure GPU optimised VMs train deep learning models on sensor data that help smallholder farmers optimise irrigation, fertilisation, pest control and disease management.
  • Azure Blob Storage stores IoT sensor data and weather forecast data.
A farmer waters his crops with a hose.

SunCulture uses AI to help smallholder farms

A SunCulture sensor in the soil next to a sprout.