Our Showcase

Rice Analytics

We monitor the growth stage of paddy fields by using NDVI value time-series and RGB images derived from drone integrated with satellite data. We are able to detect the difference growth periods of various species of rice in the field. We provide insights regarding crop health, weed detection, and water stress analysis in order to prevent loss and increase yield.

Cassava Analytics

We apply geo-informatics technology and machine learning to detect cassava conditions and identify pests, fungus, or arid conditions in the cassava fields up to two weeks prior to human eyes. Varuna application helps farmers see the problems early enough before disease spreads out with minimum effort to survey the field, resulting in time, cost and resource saving while improving crop yield significantly.

Sugarcane Analytics

Varuna sugarcane solution enables you to build 3D model of your field and equipped with easy analytics tool that help you estimate average height and identify the growth stage of sugarcane. This prosperity of identification can prevent production loss at the early vegetative phase, first 1-3 months. We support sugarcane enterprise in supply prediction around their mill and plan  step-by-step cultivation so that you can better manage demand-supply and price fluctuation

Sugarcane NDVI

Pineapple Supply Forecast

We provide pineapple supply forecast solution by monitoring the patterns of pineapple cultivation and analyzing the vegetation index. We are able to identify estimated yield and harvesting period. Our pineapple model gives you the visibility of the fields resulting in better farm management, operation cost reduction and solve market price fluctuation.

Forest Management and
Carbon Credit Solution

Forests are the most proven scalable and cost-effective means of drawing down carbon. We use satellite analytics to monitor the change of green area. We are able to detect significant changes in forest area in the past three years and plan afforestation in time.  We provide recommendation in area zoning to optimize the landuse with the goal to maximize the forest area and turn to carbon credit.