Identify moisture zones for
crops at the root zone

Allows for smarter usage of
water and irrigation scheduling

Identify surface level moisture in the soil

Determine water requirements of the soil

Manage water usage efficiently

Identify areas of good
and poor plant health

Focus efforts on specific areas
rather than a blanket approach

Track and improve health of crops
resulting in better quality and yields

Remote monitoring of farms

AI-backed using 5-year
historical satellite imagery

Identifies productivity zones
by high, medium and low ranges

Isolate areas for intervention

Select the most productive
fields intelligently

Allows farmers to apply
P&K intelligently

In the SOM analysis, black represents
areas where organic matter is good, while
grey and white represents the areas with
medium and low organic matter quality

High yield productivity area corresponds
with good SOM

Identifying zones of low, medium and high
SOM allows focused areas for soil
improvement efforts

Identify areas of high, medium
and low Nitrogen requirement

Based on AI and satellite imagery
analysis of plant chlorophyl content

Enables reduction of environmental
impact of Nitrogen

Identify which crops are under stress and
which ones are likely to be under stress
in the future

Focus efforts on specific areas rather
than a blanket approach