From Deep Insight to Exponential Growth
Our novel agritech solution allows you to make informed decisions and build a robust, resilient, and profitable future for global agriculture.
Our computational simulations provide critical and predictive insights for decision-making in land dependent industries replacing slow and labour intensive data collection and analytics. Modern agriculture is data-driven, and profitable production relies on getting operations right.
We deliver software products for:
Professional operating companies are already collecting much of the data that creates the bedrock of our analytical products. However, few services exist for immediately registering and updating insight. The time lag and inaccuracies leads to the wrong decisions in allocating time and resources.
Our software is tried and tested for tree crops, and can be adjusted to fit with any industrial crop.
The Sensonomic software gives you:
- expected future yield
- operational planning insight
- dynamic advice on how to optimise operations and logistics
Investors and owners often find it difficult to get to the insight they need to assist their operating companies with capital and knowledge. By enabling a customisable set of dashboards based on aggregated data, investors and owners get immediate insight into the status of their operating companies, and the expected future cash flow.
With the analytical capabilities of the modeling engine we can provide investors with unparalleled insight into operational performance.
The Sensonomic software gives you:
- expected value of future cash flow
- operational insight
- dynamically updated performance data
Yield Prediction
Get early prediction and insight on crop quantity and quality to guide your decisions before harvest.
Harvest Planning
Helps you direct harvest resources to the right place at the right time for optimal yield.
Transport Routing
Enables you to control and coordinate the trucks between fields and mills.
Agent Based Modelling
Simple rules combine to deliver
insightful, emergent
outcomes.
Agent based modeling (ABM) underpins our computer simulations, and means we deliver uniquely predictive and prescriptive insights. In this methodology, individual agents follow prescribed behaviour rules, and interact in a shared spatial environment which evolves over time. Integrated remote sensing and GIS layers define the spatial environment that agents operate over, respond to, and modify.
Agent based modelling allows for users to be involved in its design, as it is driven by intuitive rules, and it handles varied data and behaviours. Outcomes emerge from these bottom-up rules, and one can test policy effects in advance – and thus find the best policies among many options.
Our Clients and Operational Regions
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