What We Do

Crop Prediction

The core of our work is understanding and predicting crops – on a national and global scale.

  • Global Scale

  • Field Level Accuracy

  • Unique Ground Truth

We provide accurate, reliable and effective results – with our platform Inference. We have been recognized for our innovation  – by the European Space Agency, Norwegian Space Agency, and UK Government, and work with multiple FTSE 250 companies.

Our unique approach to Ground Truth collection and machine learning is building the world’s largest database of crops.

CASE STUDY

Case Study: Crop Prediction Thailand

A client needed to understand how much sugar was produced in Thailand ahead of the market. We built an entirely new methodology - providing unique insights for our client. 

Weather

We monitor the weather around the world. Any Crop. Anywhere. Any Scale.

We have 40+ years of historical data and forecasting for any location.

Customized alerts based on any criteria for any location.

CASE STUDY

Case Study: Barley Yield France

Using satellite data and weather data to predict the French Barley Yield - months ahead of the market with over 95% accuracy.

Yield | Disease | Risks

Monitor, identify and predict crops for disease, damage or poor irrigation,

Any field, region,  or country anywhere in the world.

National-level models with over 95% accuracy

CASE STUDY

Case Study: Crop Disease and Irrigation

A client needed to monitor crops for risk of disease and drought/poor irrigation on a national scale; the client needed weekly updates on the risks to crops and production.  The scale of the fields and the land overall meant it was not possible to check all of the fields every day manually. Even with drones, it would have been cost-prohibitive, costing tens of millions.  For this reason, we built a solution that looked at every 10m of land every week, across the entire country and used machine learning, based on billions of data points, to detect disease.

Intelligence & Research

Research and data gathering around the world – with over 1,000 data collectors around the world.  From Brazil to Bangladesh

Example: Understanding factory production in Thailand.  Field surveys in fields in Argentina.  Flood surveys in Pakistan.

CASE STUDY

Case Study: Flooding Pakistan

The 2022 floods in Pakistan killed over 1,500 people and devasted farms and buildings.  We obtained an unparalleled level of understanding of the floods, the reports coming back within hours.  We visited over 2,000 fields, conducted numerous drone surveys, mapped the country with radar data, identified the key producing factories and checked them for flood damage - with drones, radar and "in-person contact".  All of this was done within ten days. 

How We Do It

We use satellite data, weather data – and a team of over 1,000 people around the world to collect data on crops.

We collect petabytes of data and use this to build complex model and then providing insights

Our  team has decades of experience in providing insights and not just data

Understand

We work with you to understand your problem

Analyse

We use global scale data - with AI and Machine Learning

Insights

We provide clear answers