Agrograph is a global provider of agricultural production and hazard forecasts derived from satellite imagery and proprietary field-scale predictive models. 

Our story began when founder Dr. Mutlu Özdogan, a remote sensing scientist at UW-Madison, recognized that machine learning could be used to predict in-season crop yields from satellite imagery.

Since 2014, we've grown to become a trusted provider of satellite-based crop intelligence. Every growing season, we monitor millions of acres across the globe and continuously refine our models to deliver the most accurate yield predictions and hazard insights to our customers.

Our team brings together deep expertise in remote sensing, agronomy, and data science. CEO Taralinda Willis combines hands-on farming experience with a strategic understanding of what crop insurers and agribusinesses need to assess risk and make decisions. CTO Dale Willis brings the machine learning expertise to conquer the many data quality problems inherent to earth observation data in order to produce accurate predictions.

Today, Agrograph serves crop insurers, asset managers, and agricultural enterprises who need reliable, scalable crop intelligence. Whether you need to predict yields before harvest, assess portfolio risk during the growing season, or research historical production trends, our field-level production and hazard forecasts answer questions no other agricultural dataset can.