Taranis uses a computer vision model which looks at high-resolution satellite images to detect changes in the field. Trained on thousands of annotations, the model can accurately detect a field’s history over the course of time for which satellite images are available, including cover crops, tillage events, plant date, crop classification, and harvest date. This approach allows Taranis to provide accurate history on a field, gather input data for procedural models to estimate soil makeup, and perform third party validation of implemented sustainable practices. All of this without burdening an advisor or grower with data entry.