Clay
Creates embeddings from satellite imagery that can be used for classification and other downstream tasks with relatively few labeled examples.
- Field
- Remote sensing
- Method
- Foundation model
- Data it takes
- imagery
- License
- Apache-2.0
Clay is a vision transformer pretrained across Sentinel-2, Sentinel-1, Landsat, NAIP and MODIS. Rather than answering a fixed question, it converts imagery into embeddings: numerical representations of what a patch of ground looks like.
The practical effect is a reduced labeling requirement. A scene is embedded once, then a classifier is fitted on a few dozen labeled examples rather than thousands. This suits projects needing a custom classification without the budget to build a large training set.
Catalog entry last checked 2026-08-17. All models →
Run Clay on your data
The lab runs this on its own compute, in a container, with the inputs and parameters recorded alongside the result. Initial scoping conversations are free.
Contact the Lab