Anaximander: Interactively Running Geospatial Deep Learning Models on Any Compute Backend

Applying deep learning models to satellite imagery from within geographic information systems (GIS) remains high-friction for remote sensing practitioners. Models arrive in incompatible formats and target different compute environments, from local workstations to serverless cloud services.