

Research
Every location tells a story through
its connections, patterns, and context.
But AI has been deaf to these stories, processing geographic
data as disconnected points rather than understanding how
places truly relate to each other. At Globeholder,
we set out to change that.
Geo-Transformer
Our Geo-Transformer emerges from a simple but revolutionary idea: that geographic data should be treated as living, interconnected structures rather than flattened grids or isolated coordinates. Cities are more than a collection of streets and coordinates. They're dynamic, multi-layered systems where each block, boulevard, and building is part of a larger story. To capture this, we have created a transformer model that natively consumes GIS geometry using innovative network modules.
Model Features
Why not explore our Research in more detail by checking out our White Papers?
You can find out all about our value-driven benchmarking against the state-of-the-art EO foundation models and fully appreciate the power of GIS embeddings.
Use Cases
