AtlasAI

AtlasAI is a Geospatial AI platform that delivers planetary-scale GeoAI capabilities to forecast supply and demand, monitor change, and access hyperlocal socio-demographic indicators, with custom enterprise pricing (no public tier available). It targets enterprise data science teams in industries like consumer goods, logistics, manufacturing, energy, and humanitarian aid who need location intelligence at human scale.

Founded in 2018 by Stanford professor Marshall Burke, Abe Tarapani, David Lobell, and Vivek Subramanian, Atlas AI emerged from academic research into using satellite imagery and machine learning to measure economic activity in places where traditional data is sparse. The platform combines a Geospatial Feature Store of analysis-ready data, a GeoAI Model Library of production-scale models, and an Enterprise Developer Toolkit of connectors and APIs that integrate into existing ML workflows. Its flagship Aperture product line — including the recently launched Aperture® Pulse — provides queryable insights about where people live, how markets are changing, and where opportunity is concentrated, claiming to expand customer models from "tens of features to thousands."

The platform supports a defined set of solution patterns: demand forecasting and site selection for industrials and energy, asset monitoring and change detection in conflict-prone regions, last-mile targeting for humanitarian aid and consumer goods, market micro-segmentation for sales uplift, and demand-sensing for fleet and manufacturing planning. Compared to the other Geospatial AI tools in our directory of 870+ AI tools — such as general-purpose platforms like Google Earth Engine, Esri ArcGIS, or Planet Labs — Atlas AI differentiates by focusing exclusively on socio-demographic forecasting and human-scale insights rather than raw imagery analysis or GIS tooling. It is not a self-serve product; engagements typically start with a sales conversation and a custom data science scoping exercise, which makes it best suited for organizations with mature data teams and budgets for enterprise contracts.