Putting Earth AI to work: Geospatial agents for our planet's biggest challenges

When we introduced Google Earth AI, we shared a suite of geospatial foundation models — spanning remote sensing, weather, flood hydrology, and population dynamics — alongside an initial prototype showing how a Gemini-powered agent could connect those models to answer cross-modal questions.

Since then, we have evolved a Geospatial Reasoning agent from an early concept into a much more capable, experimental system built for multi-step, geospatial reasoning across planet-scale data and autonomous training of custom predictive models. Today, we are sharing three updates:

1. A new technical report on geospatial reasoning: We present systematic evaluations across four benchmarks, including GeoKTools and GeoExpertQueries, two new benchmarks we developed and are releasing for researchers to test their own geospatial reasoning agents. Our results quantify the value of Earth AI’s specialized tools and planning over out-of-the-box LLMs.
2. Insights from real-world partner testing: Over the past few months, we invited a small group of social impact and commercial partner organizations — including the World Health Organization (WHO) Regional Office for Africa, People in Need, GiveDirectly, the Milken Institute and WPP — to test the agent in support of their own real-world workflows, such as disease outbreak investigations, disaster preparedness, and clean energy screening.
3. Expanding early access on Google Earth and Google Cloud: We are expanding experimental access for both multi-step geospatial analysis and for planetary prediction. We’re offering early access to an experimental deep research update for Ask Google Earth. We’re also providing early access to an agent-to-agent API for developers building custom workflows, including integration recipes for connecting to Gemini.