Earth AI in action: Early testing with partners

To evaluate how this research translates to real-world challenges, we gave a small group of partners early access to test the experimental agent on their toughest problems. Across public health, disaster response, and infrastructure planning, below is an overview of how they are putting Earth AI into action:

• •World Health Organization (WHO AFRO) & DRC’s INRB: At the start of the 2026 Ebola outbreak in the Democratic Republic of the Congo (DRC), WHO AFRO’s Emergency Preparedness and Response Hub in Dakar used the Geospatial Reasoning agent to map remote mining corridors where the exposure risk and human mobility are high by cross-referencing forest loss (from satellite images), mining sites (from maps and web data), and population data. In minutes, the team pinpointed 48 exposed settlements and located more than 45,500 at-risk people — a process that normally would have taken weeks. This allowed local responders to proactively deploy mobile laboratories and coordinate border surveillance. Meanwhile, the Epidemic Modeling and Intelligence Unit (UMIE) at the DRC’s National Institute for Biomedical Research (INRB) used the Planetary Prediction Engine to estimate the risk of Ebola spreading into uninfected zones. By combining mobility flows with historical case trends and Earth AI models and datasets, these weekly insights give coordinators critical planning time before cases arrive.
• •“Mobile populations like miners move faster than traditional paper surveillance can track, creating dangerous blind spots. Earth AI fills those gaps with satellite and mobility signals—moving us from reactively chasing a virus to actively forecasting where it will strike next.” Dr Etien Koua, HIS Program Area Manager & Hub Coordinator for WHO AFRO Emergency Preparedness and Response (watch the video)