In October 2017, wildfires devastated Northern California, burning 245,000 acres and 8,900 buildings. They were the costliest wildfires ever, including $11 billion in insured losses. With so much on the line, government agencies, insurance companies, and the general public need a way to accurately forecast and understand wildfire risk at any given location.


Terrafuse is building technology infrastructure on Microsoft Azure to rapidly forecast wildfire risk at the hyperlocal level, starting in areas affected by the 2017 California wildfires. By combining historical fire data with existing physical simulations and real-time satellite observations, Terrafuse is building sophisticated fire risk models that will be made available via APIs and graphical interfaces to anyone interested in mitigating the effects of wildfires.

Desert landscape of rolling hills and brush.

Using AI to model climate-related risk

Tall trees in a forest.