Our founders worked together in the space industry. After studying aerospace engineering and physics at Stanford and Berkeley, they worked on engineering and risk management at multiple space companies, seeing up close what sorts of incredibly useful data satellites and spacecraft can provide. Today we use this sort of data to predict wildfire risk.
Here is a visualization of the claims for a large home insurance carrier after the 2017 and 2018 wildfires. As you can see, this leading risk model incorrectly predicted that most of the homes that burned were low risk.
When we apply our own risk model to the same areas during the same time period, it accurately labeled nearly all the homes that burned as being high-risk, and very few of the homes that our model sees as low-risk ended up burning.
Here is a visualization of the claims for a large home insurance carrier after the 2017 and 2018 wildfires. As you can see, this leading risk model incorrectly predicted that most of the homes that burned were low risk.
When we apply our own risk model to the same areas during the same time period, it accurately labeled nearly all the homes that burned as being high-risk, and very few of the homes that our model sees as low-risk ended up burning.
Our industry-leading model, based on proprietary data and cutting-edge AI, allows us to safely offer coverage in a market with very limited options.
We understand how dry the vegetation will be, based on rainfall patterns and satellite imagery. Our understanding of topography and historical wind patterns helps us model precisely where the embers from a fire would likely land. Our intelligence is based on Python code, not just a zip code.
We understand how dry the vegetation will be, based on rainfall patterns and satellite imagery. Our understanding of topography and historical wind patterns helps us model precisely where the embers from a fire would likely land. Our intelligence is based on Python code, not just a zip code.
