We're building foundation models that learn Earth's seismic patterns to deliver actionable risk intelligence for the global reinsurance market.
Earthquakes cause $100B+ in annual damages. Current models fail because they ignore the Earth's interconnected nature.
Traditional methods like ETAS only analyze local data, missing critical stress transfers between tectonic regions that trigger cascading events.
Reinsurers rely on static probabilistic models that can't capture dynamic risk evolution, leading to catastrophic losses and mispriced premiums.
Global seismic networks generate petabytes of data, but no existing system fuses heterogeneous sources into a unified predictive model.
Just as LLMs learned language by seeing the whole internet, our Transformer-based model learns seismic physics by attending to global sensor networks simultaneously.
We deliver seismic risk intelligence as an API to the catastrophe modeling and reinsurance industry.
Join the waitlist for our API beta. We're partnering with select reinsurers and catastrophe modelers.