Perilyx AI simulates the cascades — flood into fire, heat into grid failure, wind into landslide — that single-peril models miss, giving insurers and infrastructure operators months to years of lead time.
Underwriting today treats wildfire, flood, heat, and wind as separate line items. But real losses compound: a wet spring grows fuel that a dry summer burns; a burn scar turns an ordinary storm into a debris-flow event two winters later. Single-peril models are blind to the sequence.
One hazard changes the ground truth for the next — vegetation, saturation, structural integrity, grid load. We track state, not snapshots.
Compound cascades cluster losses across a book in ways diversification assumptions don't anticipate. We surface the correlation before renewal.
Most cascade windows are visible 6–18 months out in soil, canopy, and grid telemetry — if you're modeling the chain and not just the event.
We don't extrapolate from historical loss tables alone — we run GPU-accelerated neural PDE solvers over live climate, satellite, and IoT inputs to simulate how hazards physically propagate through terrain, vegetation, and infrastructure.
Satellite soil moisture, canopy density, grid load telemetry, and NOAA forecast ensembles are ingested continuously at parcel resolution.
Our neural PDE solvers propagate a primary hazard forward and estimate the state changes — fuel load, saturation, structural stress — that shape secondary hazard probability.
Cascade probability, expected severity, and lead time are scored per parcel and delivered into underwriting, claims triage, or grid-hardening workflows via API.
"We stopped asking 'what's the wildfire risk on this parcel' and started asking 'what does this parcel look like eighteen months after the wildfire.' That's a different question, and it's the one that actually predicts our losses."
Portfolio-level correlation scoring and loss-triage models that flag compound exposure before renewal, not after a claim.
Grid-hardening prioritization that accounts for cascading ignition and load-failure risk across service territory.
Resilience planning models for FEMA-aligned mitigation grants, built on the same cascade engine used by carriers.
A working session with our science team — no slideware, real portfolio data, run against the live model.