Critical Path Data Science
Simulation and optimization tools that help fire and emergency-management professionals explore where a fire could go, who could be at risk, and how to prepare.
simulated spread · 1–8 hr isochrones · illustrative
New · Suppression Planner
Run the fire once. Then scrub the timeline, place control lines, engines, and tanker drops at the moment they would arrive, and re-simulate from that point. Branch a scenario to compare two different moves from the same decision point — the untouched baseline stays on screen for contrast.
The platform
Click a point on the map and watch a simulated fire’s 1, 2, 4, and 8-hour spread contours, with the structures and census block groups at risk counted for each horizon.
Inverse multi-objective optimization works backwards from your targets to find the ignition your county should worry about most — for structures and for people.
Stage prescribed-burn ignition schedules and suppression lines, animate the burn hour by hour, and export the result as KMZ or shapefiles for GIS.
Plan wave-by-wave alert schedules that balance road capacity against simulated fire arrival, aiming to clear every zone before the modeled fire reaches it.
A forward model tells you what one scenario does. Inverse multi-objective optimization runs the physics backwards from the consequences you care about — which ignition, which conditions, which response produces the outcome you fear, and what to do about it.
Under the hood
Level-set fire spread simulation on real fuel and terrain rasters — the same model class used in operational forecasting.
NOAA forecast weather pulled at run time, plus building footprints and census vulnerability data for consequence estimates.
Multi-objective optimization searches the scenario space for the cases that matter — worst-case ignitions, best-value responses — instead of asking you to guess them one run at a time.
We’re pre-launch. Leave your name and email and we’ll reach out for a conversation about your county, your risk, and your data.