FutureProof Technologies acquires Terrafuse AI to scale property-specific wildfire underwriting
FutureProof Technologies has signed a definitive agreement to buy Terrafuse AI, a wildfire risk analytics company known for high-resolution prediction models. The goal: fuse Terrafuse's granular wildfire forecasting with FutureProof's AI-enabled underwriting and pricing engine. That combination aims to improve availability and pricing accuracy for properties in high-risk wildfire regions across the West.
Why this matters for insurers
Capacity has tightened in Western states, and the volatility is real. The January 2025 Los Angeles wildfires burned more than 57,000 acres, destroyed over 18,000 structures, and pushed insured losses beyond expected thresholds. Better property-level risk signals are now a prerequisite for rate adequacy, portfolio stability, and growth without adverse selection.
FutureProof launched in August 2024 and has already allocated more than $1B in total insurable value, with a strong footprint in the Southeast. With Terrafuse's wildfire models, FutureProof plans to extend that footprint further into Western markets where access to coverage has contracted.
What Terrafuse brings to underwriting and pricing
Terrafuse runs daily-updating machine learning models that ingest 50+ variables, including roof type, building materials, vegetation, wind direction, vapor pressure deficit, fuel moisture, and humidity. The output estimates burn probability and damage potential at roughly a 300-square-foot resolution. This is a step beyond coarse vegetation maps or wide weather grids, which often miss the micro-conditions that drive loss at the parcel level.
For carriers and MGAs, that resolution can sharpen appetite, refine rating factors, and reduce loss cost volatility. It also creates a foundation for transparent mitigation credits tied to verifiable, property-level improvements.
How insurers can put this to work now
- Underwriting guidelines: Gate new business with parcel-level burn probability and damage potential. Prioritize write-ups where mitigation and construction class materially shift expected loss.
- Pricing: Introduce finer segmentation for brush, slope, wind exposure, and structure attributes. Use daily updates to keep indicated rates aligned with current conditions.
- Capacity allocation: Steer bindable capacity toward resilient pockets within high-risk ZIPs. Cap aggregations based on block-level hazard, not county averages.
- Mitigation credits: Tie credits to actions proven to change loss outcomes (defensible space, ember-resistant vents, Class A roofs). Verify with evidence, not declarations.
- Reinsurance strategy: Use higher-resolution hazard views to negotiate terms, structure layers, and set event limits with more confidence.
- Exposure management: Monitor accumulation in micro-geographies where fuel, wind, and topography amplify spread potential.
- Claims and SIU: Pre-position resources during red flag days and triage total loss potential faster with parcel-level hazard signals.
- Model governance: Document data sources, update cadence, validation methods, and calibration. Track drift and explainability to support filings and fair underwriting reviews.
Market impact
Integrating Terrafuse's wildfire analytics into FutureProof's pricing engine is expected to expand AI-driven property insurance offerings across the West Coast. For homeowners and distribution partners, that can mean more precise pricing, clearer eligibility, and broader availability where it's been scarce.
The combined approach also supports resilience incentives. For practical mitigation standards and verification, see the Insurance Institute for Business & Home Safety's guidance on wildfire-ready homes: IBHS Wildfire Prepared Home. For incident context and active events, refer to CAL FIRE Incidents.
Signals from leadership
Alisa Valderrama, Co-Founder and Co-CEO, FutureProof Technologies: FutureProof has written over $1B in total insurable value since August 2024, with an emphasis on the Southeast. She notes that combining Terrafuse's proven wildfire models with FutureProof's underwriting platform brings sharper pricing clarity to cat-exposed property in Western markets and helps bring capacity to resilient risks where it's needed most.
Hunter Connell, Co-Founder and CEO, Terrafuse AI: Connell explains that Terrafuse's models update daily across more than fifty variables and focus on the fine-grained, property-specific conditions that drive loss. That precision supports burn probability and damage estimates at a 300-square-foot resolution, which, when paired with FutureProof's pricing engine, can expand access to affordable coverage in high-risk regions and support their mission to apply AI and climate science for community protection.
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