FutureProof Technologies to Acquire Terrafuse AI: A Clear Signal for Property Insurance in Wildfire Zones
Nov 10, 2025 - FutureProof Technologies has signed a definitive agreement to acquire Terrafuse AI. The deal pairs Terrafuse's patented wildfire prediction models with FutureProof's AI-driven underwriting and pricing platform to deliver property-specific insight and faster, more precise decisions in wildfire-affected states.
This comes on the heels of the January 2025 Los Angeles wildfires, which burned over 57,000 acres, destroyed more than 18,000 structures, and drove insured losses above expectations. Capacity is tight where it's needed most. This move aims squarely at that gap.
Why this matters to insurers, MGAs, and brokers
- Selection and pricing: Daily-updating, property-level wildfire insights can tighten risk selection and rating, reducing adverse selection while keeping competitive wins.
- Capacity allocation: Finer-grained views of burn probability and damage potential make it easier to steer capacity to resilient properties without blunt geozone exclusions.
- Underwriting speed: FutureProof's platform supports instant bindable quotes (even on complex risks), helping distribution teams move with less friction.
- Reinsurance dialogue: Transparent hazard signals at sub-parcel resolution can strengthen ceded negotiations with clear evidence of risk differentiation.
- Mitigation credits: The blend of property features (roof type, materials) and microscale conditions supports credible credits for hardening and defensible space.
What Terrafuse brings
Terrafuse's machine learning models update daily using 50+ variables, from roof type and building materials to wind direction, vegetation, vapor pressure deficit, fuel moisture, and humidity. Where many wildfire models lean on coarse vegetation maps or broad weather grids, Terrafuse pinpoints property-specific conditions.
The result: burn probability and damage potential estimates at 300-square-foot resolution. The company reports strong predictive performance over multiple fire seasons, including during the 2025 Los Angeles wildfires.
What FutureProof adds
FutureProof runs an AI-powered underwriting and pricing engine that has written over $1B in total insurable value since launch in August 2024, with early traction in the Southeast. The platform automates decisions and delivers instant bindable quotes while incentivizing resilience improvements.
FutureProof operates as both an MGA and an insurance agency, backed by investors including Innovation Endeavors and MS&AD Ventures. For details on the company, visit futureprooftech.io.
Leaders weigh in
Alisa Valderrama, Co-Founder and Co-CEO, FutureProof Technologies: "We have built an excellent track record and written over $1B in total insurable value since we launched in August 2024, with an emphasis on the Southeast. By integrating Terrafuse's proven wildfire models with our AI-powered underwriting platform, we can bring a similarly incisive view to pricing cat-exposed property in the west. Backed by validation from the insurance market including successful use by underwriters, Terrafuse's machine learning models have been proven through multiple fire seasons and now helps extend FutureProof's AI advantage into the West Coast market. This type of innovation, which uses AI to bring new sources of capacity to resilient properties, is exactly what the market needs now."
Hunter Connell, Co-Founder and CEO, Terrafuse AI: "Terrafuse's machine learning models continuously improve, updated each day with more than fifty distinct variables - from property-level details like roof type and building materials to microscale environmental factors such as wind direction, vegetation, vapor pressure deficit, fuel moisture, and humidity. Where other wildfire models rely on coarse, infrequently updated vegetation maps or broad-scale weather grids, Terrafuse pinpoints the fine-grained, property-specific conditions that actually drive loss. This precision enables us to estimate burn probability and damage potential at 300-square-foot resolution. By integrating this capability with FutureProof's proprietary pricing engine, we help more homeowners in high-risk regions gain access to affordable wildfire insurance and advance our founding mission to apply AI and climate science to protect communities from disasters."
How this could show up in your workflow
- Underwriting: Pre-bind triage that flags micro-environmental hazards at the structure level; quicker pass/refer/decline decisions with reasons you can explain to brokers and regulators.
- Rating: Feature-level signals feed rating variables or modifiers that better reflect hazard and vulnerability without over-penalizing entire ZIPs.
- Mitigation programs: Clear ties from features (e.g., roof class, defensible space) to expected loss help justify credits and post-bind inspections.
- Portfolio steering: More confident selection within brush zones to balance growth and volatility; improved aggregation control at the micro-area scale.
- Reinsurance: Evidence-backed hazard segmentation to support retentions, occurrence limits, and ILW structures.
Governance and model risk to consider
- Validation: Request backtests across multiple seasons, including the 2025 LA fires, and compare against your portfolio's actuals.
- Stability: Daily-updating signals are powerful but can be noisy; define smoothing rules and escalation thresholds.
- Explainability: Maintain documentation that translates model features into underwriting rationale for filings and market conduct exams.
- Vendor due diligence: Confirm data lineage, retraining cadence, and change-control around model updates.
- Fairness: Review potential disparate impact at the boundary of high/low hazard zones and ensure mitigation pathways are offered.
About the companies
FutureProof Technologies: A venture-backed insurtech using AI to streamline property underwriting and pricing in catastrophe-exposed markets. Operates as an MGA and insurance agency with investor backing from Innovation Endeavors and MS&AD Ventures.
Terrafuse AI: Builds physics-informed machine learning models for wildfire risk prediction. The team includes AI and climate scientists trained at Stanford, Berkeley, and MIT, with validation through insurance partners and collaborations with organizations such as the U.S. Air Force, Lawrence Berkeley National Laboratory, the National Science Foundation, and NASA.
What to watch next
- Integration timeline and how quickly new wildfire signals appear in quotes and bind decisions.
- State-by-state filings where wildfire variables inform pricing or credits.
- Capacity expansion in California and other Western states for resilient risks that have been priced out of the market.
Action for insurance leaders
- Pilot property-level wildfire signals on a sample of recent submissions; compare hit/close rates and loss picks.
- Stand up a mitigation credit schedule tied to model features you can verify and defend.
- Revisit reinsurance strategy using finer segmentation to justify retentions and attachments.
Interested in building AI fluency across underwriting and product teams? Explore practical learning paths by job role at Complete AI Training.
Media contact
FutureProof Technologies: info@futureproofins.com
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