News

AISIX wins $780,000 wildfire modeling contract with Canadian insurer

AISIX locked in a $780,000, three-year wildfire modeling deal with a major Canadian insurer, a sign climate-risk tools are becoming core underwriting infrastructure.

Nina Kowalski··3 min read
Published
Listen to this article0:00 min
Share this article:
AISIX wins $780,000 wildfire modeling contract with Canadian insurer
Source: s.yimg.com

AISIX Solutions Inc. locked in a $780,000 wildfire catastrophe modeling contract with a major Canadian insurer, turning a peril-specific analytics sale into a minimum three-year revenue stream and a fresh test case for how far climate-risk software has moved into insurer operations.

The agreement was signed on May 4, 2026 and announced the next day. It is structured as a master services agreement and statement of work worth $260,000 per year, with AISIX saying the deal was won through a competitive, invite-only request for proposal process in which multiple providers were evaluated. That matters because the buyer was not just purchasing a model, but weighing technical fit, operational readiness, and the ability to plug external hazard intelligence into underwriting and portfolio management workflows.

AI-generated illustration
AI-generated illustration

The scope is broad. AISIX said the engagement covers wildfire hazard data for all of Canada, along with location-level and portfolio-wide loss metrics including Annual Average Loss, occurrence probable maximum loss, aggregate probable maximum loss, event and year loss tables, and reinsurance integration to support net loss and capital management. The platform is designed to handle portfolio runs of up to 20 million locations, and AISIX targeted initial hazard-data delivery within 15 calendar days of the contract start. The work also includes a custom vulnerability framework calibrated against the insurer’s historical claims data.

That scale helps explain why the contract carries weight beyond its dollar value. AGORACOM reported that the insurer manages roughly 20 million insured locations, putting the deal in the same operational universe as the largest property and casualty carriers in Canada. For AISIX, the contract gives the company what it described as predictable recurring revenue, a key milestone for a smaller vendor trying to prove it can support enterprise-grade catastrophe work rather than just exploratory pilots.

The deal also fits a larger pattern inside insurance technology spending. Wildfire risk is no longer a background research topic. It is shaping pricing, accumulation control, reinsurance buying, and how carriers decide where to grow or pull back. In that environment, insurers increasingly need external peril intelligence that is precise enough to influence portfolio strategy, even if the end result is mostly invisible to policyholders. The ROI question is less about a consumer-facing feature than about avoided loss, tighter underwriting selection, and better capital deployment.

AISIX had already been moving toward that kind of role. On February 26, 2026, it said it had been selected as wildfire catastrophe modeling vendor for a three-year engagement by a major Canadian insurance company, pending legal review of the master services agreement and statement of work. Before that, on November 4, 2025, the company disclosed a 30-day pilot with a global specialty insurance, engineering and risk management provider using up to six users and 500 locations. Its January 20, 2026 update said it had launched Wildfire 3.0, the Climate Genius dashboard, and an API. Taken together, the sequence shows a vendor moving from pilot to platform to paid multi-year deployment, which is exactly where climate-risk software begins to look less experimental and more like insurer infrastructure.

Know something we missed? Have a correction or additional information?

Submit a Tip

Never miss a story.

Get P&C Insurance Software updates weekly. The top stories delivered to your inbox.

Free forever · Unsubscribe anytime

Discussion

More P&C Insurance Software Articles