San Francisco tech company launches foundation model, leveraging machine learning and vast datasets to provide actionable intelligence to businesses and governments for climate resilience and disruption planning
San Francisco, CA – May 21, 2025 — ClimateAi has today launched FICE (Foundational Intelligence for Climate & Economy), a new foundational model that provides a precise view of how extreme weather influences consumer behavior, revenue patterns and economic impacts. The model can be used by businesses looking to understand how they perform during climate events, investors assessing the resilience of portfolio companies, insurers looking to price risk more accurately, or governments assessing where to target disaster aid. By teasing out the potential sales upsides of weather events, FICE moves the conversation from risk management to seizing opportunities via climate adaptation.
What is FICE?
By combining aggregate consumer transaction data and other macroeconomic indicators with ClimateAi’s hyper-local and granular weather risk modeling in an AI framework, FICE explicitly models the direct impact to economic activity, measured by sales data, of weather conditions. Users can finely tailor insights to specific geographies and segment by industry to access high-value use cases and strategic intelligence. The result is end-to-end value for supply and demand planning.
Surpassing any model in existence, and encompassing a vast range of data, FICE sets the gold standard for predicting, mapping, and addressing the economic impacts of climate volatility.
Unlike many “black box” AI models, FICE is built for explainability—clearly showing how much of a given outcome is driven by weather versus other factors. This transparency expands its utility beyond demand planning to include financial impact analysis, insurance applications, and disaster response. This will empower businesses, communities, and cities to build smarter, more resilient strategies.
Resilience benchmarking: an AI-powered ‘Waffle House Index’
FICE is an AI-supercharged Waffle House Index – named after the American diner whose open / closed status is used by FEMA to evaluate disaster impacts – allowing companies to benchmark their own financial performance to show how they can improve. Insights into consumer behaviorcan be segmented on a sector-by-sector, store-by-store, and day-by-day basis.
FICE will centralize sales and weather data on one platform. Where in the past, supply planning for extreme weather has been based on individual companies’ data and anecdotal information around consumer behavior, the FICE model will be fed on an unprecedented range of transaction and weather data across sectors, brands, and locations.
This has particular applications for franchises and chains, which can identify trends and variations in the resilience of different locations, replicating the strategies of high performers. This will allow for data-led preparedness strategies, targeted to retain customers and allocate inventory efficiently when different kinds of extreme weather strike.
FICE in Action: Retrospective Insights on Weather-Linked Demand
FICE’s longitudinal analysis reveals that extreme weather doesn’t just disrupt, it drives demand. Across a ten-year period, the grocery sector alone saw over 3,000 days of weather-driven, state-wide sales surges above 10%, compared to roughly 1,350 days with equivalent sales drops. That’s an average of six major gain days and three loss days per state each year.
These impacts vary by geography and weather type. Florida, for example, had 48 gain days and 16 loss days, largely driven by multi-day hurricane stock-ups. In contrast, Connecticut recorded 96 gain days and 52 losses, reflecting frequent winter storms and the high correlation of weather effects across its smaller area. Meanwhile, California saw just 21 gain days and only two losses, likely due to its size and milder climate.
This counterintuitive pattern, where pre-event stockpiling and post-event recovery more than offset temporary disruptions, holds true across sectors like apparel, lodging, casual dining, and home improvement. These findings – for the first time ever – provide a positive business case for developing resiliency, encouraging businesses to model leaders and not just mitigate downside.
Hurricane Ian
Through retrospective analysis of Hurricane Ian – the third most costly hurricane in US history – FICE shows how companies like Ace Hardware were able to outperform competitors like Home Depot and Lowe’s by decentralizing decision-making, empowering local franchises, and pre-positioning inventory in high-risk areas. Over an eight-year weather performance analysis, FICE shows Ace consistently ranking higher in climate resilience. This provides a blueprint for repeatable operational excellence that other businesses should learn from.
These types of insights, once anecdotal or inaccessible, are now made measurable and actionable. Thanks to FICE, businesses now have a new kind of competitive edge in a climate-stressed world.
Unlimited use cases
Public bodies will also gain from minimising shortfalls in tax revenue linked to disaster-related economic slowdowns. Federal and local institutions can plan ahead to target disaster aid, funds, and recovery efforts to the most impacted sectors and regions.
As a foundation model, the short- and long-term insights revealed by FICE are only as limited as the questions asked. Its use cases can expand and be tailored to each customer by incorporating additional data sets to inform investment decisions, insurance policies, and government protocols alike.
Climate adaptation is business-critical. Extreme weather events are increasing in frequency and severity and the economic case is self-evident: physical climate risks could cost businesses up to 25% of their EBITDA in the next two decades, and companies report that every dollar spent on adaptation today could return between $2 and $19 (WEF). For the first time, FICE quantifies the financial benefit experienced from climate preparedness for companies leading the way.
Himanshu Gupta, CEO of ClimateAi commented: “This is game-changing research. For the first time, we’ve quantified the opportunity in climate adaptation—not just the cost. FICE shows how weather impacts economic performance in measurable ways, turning climate volatility into a source of strategic insight. Businesses now have the data to reduce losses—and lead with resilience.”
Will Kletter, COO of ClimateAi, remarked: “What’s powerful about FICE is that it’s not limited to any one industry. Whether you’re a supplier planning demand, a grocer preparing for storms, or an insurer pricing regional risk, FICE looks back at how businesses have responded to past weather events and turns that insight into forward-looking intelligence—helping leaders across industries make smarter, faster decisions.
Dave Farnham, Senior Director of Data Science at ClimateAi, said: “FICE insights isolate the impact of weather on a wide variety of economic outcomes in an interpretable manner. This product uses an adaptation of tree-based models and provides a clear window into how climate drives economic outcomes; it’s a transparent tool to drive adaptive action rather than a black box.”
ENDS
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About ClimateAi
ClimateAi’s mission is to climate-proof the global economy, aiming for zero loss of lives, livelihoods and nature. Leveraging proprietary AI modeling, its first-of-its-kind climate resilience platform, ClimateLens, predicts the risk and impacts of extreme weather from 2 weeks to 20 years out. By quantifying climate impact at a new industry standard, ClimateAi helps businesses to reduce risk, create new value opportunities and identify the actions needed today to adapt to the climate change disruptions of tomorrow. Headquartered in San Francisco, learn more at www.climate.ai
About Foundational Intelligence for Climate & Economy (FICE)
FICE is ClimateAi’s proprietary foundational model designed to quantify the economic impacts of extreme weather. By integrating hyper-local weather data with consumer spending patterns and socio-economic factors, FICE isolates the specific influence of climate events on business performance. Its custom tree-based architecture is built for interpretability, allowing users to clearly estimate what portion of variation in consumer spending is attributable to weather events—whether from a major hurricane or an unusually warm spring—helping businesses quantify risk and surface untapped opportunities.
