SBIR Phase II: Combining Physics and AI for Enhanced Risk Assessment
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This National Science Foundation SBIR Phase II award, titled Combining Physics and AI for Enhanced Risk Assessment, funds the development of a next-generation risk prediction platform. By integrating physics-based models, deep learning, and atmospheric foundation models, the project aims to overcome current limitations in predicting destructive events on sub-seasonal to seasonal timescales. Key technical goals include the creation of high-resolution hazard maps and a stochastic event simulator capable of generating synthetic scenarios that reflect future atmospheric conditions, thereby improving predictive accuracy and uncertainty quantification. The commercial objective is to provide the global insurance and reinsurance markets with timely risk prediction data to enable more precise pricing and reduced coverage gaps. The project will be delivered via a SaaS platform with API-based integration and tiered subscriptions for enterprise clients, governments, and energy providers. By combining AI with atmospheric modeling, the technology seeks to establish a competitive advantage over historical-data-based models, ultimately enhancing economic resilience and resource allocation in the face of changing climatological patterns.
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