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About
Sust Global is an enterprise-grade Geospatial AI platform purpose-built for organizations operating at the intersection of climate science and financial decision-making. Its core engine ingests and harmonizes multimodal datasets—including satellite imagery, meteorological records, and proprietary geospatial signals—to generate high-resolution physical climate risk assessments at the asset and portfolio level. The platform supports scalable processing of over one million global assets, delivering physics-based models transformed into actionable intelligence across hazard categories such as wildfire, heatwaves, drought, sea level rise, and wind exposure. Outputs are accessible through intuitive analytics dashboards or via API integration, enabling seamless embedding into existing risk management workflows, TCFD reporting frameworks, and investment due-diligence processes. Sust Global's technology has been adopted by leading financial institutions, ESG advisors, utilities, and conservation organizations to meet growing regulatory and stakeholder demands around climate risk disclosure. The platform integrates with third-party data providers—including partnerships with Yield Book and the London Stock Exchange Group—to power next-generation geospatially informed investment strategies. Acquired by ISS Stoxx, Sust Global continues to advance the frontier of climate AI, with research presented at venues such as ICLR 2025. It is the go-to solution for enterprise clients who require credible, global-scale climate risk data that meets the rigor of institutional finance and sustainability reporting.
Key Features
- Multimodal Geospatial Data Fusion: Collects, indexes, and harmonizes diverse data sources—including satellite imagery and environmental datasets—using proprietary geospatial AI techniques for high-fidelity inference.
- Asset & Portfolio-Level Climate Risk Metrics: Generates granular risk scores for wildfire, drought, heatwaves, sea level rise, and wind across 1M+ global assets, enabling comprehensive portfolio risk management.
- Physics-Based AI Models: Combines physics-based climate models with machine learning to deliver scientifically rigorous, forward-looking risk projections across multiple climate scenarios up to 80 years into the future.
- Intuitive Analytics Dashboards: Provides rapid upload, processing, and visual exploration of geospatial risk data through user-friendly dashboards requiring no specialized GIS expertise.
- API & Third-Party Integration: Offers API-based data delivery and seamless integration with third-party platforms, enabling embedding of climate risk intelligence into existing investment and risk workflows.
Use Cases
- Institutional investors assessing physical climate risk exposure across real estate, infrastructure, or fixed-income portfolios to inform asset allocation and due diligence.
- ESG and sustainability teams generating TCFD-compliant climate risk disclosures for regulatory filings and stakeholder reporting.
- Utilities and energy companies modeling the impact of climate change on renewable energy generation assets such as wind farms and solar installations.
- Conservation and land management organizations analyzing climate hazard exposure across geographically dispersed natural assets and conservation easements.
- Mortgage-backed securities (MBS) investors integrating geospatial climate risk metrics into bond pricing, portfolio construction, and credit risk assessment.
Pros
- Enterprise-Grade Scalability: Capable of processing over one million global assets with a robust pipeline, making it suitable for large institutional investors and asset managers.
- Regulatory & Reporting Alignment: Outputs are designed to support TCFD reporting, ESG disclosure frameworks, and sustainability compliance, reducing the burden of regulatory preparation.
- Trusted by Leading Institutions: Adopted by major financial institutions, ESG advisors, utilities, and conservation organizations, reflecting strong credibility and reliability in the market.
- Long-Horizon Climate Projections: Provides climate risk projections across multiple scenarios extending up to 80 years, supporting long-term strategic planning and asset valuation.
Cons
- Enterprise Pricing Model: Access requires contacting sales for a demo, with no self-serve free tier available—making it less accessible for smaller organizations or individual researchers.
- Specialized Use Case: Primarily focused on physical climate risk for institutional finance and ESG contexts, limiting relevance for general-purpose geospatial or analytics applications.
- Integration Complexity: Full value extraction may require technical resources to integrate the API and harmonize outputs with existing internal data systems and risk models.
Frequently Asked Questions
What types of climate hazards does Sust Global cover?
Sust Global covers a wide range of physical climate hazards including wildfire, heatwaves, drought, sea level rise, and wind exposure, with projections available across multiple climate scenarios and time horizons up to 80 years.
How does Sust Global deliver its data and insights?
Clients can access climate risk intelligence through intuitive web-based analytics dashboards or via a robust API, enabling integration into existing portfolio management, risk, and reporting workflows.
Is Sust Global suitable for TCFD reporting?
Yes. The platform is specifically designed to support TCFD (Task Force on Climate-related Financial Disclosures) reporting by providing credible, granular, asset-level physical climate risk data aligned with regulatory requirements.
How many assets can Sust Global process?
The platform features a scalable processing pipeline capable of handling over one million global assets, making it suitable for large institutional portfolios across geographies and asset classes.
Who acquired Sust Global and what does that mean for users?
Sust Global was acquired by ISS Stoxx, a leading provider of data and analytics for institutional investors. This acquisition strengthens the platform's data resources and distribution reach, with continued development of its climate AI capabilities.
