Repath offers an AI‑driven platform that combines machine learning with high‑resolution Earth observation data to deliver asset‑level physical climate risk assessments and quantified financial exposure. The solution provides interactive dashboards, adaptation ROI calculations, and audit‑ready reports to help infrastructure owners and operators prioritize resilience investments and meet ESG, CSRD, and EU taxonomy compliance.
Funding
$4M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
3OFounders
Product
Problem
Infrastructure assets such as power grids, wind turbines, solar farms, rail lines, data centres and roads are increasingly exposed to extreme weather and long‑term climate change, leading to physical damage, operational downtime and financial losses. Traditional risk assessments rely on generic regional scores and lack asset‑level detail, making it difficult for owners and operators to prioritize adaptation investments and meet emerging ESG and regulatory requirements.
Solution
Repath provides an AI‑driven climate risk analytics platform that combines machine learning with high‑resolution Earth observation data to deliver asset‑specific physical risk assessments. The engine incorporates each asset’s design specifications, age, material composition and location to model exposure to hazards such as flooding, heat stress, wind gusts and storms across multiple future climate scenarios. Results are expressed as quantified financial exposure and adaptation return‑on‑investment, enabling users to prioritize upgrades, balance CAPEX versus OPEX, and generate audit‑ready reports for ESG, CSRD and EU taxonomy compliance. The platform offers interactive dashboards for portfolio‑wide overviews and drill‑down views to individual components, supporting proactive, data‑backed resilience planning.
Target Audience
Primary customers are infrastructure owners and operators—such as utilities, renewable energy developers, transport agencies, data‑centre managers, and large‑scale investors—who need asset‑level climate risk insight for resilience planning and regulatory compliance.
Features
- Machine‑learning models that fuse decades of climate observations with asset‑level technical data to predict physical vulnerability
- Hazard mapping for each asset (e.g., substations, turbines, panels, data‑centre cooling systems) including flood, heat, wind and storm exposure
- Financial impact quantification and adaptation ROI calculations across short‑, medium‑ and long‑term climate scenarios
- Interactive dashboards that visualize portfolio risk, enable drill‑down to component level, and generate audit‑ready compliance reports
- Scenario analysis tools for CAPEX/OPEX planning, allowing users to compare adaptation strategies and prioritize investments
- API integration for ESG, CSRD and EU taxonomy reporting workflows