Eoliann S.R.L. Società Benefit

Airis

Eoliann's Airis assesses the exposure of locations and assets to physical climate hazards across multiple time horizons and IPCC scenarios, applying machine learning to satellite Earth-observation data. It estimates hazard probability and severity plus indicative financial damage at asset and infrastructure level, delivered via platform and API for finance and real-asset users; the company is organised as an Italian benefit corporation and its tool is catalogued in the UNEP FI dashboard. A young, Earth-observation-led specialist, distinctive for combining satellite data with AI to produce fast, location-specific hazard analytics.

Vendor methodology

Transparency Score

Beta

Public transparency, not model quality iThe Transparency Score (0–3) estimates public methodological transparency: the degree to which the vendor's analytical approach to modeling climate and nature risk can be assessed from publicly available sources. It is explicitly not a measure of vendor quality or accuracy.

1

Product-level: public materials indicate risk scope and outputs, but little detail on modeling approach.

Product-level: public product and press materials name methodological elements (IPCC SSP1-2.6/2-4.5/5-8.5, 30 m resolution, ML on satellite data, ESA-supported validation) and the cause-effect modelling approach, though the model itself stays proprietary and no full methodology document is surfaced.

For further information, see the section 'Transparency Score methodology' in the Readme.

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