Abstract: The disclosure includes a system and method for determining climate risk using artificial intelligence including receiving a location of a property from a user; obtaining property data associated with the property, wherein the property data includes image data of the property; determining, using a first climate risk model associated with a first climate risk, a first score associated with the property, the first scores representing a first climate risk to the property; and determining, using a second climate risk model, a second score associated with the property; presenting the first score representing the first climate risk to the property and the second score associated with the property to the user.

Abstract: Methods and systems are disclosed for identifying consumers likely to adopt a particular clean energy solution (e.g. solar solutions, such as rooftop panels or community solar offerings; electric battery storage; an electric vehicle; electric vehicle charging infrastructure; energy efficient appliances; etc.), which in some instances includes satellite image analysis of buildings used by consumers. In some cases, the methods can include using GIS data (e.g., LiDAR 3D point cloud data) to model roof facet surfaces and the amount of solar energy received by such surfaces. The methods can also include evaluating additional consumer-related data to predict consumers likely to adopt clean energy solutions. In other implementations, methods and systems are described for remotely sizing a particular clean energy solution based upon a user's submission of a particular address. Additional uses of energy-related data are also described.