at least one processor;

a communication interface communicatively coupled to the at least one processor; and

memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

receive, from a first data source, historical images comprising aerial images of a plurality of residential properties;

receive, from a second data source, historical inspection data indicating historical inspection results corresponding to one or more of the plurality of residential properties;

train a roof waiver model of a neural network computer vision model, using a machine learning engine, the historical images, and the historical inspection data, wherein training the roof waiver model configures the roof waiver model to output inspection prediction information directly from an image using a set of rules, and wherein the neural network computer vision model correlates the historical inspection data with the corresponding historical images and generates a labelled set of training data for training the roof waiver model, and wherein the machine learning engine iteratively refines the roof waiver model in response to new images;

receive, from the first data source, a new image corresponding to a particular residential property;

analyze, using the roof waiver model, the new image, wherein analyzing the new image directly results in output of a likelihood of passing inspection;

update the roof waiver model in response to the new image; and

send, to an enterprise user device, inspection information, based on the likelihood of passing inspection, and one or more commands directing the enterprise user device to display the inspection information, wherein the inspection information indicates whether or not a physical inspection should be performed, and wherein sending the one or more commands directing the enterprise user device to display the inspection information causes the enterprise user device to display the inspection information.