Iaa, Inc.

Allstate Insurance Company

Iaa Holdings, LLC

Michael Cornelison

Anurag Sharma

David L Gilkison

Steven Genc

Pinal Patel

David M Zahn

Andrew Daniels

Shawn Caswell

Daniel Brickman

Maju Abraham

Subbu Viswanathan

Ryan Fagan

Stephen Muscarello

Ashish Kashyap

Mark Oost

Meggan O'Malley

Meggan O′Malley

Systems and apparatuses for generating surface dimension outputs are provided. The system may collect an image from a mobile device. The system may analyze the image to determine whether they comprise one or more standardized reference objects. Based on analysis of the image and the one or more standardized reference objects, the system may determine a surface dimension output. The system may determine one or more settlement outputs and one or more repair outputs for the driver based on the surface dimension output.

Processing system having a machine learning engine for providing a surface dimension output

Aspects of the present disclosure relate to automated vehicle condition grading. In examples, a set of images for a vehicle are processed using a machine learning engine to generate an optical vehicle condition grade for each image of the set. The resulting set of optical vehicle condition grades may be aggregated to generate an aggregate optical vehicle condition grade for the vehicle. In some examples, additional information associated with the vehicle is processed, which may be used to generate an adjustment grade. Accordingly, the adjustment grade and the aggregate optical vehicle condition grade are used to generate a final vehicle condition grade for the vehicle. The final vehicle condition grade is associated with the vehicle in a vehicle condition grade data store for subsequent use by the vehicle grading service and/or by an associated client device, among other examples.

Automated vehicle condition grading

A computer-implemented method of generating electronic documents is described. The method comprises receiving a plurality of scanned documents for a plurality of vehicles; providing the plurality of scanned documents to a neural network model that outputs respective class identifiers of the plurality of scanned documents; for each scanned document of the plurality of scanned documents, extracting data from the scanned document according to a corresponding class identifier, and associating the scanned document and the extracted data with an identified vehicle of the plurality of vehicles, wherein the identified vehicle is identified by the extracted data; and generating an electronic document for the identified vehicle using the extracted data.

Automated data extraction and document generation

Processing systems and methods having a machine learning engine for providing a surface dimension output

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LaGrange Highlands, IL, United States of America

Michael Cornelison