Mitchell International, Inc.

Niv Genchel

John Milford Fletcher

Jerry Gastineau

Beau Sullivan

Julian Louis

Stefanos Makris

Kshitij Deshmukh

Juveria Kanodia

Craig A Schneider

Frederick Albert

A method, non-transitory computer readable medium, and apparatus that improves automated damage appraisal includes analyzing one or more obtained images of property using a deep neural network with multiple hidden layers of units between an input and output and which has stored knowledge data encoded from one or more stored property damage images to identify the part of the vehicle that has sustained damage. Damage data on an extent of the damage in the identified part of the vehicle is determined using the deep neural network which has stored knowledge data encoded from one or more stored property damage images. The identified generic part of the vehicle is used to obtain a corresponding Part ID Code by using a parts dictionary. Part Qualifier information obtained using VIN information is then used in conjunction with the Part ID to obtain the OEM-specific part and then generate one or more repair lines for the repair estimate.

Systems and methods for automatically determining associations between damaged parts and repair estimate information during damage appraisal

A collaboration message is received at a computer system network node of a computer network that operates in a decentralized arrangement such that network nodes comprise work process sources and destinations, and the collaboration messages convey process state updates among the collaborators. There is no central authority though which all process messages and state updates must pass and which thereby may create a system bottleneck and limit system growth. The computer system is scalable and system operation remains efficient with increasing numbers of network nodes.

Work process collaboration management

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San Diego, CA, United States of America

Niv Genchel