Vehicle status analysis mechanism

Abstract

There is provided a system for generating instructions for a generative model to present vehicle damage assessment. The system includes image sensors positioned at different heights and angles to capture vehicle images, a communication element for receiving images and accessing a stored model, and a processor connected to endpoint devices via a network. The processor generates instructional inputs combining damage severity classifications with vehicle images, sends these to the generative model, and obtains natural language elements for structural damage reconstitution. The system creates interactive presentations with populated template fields and classification selection elements displayed on endpoint devices. When users select different damage severity classifications in real-time, the system automatically generates new instructional inputs, obtains updated natural language elements from the generative model, and dynamically updates the presentation by replacing template fields. This enables real-time comparison of different damage severity assessments for the same vehicle damage using the same source images.