Revvitalize Automotive Inc. aims to enhance the efficiency of identifying and matching used car parts with compatible vehicles. The current process is manual and time-consuming, often leading to errors and mismatches. The goal of this project is to develop an AI-driven system that can accurately identify used car parts and determine their compatibility with various car models. This system will leverage image recognition and machine learning algorithms to analyze part features and cross-reference them with a database of vehicle specifications. By automating this process, Revvitalize Automotive Inc. seeks to improve accuracy, reduce time spent on manual checks, and enhance customer satisfaction. The project will involve tasks such as data collection, model training, and system integration, all of which align with the skills of students in a computer science or data science program.

The project deliverables include a functional prototype of the AI-driven system capable of identifying and matching used car parts with compatible vehicles. Students will provide a detailed report documenting the development process, including data collection methods, algorithm selection, and system testing results. Additionally, a presentation will be prepared to demonstrate the system's capabilities and potential impact on operation of Revvitalize Automotive Inc.'s platform. These deliverables will showcase the practical application of classroom knowledge in AI and machine learning.