IQTransit partnered with a rental vehicle inspection company to design and develop a next-generation AI-driven inspection platform. The solution leverages computer vision to automatically detect vehicle damage, improving accuracy, accountability, and efficiency for rental agencies and logistics fleets.

Solution Overview

The platform supports automated photo capture and damage recognition through deep learning models trained on large-scale real-world vehicle imagery. Integrated with a microservice architecture, the system provides instant AI-powered analysis via a secure web dashboard. The solution was designed with scalability in mind, ensuring rental companies and logistics providers can process thousands of inspections in real time with high reliability.

• Computer vision models identify dents, scratches, and structural anomalies with high accuracy.
• Microservice-based design ensures scalability and modularity for future feature additions.
• Web dashboard provides instant results with AI confidence scoring for transparency.
• Seamless integration with existing fleet management software and APIs.

Impact

• Reduced manual inspection effort by over 60%.
• Enhanced accuracy in identifying dents, scratches, and structural damage.
• Improved accountability with image-based, time-stamped reports.
• Real-time inspection scoring and AI confidence ratings for quick decision-making.
• Adopted by rental agencies, logistics fleets, and marketplaces to cut operational costs.

Technologies Used

• Backend: Java, Grails Framework, MySQL, Microservices
• Frontend: HTML5, CSS3, Bootstrap 4, JavaScript (Vanilla)
• AI & Computer Vision: Python, PyTorch, TensorFlow, YOLOv5
• Infrastructure: Hosted entirely on AWS (EC2, S3, RDS, Lambda)

This case study demonstrates IQTransit’s ability to blend AI innovation with scalable cloud architecture. By integrating computer vision, microservices, and AWS, we helped standardize inspections, reduce costs, and deliver measurable value for high-volume fleet operations.