Revolutionizing Vehicle Warranty Management with AI and Real-Time Data Integration

2025-28-0304

11/06/2025

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Authors Abstract
Content
This paper introduces an AI-powered mobile application designed to enhance vehicle warranty management through real-time diagnostics, predictive maintenance, and personalized support. The system supports multi-modal inputs (text, voice, image, video), integrates real-time On-Board Diagnostics (OBD) data, and accesses OEM warranty terms via secure APIs. It employs supervised, unsupervised, and reinforcement learning to deliver accurate fault detection, tailored recommendations, and automated claim decisions. Contextual analysis and continuous learning improve precision over time. The application also provides service cost estimates, part availability, and proactive maintenance alerts. This approach improves customer satisfaction, reduces warranty costs, and streamlines aftersales support.
Utilizing advanced AI and machine learning algorithms, the application interprets customer queries through multiple input modes—text, voice, video, and image—and retrieves relevant information from the manufacturer’s database to provide accurate and timely responses. Continuous data collection and learning (Model retraining monthly or quarterly as per new data availability) enhance the system’s precision over time, significantly improving customer satisfaction and support quality.
Beyond warranty management, the application offers comprehensive features such as product quality assessments, tailored servicing plans, estimated service and replacement costs, part availability from nearby dealers, and streamlined warranty support requests. By analyzing contextual factors like vehicle make, model, usage patterns, and environmental conditions, the system delivers highly personalized responses.
Integration with real-time On-Board Diagnostics (OBD) data further refines the app’s capabilities, enabling it to address customer concerns with precision. As the system evolves through ongoing data accumulation, its machine learning models continuously improve, ensuring increasingly accurate and relevant support.
This holistic approach bridges the gap between vehicle owners and manufacturers, providing users with transparent, intelligent, and proactive warranty and maintenance solutions throughout the vehicle ownership lifecycle.
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Pages
10
Citation
Ramekar, V., and Chaudhari, H., "Revolutionizing Vehicle Warranty Management with AI and Real-Time Data Integration," SAE Technical Paper 2025-28-0304, 2025, .
Additional Details
Publisher
Published
Nov 06
Product Code
2025-28-0304
Content Type
Technical Paper
Language
English