Challenge

An Automotive Giant's dealer and customer service teams faced delays and inefficiencies in responding to part enquiries. Manual processes meant turnaround times stretched from hours to days, frustrating customers and reducing retention. Errors in part identification and availability created further operational bottlenecks, while increasing enquiry volumes placed pressure on staff. Daimler needed a scalable, accurate, and efficient solution to deliver real-time responses without driving up costs.

Solution

Digile implemented a Gen-AI powered enquiry platform on Microsoft Azure, leveraging NLP, Qdrant, and LangChain to streamline the entire process.

The solution included:

• AI-powered part retrieval trained on historical ticket data for NLP-driven accuracy.
• Smart VIN-based and descriptive part lookups, even with incomplete or inconsistent details.
• Automated closures for confidential material requests and direct ticket creation.
• Continuous AI knowledge management with self-learning capabilities for smarter support over time.

The architecture was scalable, secure, and designed to automate workflows while reducing manual effort, freeing staff to focus on higher-value tasks.

Technology Used

The following technologies were utilized in the managed services and integration solution:

1. Microsoft Azure
2. Python
3. Qdrant
4. Langchain