A global automotive manufacturer drives customer support into the future with Elasticsearch

As one of the world's most distinguishable automobile brands, the company is a premium manufacturer with nearly a century of historic innovation and is importantly recognized for its commitment to safety and sustainability. The customer-focused company has extensive support networks in APAC, EMEA, and the Us. Hundreds of customer support agents in EMEA handle diverse inquiries via phone, email, chat, and social media. The automotive manufacturer emphasizes proactive driver care alongside vehicle maintenance, reflecting its commitment to quality and customer support.

The support team serves as the first point of contact for customers, whether they need assistance ordering a car, booking maintenance, or troubleshooting an issue. The engineering manager at the leading automotive brand says, "We live in a world of instant information and instant answers. Any delays or inconsistencies in responses can negatively impact customer satisfaction and, ultimately, the company's brand reputation."

This is where Elastic and its generative AI search features come into play. With the right data architecture and large language model (LLMs), customer service agents can query multiple systems and receive concise, accurate, up-to-date answers. This is essential for the business, where information is stored across multiple content management systems and translated into 27 languages.

In the past, customer service agents sometimes had difficulty locating information and often resorted to messaging colleagues, leading to inconsistent answers and slower response times. "Elastic gave us the opportunity to provide agents with a unified, easy-to-use search interface without needing to overhaul our systems and onboard separate teams onto a single platform," says the engineering manager.

With Elastic, the engineering team has transformed the way the company's support agents access information. Previously, agents relied on multiple disconnected systems, manual searches, and internal chats to find answers. With Elastic's hybrid search capabilities, they can now retrieve relevant knowledge instantly. Additionally, agents can now search in either English or their local market language, improving accessibility and efficiency across the brand's global support network.

"The biggest improvement is that agents can find the right information in a single step. They no longer have to search across different platforms or ask colleagues for help."

To enhance information retrieval, especially for FAQs and knowledge search, a hybrid search strategy is crucial. This method allows search queries to analyze both textual data from support manuals and vector embeddings that understand multilingual support instructions. Elastic facilitates hybrid search by integrating datasets and delivering results within a single query. When combined with vector search, this ensures customer support agents receive concise and accurate answers instead of lengthy, disorganized documents.

The team was very impressed with Elastic's hybrid search performance, especially for multilingual support Q&A. They felt confident in rolling it out to customers across EMEA, which led to operational complexities in running the search infrastructure. At this point, the team decided that a move to Elastic Cloud on Microsoft Azure to streamline operations and reduce overheads would be prudent. "With Elastic Cloud, upgrades are seamless, there's no downtime, and our engineers can focus on building business logic instead of maintaining infrastructure," says the engineering manager.

The company's platform team partnered with Elastic's professional services team who provided architectural guidance and helped to build a scalable and efficient search solution.

"When we worked with Elastic, it wasn't a sales pitch — it was a technical engineering conversation, and that helped to ensure we were aligned. The Elastic team understood our challenges and provided concrete suggestions that helped us build the right solution."

With Elastic handling millions of search queries across the brand's knowledge base, performance is critical. The search engine delivers faster response times, ensuring that agents are not left waiting for results.

Elastic's flexible ingestion pipeline enables the company to index both structured and unstructured content, including PDFs, attachments, and proprietary CMs data. "The combination of vector search, inference APIs, and machine learning nodes has significantly improved retrieval accuracy," says the engineering manager.

Unlike other vendors that might have multiple disconnected tools that can create complexity, Elastic provides a cohesive platform full of features that are designed to work together, and everything is in one place. As a result, the business now has a clear roadmap for further AI enhancements to its customer service search initiative in the future. These include AI-powered observability and Microsoft's E5, a small, optimized, natural language processing model for multilingual semantic search; E5 is built-into Elasticsearch, providing a native user experience.

The road is now clear for further AI enhancements to customer service. "With Elastic's hybrid search, AI-driven capabilities, and cloud scalability, the company has built an intuitive, future-ready search platform that enables a premium experience for their premium customers that ensures premium service for premium customers,"" says the engineering manager.