The Client & Challenge

Our client, Europe based premium car dealer struggled to deliver quick, accurate, and conversational responses to customer inquiries across its online car inventory. Their reliance on static FAQ systems and manual chat support resulted in slow response times, limited user engagement, and missed lead opportunities. This inefficient setup led to a poor customer experience and hindered the company’s ability to convert interest into action.  

Our client needed a more intelligent, scalable solution to provide real-time assistance and personalized interactions that could guide users through their vehicle exploration journey around the clock. 

The Solution & Outcome

To address this problem, we designed and developed a generative AI-powered chatbot tailored for our client, a major used premium car dealership in Europe. Trained on the company’s dynamic vehicle inventory and product data, the chatbot engages customers in natural, conversational interactions—answering detailed questions about cars and directing users seamlessly to relevant product pages. This solution significantly improves digital customer engagement and streamlines the vehicle discovery process. 

Built on a Retrieval-Augmented Generation (RAG) framework, the chatbot utilizes an in-house large language model (LLM) fine-tuned specifically for automotive data. It employs natural language processing techniques for context-aware querying and accurate product mapping. To ensure up-to-date information, a backend API automates daily updates to the knowledge base with new car listings. The technology stack features custom vector search over vehicle specifications, dynamic model retraining, and seamless integration with the client’s product database. 

The chatbot enhances customer engagement by providing 24/7 support, boosting lead conversion, and improving satisfaction. It reduces manual workload, speeds up vehicle discovery, and scales effortlessly to meet growing demand, becoming a vital digital sales tool.