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20 June 2025

Our GenAI empowers Suzuki sales channel in Spain

From AyGLOO, the Spanish company of the Mashfrog Group, a conversational LLM solution using RAG technique to provide fast and detailed information about car models. Easy to use for sales staff, effective and real-time for buyers.

suzuki

Suzuki, a global automotive brands leader, has embarked on a digital transformation journey in collaboration with AyGLOO, the Spanish company of the Mashfrog Group specialized in Artificial Intelligence, integrating GenAI to enhance its online sales channel around Spain.

In the Iberian market, Suzuki relies on a network of 650 dealers and a team of 200 agents, maintaining a close and continuous relationship with end customers (to give an idea: they handle around 2,000 inquiries every day related to the new Swift model alone).

Faced with the need to expand its market presence and facilitate access to key information about its vehicles, Suzuki has implemented a virtual assistant that not only improves the user experience but also provides real-time insights into customer preferences and concerns.

Thanks to this innovative solution, the company now has a dynamic communication and analysis tool that enables it to adapt its offering to market demand with greater precision and efficiency.

The challenge: clarity and speed

Suzuki is in the process of innovating and achieving competitive differentiation in the market, but it faces a big problem: it needs to reach a broader market and facilitate the distribution of key information about the vehicle.

Its objective is to offer details about the product, features, financing options and comparisons with other competing models. However, the biggest challenge lies in ensuring that potential customers receive this information clearly and appropriately, without having to navigate multiple channels or make considerable effort to compare models.

The solution: GenAI to engage with customers

The integration of a conversational solution powered by generative Artificial Intelligence into Suzuki's operations represents a significant step forward in how the company engages with its customers.

This technology enables Suzuki to deliver detailed and structured information about its various models instantly and in a personalized way. The system excels at providing accurate, real-time responses, eliminating the need for customers to browse through lengthy brochures.

By enabling direct and efficient interaction, it ensures each inquiry is addressed with relevant information, significantly enhancing the user experience.

Advanced technology, simple to use

At the core of the solution is a Large Language Model (LLM) specifically trained on Suzuki’s warranty documentation. We used a technique known as Retrieval-Augmented Generation (RAG), which allows the model to query the technical manual in real time to find the most relevant and accurate information for each case.

The Suzuki employee simply enters the claim details into a very simple web interface. The system uses a semantic search engine to “understand” the query and search the manual not just by keywords but by the meaning and context of the issue. The AI analyzes the information and returns a clear recommendation (approved, denied, or requires review) along with the exact excerpt from the manual that justifies the decision.

The solution functions as a standalone tool through a custom web interface, designed to be intuitive and not require technical training for the warranty team. Its goal is to be a digital assistant that streamlines their daily workflow.

The results: precision, speed, and personalization

The implementation of a GenAI solution in Suzuki's sales channel represents a major step forward in how the company engages with its customers. This technology enables Suzuki to deliver highly personalized and accurate information tailored to each individual user.

Moreover, the system captures and analyzes the full scope of customer interactions, generating dashboards with key performance indicators. This allows business managers to extract valuable insights and continuously adapt the system’s behavior based on customer needs.