Olyslager’s core business is to answer a seemingly simple yet business-critical question: what lubricants and engine fluids does a specific vehicle need? In practice, the answer is complex. Every vehicle, engine type and market has different requirements, and the product selection from oil companies is extensive and constantly changing.
Our strategy for product development and innovation is based on real needs, clear business value and long-term value creation. Through close customer dialogues, cutting-edge technical expertise and a structured yet agile approach, we turn visions and investments into concrete, everyday solutions. A particular focus area is how to use AI in a safe, reliable and practical way in order to simplify, streamline and strengthen our customers’ competitiveness.
The following case illustrate how these principles are applied in practice in different industries and business contexts. The examples demonstrate how our companies combine customer insights, technical innovation and responsible development to create measurable effects – from better user experiences and improved efficiency to new business models and stronger societal benefit.
To handle this complexity, Olyslager has built a global data platform that connects the oil companies’ products with OEM vehicle data. The system is used by the leading oil companies around the world, and includes over 3.5 million unique products, which are connected to the right vehicle and engine type.
Olyslager’s product selector is mainly used by mechanics in workshops and is integrated into customers’ websites. By entering a registration number or VIN number, the user immediately gets the correct recommendation for lubricant or engine fluid – no matter where in the world the vehicle is located.
Many customers use Olyslager’s main system, LIS (Lubricant Information System), relatively rarely. To reduce the need for training and support, Olyslager has developed an AI-based smart guide with a chatbot. The guide leads the user through the system step by step, allowing even sporadic users to work efficiently – without any training initiatives.
Using AI, the mechanic can now take a picture of the license plate or VIN number (chassis number) with a phone or tablet, after which the system automatically identifies the vehicle. This process is both faster and more accurate than manual entry and lowers the threshold for use.
“Matching used to be done manually between Olyslager’s vehicle data and fluid products collected in external catalogs, such as TecAlliance and large American catalog systems, which took several weeks. With AI, the same work can be done in a few hours with about 95 percent accuracy, and the remaining discrepancies are quality-assured manually,” says Tom Rensink, CTO at Olyslager.
AI has made it possible to increase the update frequency from four to twelve times per year. Customers do not pay for AI itself, but for the value of more relevant and reliable recommendations. More frequent updates have therefore become a key offering.
Olyslager’s solution is used globally and is available in 33 languages. With AI and context-driven translation, terminology in the automotive industry can be handled properly. What used to take two months via external agencies can now be done in about an hour – with higher quality.
“The business model is based on recurring, fixed software revenue combined with payment every time the customer searches for a match. Through AI-driven simplification and improved user-friendliness, use of the system has increased by 45 percent in the past year,” says Tom Rensink.
For Olyslager, AI is not a goal in and of itself, but a strategic tool for simplifying complex processes, increasing use of the service and creating scalable and sustainable business value.
This article was originally published in Vitec's Annual report 2025