Auto Intelligence

We create intelligent technology solutions and services for the automotive industry and mobility service contractors. Our technological developments are based on our long-term expertise in Machine Learning, specialized algorithms and Big Data analyses. Our consulting service is fed from a pipeline of innovative research ideas.

We transform our technology into intelligent services that are scalable and easily put together. For this we build on strong partnerships with OEMs and sector experts. Our solutions have already been productively implemented in important areas of the automotive industry and have received numerous awards.

We help you assess your technology and are working on safeguarding and certification processes for AI applications. Ultimately, providing proof that partially autonomous vehicles with integrated AI are safe is a huge challenge for research and development.

Portfolio of service

Our customers are the automotive industry, external suppliers, local public transport and car sharing providers. We help the automotive industry assess technologies specifically targeted for their purposes and to integrate them into strategies for their products. We help create movement models from a range of inhomogeneous data sources and enhance them by applying Machine Learning procedures. Our work encompasses intelligent services and the development of special solutions right up to the safeguarding of AI-based functions for autonomous driving.


through modular software architectures linking services depending on demand

Specialized technology strategies

through the analysis of requirements and need-based innovations

Mobility analyses

through data-driven traffic modeling for fleets

Data-driven components in vehicles

through the development and adaptation of transparent ML solutions

Safeguarding measures in autonomous driving

through research and development of new ML procedures based on Deep Learning


Lifestyle configurator

Purchasing a vehicle as a digital experience

Buyers want to have their new car specified to their personal requirements. However, many feel overwhelmed by the vast choice of options available to them. In cooperation with Berylls we developed the "Mercedes-Benz Lifestyle Configurator" which uses images to establish a customer’s lifestyle and matches it to suitable car models which it then recommends. The configurator was awarded three Red Dot Awards for customer dialog innovation and the Automotive Brand Contest’s "Best of the Best" digital award. The highlight: Instead of focusing on models, engine sizes or accessory packs the dialog with the customer asks about their preferences such as what type of architecture, leisure activities and means of transport they enjoy.

Transparent vehicle assistance system

If the occupants of a car are to accept and use intelligent vehicle functions they have to be transparent and trust needs to be established. Together with the Volkswagen research team we developed an AI-based system for a concept vehicle that dynamically adapts to the car occupants’ behavior. Communication was key during the development stage of this infotainment system: Whichever decisions AI makes must be plausible and comprehensible for the people in the car.

Safeguarding measures in autonomous driving

Under the leadership of Volkswagen, and together with BMW and Bosch, we are working on safeguarding AI-based perception functions for automated, driverless driving. Most importantly, we are developing methods and measures that help recognize pedestrians and read their behavior in urban traffic. By actively involving normative boards and certification bodies it is hoped there will eventually be an industry-wide AI test strategy consensus.

Mobility analyses for local public transport systems of the future

Key to the research project is designing a future-proof local public transport system able to react flexibly to changes in demand. An app is used to analyze people’s mobility behavior by collecting high resolution mobile data relating to space and time. By evaluating the extrapolated multimodal mobility mix it becomes easier to steer planning proposals and to establish novel and transparent billing models for linked transport systems.