Customers get a damage assessment in a maximum of 5 minutes. Insurers get a quick overview of the total claims volume in an affected region. Modular AI algorithm allows rapid expansion of the business model. Zühlke supports the German company PDR-Team in the development of a mobile hail damage scanner and uses Deep Learning to create a flexible, future-proof and scalable solution. Starting position - Automated, mobile and autonomous assessment For a hail damage assessment including valuation, an assessor needs about 40 minutes. PDR-Team wants to change that: using a system that automatically and reproducibly determines the number and size of hail dents on a car – with 90 % accuracy. The solution has to work on the go and without an internet connection, and is intended to expand to include other types of claims in future, resulting in high requirements where the scalability of the hardware is concerned. In addition, the solution needs to be cost-effective to ensure that vehicle insurers can use it for a reasonable price while still achieving a profit. Solution - A finished demonstrator in four months Building on the concept and hardware from PDR, Zühlke developed a computer vision solution based on CNN and completed a finished demonstrator in just four months. The solution is fully integrated into the existing system architecture. This saves PDR from having to make major investments in additional hardware. The flexible solution uses different methods of object tracking, segmentation, and the detection and measurement of dents and dent patterns. The modular structure of the AI algorithm allows flexible expansion to include other types of claims in future development steps. ' Zühlke’s clear perspective enabled us to quickly identify the problem with our concept and, based on existing AI experience, to implement a more secure, flexible and cheap solution. ' Nathanael Alain Managing director PDR-Team Benefit More speed, accuracy, flexibility and less costs The solution offers speed, accuracy and cost benefits for customers and insurers. The finished assessment is available in less than five minutes – with an accuracy significantly higher than the 90 % initially specified. Insurers get a quick overview of the total claims volume in a region. By applying the principle to other types of damage, the business model can be expanded quickly. Contact person for Germany Tobias Joppe Director Customers Solutions Tobias Joppe studied automation and control engineering at the TU Braunschweig and was most recently head of a innovation team at Siemens AG. He has been with Zühlke since 2008, is a partner and, as Director Customers Solutions, is responsible for the Trend Lead Data Science in Germany. In his role, he builds the bridge between cutting-edge technology and current customer needs. Together with customers, he translates visions and goals into a strategic roadmap and concrete project procedures. As Director Customers Solutions, many completed interdisciplinary projects form the basis of his experience. Contact tobias.joppe@zuehlke.com +49 511 220 021 43 Your message to us You must have JavaScript enabled to use this form. First Name Surname Email Phone Message Send message Leave this field blank Your message to us Thank you for your message. Our work Banking, Commerce and Consumer Goods Zühlke's GenAI Project Finder boosts presales efficiency Learn more Government & Public A new strategy to consolidate market position Learn more Energy & Utilities, Government & Public Innovate UK demonstrates how data ecosystems can support decarbonisation Learn more Go to case studies Deliver transformative impact with Zühlke. Speak to our team today. Get in touch
' Zühlke’s clear perspective enabled us to quickly identify the problem with our concept and, based on existing AI experience, to implement a more secure, flexible and cheap solution. ' Nathanael Alain Managing director PDR-Team