For more transparency in the automotive market


(Published in The Produktkulturmagazin issue 2 2019)

Those wishing to purchase a new car can either go to a car dealer or browse online platforms and websites. Maintaining an overview here is difficult, and how do you know whether the information you are being given is actually accurate? Ultimately, a new car also represents a financial risk, particularly in the case of used vehicles. To create greater transparency for all parties in these situations, Twinner has developed a solution with which a full ‘Digital Twinn’ of vehicles can be generated, hence minimising the risk for buyers and helping create a more stable sale for the vendor. And this is merely one of the numerous potential applications. At Twinner, we spoke to Geert Peeters about the way the technology works and its benefits.

Mr. Peeters, how did you come up with this idea? 

The idea for Twinner came from an experience with contactless robots for wheel alignment at the former parent company API, and the vision of completely digitalising a vehicle. On this basis, API started examining the holistic optical and sensor-based mapping of vehicles back in 2015, thinking about business models and constructing and making them practicable. In June 2018, we were able to finally unveil the product, the Twinner Space, to a select group for the first time. Twinner has been autonomous since 2019. Ultimately, a Digital Twinn can be created for anything. The concept is therefore being rolled out in all sectors – for example, in the healthcare sector, where – based on MRI scans – operations can be carried out in parallel. This is a multifaceted topic which focuses on the general dematerialisation of the industry. Everything is managed in a data-driven manner and it is only at the end of the value chain that the actual physical product is touched again.

What demand are you catering to within the market?

For example, the trade can use our services to secure customer trust online by providing maximum transparency. By the way: we create a Digital Twinn for a used car for all parties involved in the sale process – from the dealer to the end customer. This creates objectification and information symmetry for all parties, which are available at any time and at any location. The car trade overcomes time and space. And the Digital Twinn releases tremendous potential in the process. Can you actually buy a car on No. With our Digital Twinn, we are dissolving two major uncertainties within the market, among other things. First: the condition and the value actually correspond to the photos and the written description (because a Digital Twinn has been objectively created and assessed). Second: the vehicle actually exists. We used to have bookshops, we now have Amazon. We used to have CDs in stores, we now have Spotify. We used to have road maps, we now have Google Maps. Many sectors are currently experiencing what happens when time and space are dissolved. Among other things, Twinner makes it possible for dealers to complement their e-commerce operations: the first dealers are considering allowing customers to reserve and/or purchase vehicles directly online. Furthermore, the end customer can actually make a decision to purchase online on the basis of a Twinn. This has not been possible to date, as photos alone are unable to provide comprehensive information. We have detected a particularly positive impact on process costs, the time vehicles spend on the forecourt and media reach in the used car trade: firstly, process and transaction costs fall as a result of fully automatic digital execution. Because the Digital Twinn is created in a matter of a few minutes, employees do not have to enter the data and photographers do not need to be on site. The vendor is burdened to a lesser extent, while quality simultaneously increases. Secondly, the dealer can offer the product online more quickly and more transparently and clearly differentiate from other offers – hence increasing turnover and reducing the time vehicles spend on the forecourt. And, thirdly, transparent online presentation and the resulting end customer trust increases the media reach. Because if everything is transparently presented with advantages and defects, and the customers are also able to reserve the vehicle online, they will be willing to consider travelling further to collect cars. In addition to this, the price discussion changes: today, many people automatically factor in a certain risk when purchasing a used car and try to offset this by asking the dealer for a price reduction. Since Twinner reduces this risk due to the most transparent and objective representation possible, it also stabilises purchase prices. 

How exactly is a Digital Twinn created?

Creating a Digital Twinn starts with the vehicle being registered on the system. For this, Twinner uses a so-called VIN – vehicle identification number – in order to unambiguously identify the vehicle. In the next step, the vehicle is driven into the Twinner Space and the digitalisation process starts. Here, digitalisation comprises an optical and sensor-based scanning of the vehicle, whereby we measure the vehicle upon entry, determine the tyre profile depths and photograph the vehicle undercarriage. The vehicle is then photographed on a turntable – both with the doors closed and open – and scanned using a so-called repaint scanner. As soon as the measurements and photos have been completed, the vehicle is rotated by 180 degrees and can be driven out of the Twinner Space. The data is then uploaded to the Twinner Cloud and turned into a Digital Twinn using a series of algorithms and other software processes. The entire process generally takes, for the simplest version, between two minutes and, for full digitalisation, seven minutes before the data set is made available to the customer. However, the Digital Twinn is then also immediately available for the individual processes and could, for example, be placed on the customer’s website or selling platform. 

What interfaces does Twinner currently offer for integration into the users’ software systems and how should its data management be ideally structured in order to draw the greatest possible benefit from Twinner? 

We are approaching this very simply and pragmatically: we are collaborating with third-party vendors, such as DAT and Schwacke, for instance, and are creating functioning interfaces to their systems. If a partner takes over data from Twinner, we offer access to all the data model’s public data by means of REST interface. The partner can access this data depending on which data is relevant to their business model.

Who are you addressing with your business model?

The Digital Twinn is transaction-based. We sell digitalisations. For our customers, this has the benefit that no investment is required – hence keeping potential obstacles to digitalisation to an absolute minimum. With the market launch, we have started by signing initial contracts with major car dealerships. But there are very many more examples of further potential applications. With Twinner, we are not only able to support the marketing of vehicles, we can also keep track of all documentation and transfers of ownership. Twinner is interesting to vehicle leasing companies, used car service providers, corporate fleets, manufacturers, car rental businesses, captive banks, insurance companies, surveyors and many more.

Who determines what ‘normal’ signs of usage are and what represents damage?

A central question within the market as it is treated in a very opportune manner. Twinner will, however, not dwell on this question for long, because the more vehicles we digitalise, the more clearly we are able to distinguish between usage and damage. Based on the mileage and registration details, damage profile clusters can be compiled from which a mean value can be derived for what is deemed to be ‘normal’. Twinner generates the decisive advantage that all subjective elements can be excluded from the assessment.

How do you ensure that the value is not falsified and hence reliable information can be provided regarding the vehicle’s condition?

A value is always determined on the basis of a snapshot, which is why we can ensure this. The vehicle data set is consolidated, saved in the Twinner Cloud and can then no longer be changed in its original state. If a second Digital Twinn is created for the same vehicle, this is linked to the old data set, ensuring we present an historical value development on this basis and can therefore document the entire vehicle lifecycle.

With the Digital Twinn, you automatically gain access to a considerable volume of vehicle data and hence a valuable insight into the automotive market. What further applications do you see for this data in the future?

The central objective is to achieve equality of information between buyer and vendor, generating exciting applications in the process. This includes vehicle financing and insurance too – although repair requirements can also be viewed differently. Particularly for all emerging new mobility concepts, Twinner is able to support business model providers and offer end customers certainty. 

You have been able to secure considerable investor funding. In which areas are you planning to invest in the short to medium term and what concrete developments can we expect?

The secured additional capital will be predominantly used to expand the Twinner system’s market and to develop the product itself. Here, the two main focuses are on establishing further development resources and on national and international sales. 


The experienced IT and e-business manager has been Managing Director of the start-up company Twinner (formerly APi Automotive Process Institute GmbH) since 2017. His strength is the interface between product development and market opportunities of online products and platforms.

Picture credit © Stefan Veres

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