The AtomLeap High-Tech Accelerator has recently welcomed a fourth startup—Motor Ai—in the second round of our program. As is customary, we invited the team members to answer a few questions about themselves and what they do. Happy reading!
How did Motor Ai come to be?
For several years, we had been reading about how car companies were going to shift from business models focused on manufacturing to services. We had assumed that original equipment manufacturers (OEMs) were far ahead of startups when it came to digital services for the connected car and artificial intelligence (AI) to produce insights from the data. After talking to them, however, we discovered that the opposite was true: OEMs had no data to analyze and were only beginning to develop digital services. It was at this moment that we got the idea for Motor Ai. By pooling our combined skills in software and AI, we knew we could build a product that could unlock the huge market potential of the connected car for OEMs.
In your own words, what does Motor Ai do?
We take raw mobility data—visual, audio, or numeric—and refine it using our custom AI software to reveal the underlying logical associations between the data points. These “logics” give decision-makers the necessary facts to develop new products. Our Mobility Intelligence is continuously self-learning, meaning associations get stronger or weaker over time and new ones can emerge. It is also fully automated, meaning it produces valuable business insights even when you’re asleep. Almost every other AI product has to be tuned and turned on manually. We have eliminated that grunt work, freeing our customers up to spend more time on what they excel at, namely analyzing refined data.
We have also used our Mobility Intelligence in our first product—Knox. Knox is a device that can be installed in the front and rear windshields of any car and supports car owners with protecting their parked vehicles by collecting evidence in the event of accidents so that owners can report the incident to the appropriate authorities. Through this, perpetrators can be more easily identified and held responsible in the spirit of the cost-by-cause principle (Verursacherprinzip in Germany). The device is in a continuous stand-by mode and is woken up by anything in the car’s immediate environment that causes the car to move. Knox’s advantage is the ability to differentiate, based on the intensity of the movement, between an actual collision with the car itself and, for example, a vibration caused by a heavy truck passing by. We use our innovative artificial intelligence to analyze these nuanced responses so that owners only react to real hit-and-runs. This is Knox’s special advantage. If a movement is identified as a hit-and-run, Knox activates, solely for evidence collecting purposes, its cameras. Each of these cameras has a 180-degree field of vision. Through this, Knox can identify not only the perpetrator’s car, but also the license plate. The recording is then securely uploaded to a server, which sends a notification to the cellphone of the car owner. The car owner can then view all the information of the hit and run incident in a smartphone app.
What problem(s) are you hoping to address through your solutions?
We are addressing two huge problems in the field of AI. First, by producing an automated self-learning system, we have eliminated the tedious cycle of manually training, testing, and adjusting models. This is an underlying structural problem in AI that keeps it prohibitively expensive. Second, we have solved the problem of only being able to connect a fraction of the dots.
For example, a company may wish to see how road quality affects driving speed. Without Motor Ai, they would have to first train an AI model to detect road damage and then build another model to correlate the classified pictures with speed data. That way, they would have a model that solves their initial problem, but they would never notice the hundreds of other variables—like weather—that might affect driving speed. Because our Mobility Intelligence is continuously learning and is trained to spot things it has not seen before, we would be able to connect weather data to road quality and speed and present a more nuanced picture to the company. Mobility is a complex field, and we think that the more nuanced AI is, the more valuable it will be to decision-makers.
Germany has an established automotive sector that is dominated by multinationals. What role do startups play in innovating the automotive industry?
A defining characteristic of the German automotive market is that it is dominated by brands that have until now led the global automotive industry. In recent times, however, German car manufacturers are under considerable pressure from China, whose own automobile industry is growing dramatically. So currently, the automotive industry is very receptive to working with companies that are highly competitive in the development of new technologies. For a long time now, startups have transitioned from being supporting players to constituting the foundation for technological innovation in the automotive industry.
Who are the people that make up Motor Ai?
First off, what unites Motor Ai as a team is the belief in an idea that at first we thought would not be possible. It is this attitude that we want to take with us into the future: to keep pushing the boundaries of the possible. This is the energy that gives our team its power.
Motor Ai was co-founded by Roy Uhlmann and Adam Bahlke.
Roy Uhlmann has over ten years of experience in AI and providing solutions to large companies. Over the course of the last decade, he has come to the conclusion that AI can only ever be as smart as its creators. And since no human can know everything, this will always limit the technology.
Adam Bahlke came to the mobility world obliquely. Deeply interested in urban development and New Urbanism, he had long been aware of trends in mobility. Prior to Motor Ai, he has worked in the education and financial technology sectors, gathering skills on how to build complex, future-proofed products quickly.
Nadine Brunner is the newest member of our team and supports us with her PR and communications skills. She has over ten years of expertise in B2B and consumer PR and has advised clients in the software, telecommunications, and healthcare sectors. In the last decade, she has developed several strategic and content PR campaigns for brands and companies. She believes in the power of the perfect blend between pointedly curated content and close media relationships.
Upon meeting, they discovered their complementary skills and shared interests, which led to the idea of building a self-learning intelligence that can find logical associations between data. This would allow human and machine to play to their strengths: machines to connect the data, humans to study the results to look for practical, business uses.
What prompted your interest in joining the AtomLeap High-Tech Accelerator?
Berlin’s flourishing startup scene, with its many accelerators and incubators is the perfect home for an innovative startup like Motor Ai. Within it, AtomLeap is an ideal partner for us because it will be helping us to further develop our hardware, on on the one hand, and contribute its significant business expertise and competence on the other.
What are your goals for the next six months?
To bring Motor Ai to market!
Do you feel inspired by Motor Ai and want to learn more about them? Then go ahead and explore their website and follow Roy, Adam, and Nadine on social media. As always, if you need help accelerating your high-tech startup, feel free get in touch with the AtomLeap High-Tech Accelerator using the contact form on our homepage.
This program is financed by the European Social Fund (ESF), as well as the State of Berlin.