Silexica, which optimises how disparate applications work together on autonomous cars, raises $18M

As we inch closer to building increasingly autonomous cars, the complexities that these vehicles will present as programmable hardware are increasing, with some 250 applications ranging from cameras to navigation controls to weather sensors running on a typical high performance system today. Now, a startup that is building a system to help optimise that and let all of those vendors work together in a neutral way is announcing some funding to continue its growth. Silexica, a startup based out of Cologne, Germany, that has developed a set of tools to help map and optimise a wide range of applications across multicore processors — specifically the kinds of applications and computers that power self-driving cars — has raised $18 million.

The Series B is led by EQT Ventures, the newish firm that sits under the PE firm EQT Partners, based out of Stockholm. Existing investors Merus Capital, Paua Ventures, Seed Fonds Aachen (Silexica originally spun out of the University of Aachen) and DSA Invest all also participated in this round. The company has raised $28 million to date.

The funding, Silexica’s CEO Maximilian Odendahl (who co-founded the team with Johannes Emigholz and Weihua Sheng) told TechCrunch, will be used not just to increase its optimisation features — allowing for an increasing variety of services and functionalities to be monitored and diagnosed — but also to add a cloud component to how it monitors and processes information on a vehicle.

“Currently we are an on-prem solution, but we are building cloud platform,” he said. The company is also working on a simulator, so that multiple partners can work together on one platform to test their services and how they perform together. Its customers today include Denso, Toyota, Fujitsu and Huawei — underscoring the range of potential buyers of its tech.

The simulator points to one of the key reasons why companies like Silexica are emerging and attracting interest from the autonomous car industry. In large part, these systems are being built using components and technology from dozens or more vendors on top of the car company itself. But data, as people like to say, is the new oil, so what a vendor gathers from its specific sensors and services becomes valuable training information for better services. This means many of them are very guarded about what they share with others, and why, in turn, it is valuable to have an independent platform where that data mixes and is “seen” by no one else.

The other area where Silexica’s SLX tools are notable is that they work in real time to provide their diagnostics. Today, we’ve already seen some dreadful accidents involving autonomous vehicles not behaving in the way that we would have expected, resulting in fatalities. Inevitably, there will be more times that these systems don’t work the way that we think they will, and so any service that can improve how applications communicate and respond to each other will be increasingly essential — and in some cases fundamental — both to make the systems work better, and to make sure not just that vendor trust is in place, but that user trust is, too.

“In their quest to solve one of the largest challenges of the post-PC era, we believe Maximilian, Johannes and the rest of the team can steer Silexica into becoming one of the most important technology companies of this decade,” said Ted Persson, Design Partner and investment advisor to EQT Ventures who will be joining Silexica‘s Board.

There will be other approaches taken to solving this problem, too. Given that we are still at a relatively nascent stage of the race for self-driving vehicles –Odendahl estimates that fully-autonomous might not in use until 2025, and that is possibly optimistic — it will be interesting to see how this aspect of the stack plays out.

Updated with correction to date for autonomous car rollouts, which should have said 2025, not 20-25 years.