Exponential Technologies (xT), a German-Latvian startup and winner of the Formnext Startup Challenge 2019, has attracted a pre-seed investment from Berlin-based VC fund APX to expand its presence in the German industrial sector.
“Being a global industrial powerhouse, my home country Germany was always one of our major focus markets. Now, the investment by APX further strengthens this connection. We are looking forward to many upcoming projects with the German chemical and material industrialists,” explained Matthias Kaiser, Co-Founder & CEO of xT, and a Frankfurt native. “Germany is in the midst of a massive digital transformation, and xT wants to establish itself as a major driver of this shift towards the next generation of industrial technologies.”
APX is a very-early-stage startup investor. Based in Berlin and backed by Axel Springer and Porsche, APX supports and partners with the most ambitious pre-seed startups from Europe and beyond – often as their first investor. Since 2018, APX has invested in 80+ startups across 20+ industries with founders from 20+ countries together with 100+ co-investors.
“We are particularly excited about the investment as APX is well connected to the Porsche Group, which will further strengthen our business development efforts in the materials and manufacturing markets. It is especially important because our newest software version has applications in R&D as well as in the management of production anomalies. We see here a huge market potential for the automotive but also other manufacturing industries,” explained Matthias.
Exponential Technologies Ltd. (xT) was founded in 2019 by the 3 Co-founders Pavel Cacivkin, Matthias Kaiser and Girts Smelters to address these challenges.
Currently, the most commonly used approach to find new chemical formulations and processing parameters is the use of classical Design of Experiments (DoE) software often in combination with statisticians, data scientists or DoE experts. DoE software is complicated and requires expert knowledge in statistics. This means, if a company is big enough to hire expensive DoE experts, researchers have to book slots with the limited number of available DoE specialists which leads to bottlenecks in the R&D process of many industrial companies. Most SMEs won’t even be able to effort DoE experts, which forces them to use less efficient research methods like one-factor-at-a-time (OFAT) or grid optimization.
xT SAAM automates this process by combining classical DoE methods with novel AI algorithms. This allows domain experts and laboratory personnel to run experiments without the need of DoE experts in a fast and efficient manner. Data scientists and DoE experts can then concentrate on high-level data analysis using our integrated data science toolset. Compared to other techniques xT SAAM finds satisfactory results with fewer samples required, which additionally reduces R&D time and cost.
With their partner Evonik Industries, xT could show strong results in the field of chemical formulation. Projects in the field of production anomaly management, biotech and additive manufacturing all have led to astonishing results.