When David and I founded nexwise roughly two years ago, coming from the Technical University of Munich, we thought about which solution genuinely deserves to be built in Europe – and specifically from Munich. Not as an abstract exercise, but as a concrete question: where is there a deep, structural problem that we understand better from here than anyone elsewhere could?
The answer came from looking at the companies around us. Germany, and Europe more broadly, is home to the densest concentration of industrial manufacturing expertise in the world. The Mittelstand – the mid-sized, often family-owned manufacturers that form the backbone of European industry – builds some of the most sophisticated products on the planet. These companies operate globally, across dozens of markets, in multiple languages. And nearly all of them share a constraint that is as fundamental as it is underappreciated.
Nine out of ten workflows depend on product information
Across industrial manufacturing, roughly nine out of ten market-facing workflows require product information as an input. A sales engineer configuring a solution needs to know which product fits. A marketing team launching in a new region needs technical content adapted for that market. A support agent responding to a customer question needs the right specification, in the right language, at the right level of detail.
Product information is, in effect, the operating system of the commercial side of industrial manufacturing.
Complex portfolios, fragmented data
For companies with simple product lines, managing this information is straightforward. Industrial manufacturers are different. Their portfolios can span hundreds of thousands of product variants. Configurable products alone can reach up to 10²⁴ possible combinations. This depth and breadth is not a flaw – it is the core competitive advantage that secures these companies' dominant positions in global markets. But it has to be managed.
And that product knowledge is described across a fragmented landscape of systems and formats: ERP, PIM, PDF catalogues, CAD drawings, configuration tools, Excel sheets.
The result is a domain that is simultaneously critical and chaotic. Product data is scattered across dozens of systems. It is inconsistent between channels. It is often outdated. And the people who truly understand the products are a scarce resource, stretched thin across too many requests.
AI automation stops where products come in
The promise of AI-driven automation across sales, marketing, and support is significant – and the technology is ready. But in practice, AI automation in industrial manufacturing hits a wall. That wall is product data. Models cannot reason reliably over information that is fragmented, inconsistent, or locked in proprietary formats.
This is not a model problem. It is an infrastructure problem.
What we are building
This is why nexwise exists. We build AI-native product data infrastructure for industrial manufacturers. At its core is nexwise – a harmonized product data layer that ingests, reconciles, and structures scattered product knowledge into a single, reliable foundation.
On top of this foundation, we deploy AI agents that serve technical sales, marketing, and customer support teams. The result: manufacturers can scale their product knowledge without scaling their headcount.
We are already deployed with leading industrial manufacturers and have now secured pre-seed financing to build out the team and the platform.
What comes next
We are hiring founding team members – engineers, a founder's associate, and others who want to work on hard, meaningful problems at the boundary of the digital and physical world.
As Moritz Zimmermann, hybris co-founder and partner at 42CAP, puts it:
What convinced us about David and Mathis is that they've already proven value with leading manufacturers before raising significant capital. The team understands that this market rewards deep execution over speed, and they're building accordingly.
We are grateful for the support of our investors: 42CAP, CDTM Venture Fund, Dr. Pascal Wichmann, Mathis Lichtenberger, Matthias Turck, Moritz Philipp Weisbrodt, Manuel Bönisch, OMA Angels (ProGlove), Ines Ključar, Dr. Juergen Steuer, and Willi Tscheschner.
We’re hiring founding team members in engineering and communications. If you want to build at the intersection of AI and industrial manufacturing, have a look at our open roles or reach out directly.
nexwise originates from the Technical University of Munich and is backed by investors including 42CAP, OMA Angels, and a group of experienced founders and operators from the European technology and industrial ecosystem.