Munich Startup
Lytra: AI makes mechanical engineering service scalable

Lytra: AI makes mechanical engineering service scalable

Lytra founders Etienne Fieg (l.) and Benedikt S. Vogler (r.)

Lytra founders Etienne Fieg (l.) and Benedikt S. Vogler (r.)

Saskia Doll

Saskia Doll

How can service in mechanical engineering be scaled efficiently when knowledge is locked in people’s heads and systems are highly complex? Munich-based startup Lytra relies on an AI operating system that automates service processes from scattered data, unlocks revenue potential, and provides maximum data security.

January 16, 2026

4 min. read time

Munich Startup: What does your startup do? What problem do you solve?

Etienne Fieg, Co-Founder & CEO: The service business in mechanical engineering has the potential to become a revenue driver, and given the current economic situation, it must. Best-in-class companies generate nearly 50 percent of their revenue from service, which has much higher margins compared to new customer business. However, most mechanical engineering companies in Europe are far from achieving this. But why?

Their service business is hardly scalable because process and product knowledge – which quickly becomes enormous in scope for complex machines – resides in the heads of experienced employees and is only minimally documented. Yet these are precisely the employees who will retire in the coming years. Additionally, this situation makes it difficult to automate service processes because there are no clear rules to feed conventional automation tools with.

We have developed an AI operating system for mechanical engineering service that gives service teams superpowers. Lytra extracts service processes from data sources that weren’t originally designed for this purpose and can use that to automatically execute customized service processes through AI agents. This saves time, reduces costs, and drives higher service revenue.

Standard AI reaches its limits in mechanical engineering

Munich Startup: But this already exists!

Etienne Fieg: Not really, at least not when products become as highly complex as they are in mechanical engineering. While many new AI tools and chatbots work wonderfully for simple service cases, they quickly reach their limits with scattered data, complex products, and highly individualized service processes.

Considering that IT systems used in mechanical engineering don’t necessarily have standardized interfaces, you need a solution that is tailored to the complexity and specific requirements of the industry and integrates seamlessly into existing system environments.

Munich Startup: What’s your founding story?

Etienne Fieg: During my mechanical engineering studies, I repeatedly experienced the various problems arising from implicit expert knowledge firsthand, working at both large players and mid-sized mechanical engineering companies.

This was followed by extensive and intensive expert interviews that ultimately revealed the concrete use case and untapped potential to us. Combined with developments in artificial intelligence in recent years and supported by the EXIST founder grant, Lytra emerged from this.

Data security as the key to AI acceptance

Munich Startup: What have been your biggest challenges so far?

Etienne Fieg: One major challenge is the understandable fear many companies have about what happens to their data. While many companies desire greater efficiency on one hand, they have so much fear of change on the other that decision-making processes often take longer than necessary.

We address this with a special software architecture. Data remains with the company and is stored only there as before. This way, our customers get both: maximum data security and control combined with the benefits of cutting-edge, AI-centric IT systems.

Munich Startup: How is business going?

Etienne Fieg: Extremely well! We have excellent customers we work with in partnership and continuously develop our solution with (and more are joining every month), investor funding that is massively accelerating our growth, and our team keeps getting bigger: By Q2/2026, we want to scale our team to ten FTEs.

Munich Startup: How have you experienced Munich as a startup location so far?

Etienne Fieg: It’s no coincidence that the Munich startup ecosystem and UnternehmerTUM was again named Europe’s leading startup hub by the Financial Times in 2025.

Countless networks, initiatives, incubators, accelerators, and investors call Munich home. This makes it significantly easier for startups, regardless of what stage they’re in. At the same time, the opportunities are so diverse that you can’t lose focus on building an outstanding product that creates real added value for your customers.

Munich Startup: Risk or security?

Etienne Fieg: Both. Calculated entrepreneurial risk when it comes to growing Lytra. And maximum security when it comes to our customers’ data.

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