Turning complex technology into operational reality.

I build and scale AI and technology in environments where legacy systems, regulation and organizational complexity make execution difficult.

AI · Technology · Execution — Founder and operator. Munich.

01

The hard part is rarely the technology.

Most organizations already have more technology, data and ideas than they can effectively use. The real challenge is deciding what matters, creating the structures to execute it, and making new technology work within the constraints of an existing organization.

My background spans deep tech, industrial transformation, defence and banking — from building ventures from zero to establishing AI capabilities inside large organizations.

It is technology that works under real operational conditions — not innovation for its own sake.

02

From ambiguity to execution.

AI & Technology Strategy. Identify where technology creates real advantage — and where it does not. I translate broad ambitions into a short list of priorities and executable plans.

Build & Delivery. Move from strategy into delivery. I build teams, define how the work gets done, and take selected initiatives from concept into production.

High-Constraint Environments. Make technology work where the environment leaves little room for error — industrial restructuring, defence, regulated banking. Where legacy systems, regulation and hard operational constraints are the norm, not the exception.

03

Evidence over promises.

Different environments and constraints.

HSBC London (GB)

Banking: regulated cutovers in hours.

Context
Tier-1 banking. Partial S/4HANA cutovers usually mean weeks of systems-integrator work across legacy data, approvals, and change windows.
Execution
Built autonomous agents that compose and check migration logic end-to-end. Live in production. Cutovers in hours, not weeks, with no external consultants in the loop. Eliminating hundreds of consultant hours.
EMCO Hallein (AT)

Machine Tools: reliable answers from legacy data.

Context
€200M machine-tool manufacturer. Decades of maintenance records and machine telemetry were trapped in formats neither technicians nor downstream systems could reliably use.
Execution
Built different AI functions from zero. Converted fragmented machine data into a searchable knowledge base for service teams and engineers.
Rheinmetall Düsseldorf (DE)

Defense: resilient communication under constraint.

Context
European defense. Highly-available, resilient data communication under classified-grade constraints and non-negotiable integrity requirements.
Execution
Led joint research initiatives with TU München and ETH Zürich. Translated operational, availability and integrity requirements into engineering specifications the teams could build against.
YC Mountain View (US)

Deep-Tech: patented emotion-recognition IP.

Context
Co-founded Going Ninja, a deep-tech company built around patented emotion-recognition technology. From patent to global market standard.
Execution
Y Combinator S18 alum. Raised $60M in venture capital. Exit and integration to Volkswagen delivered without losing the product core.

04

How I work.

Find the constraint. Technology, process, data, organization, incentives, regulation — or simply solving the wrong problem.

Prioritize. Decide what deserves resources. Not every technically interesting problem is worth solving.

Structure. Create the conditions for the work. Define ownership, responsibilities and what done really means.

Build. Move into implementation. Work with the people who own the systems, not alongside them in a separate layer.

Measure. Prove what changed. Time, cost, revenue, capacity — against what the objective actually was.

05

Founder by background. Operator by practice.

I am a Munich-based founder and operator in technology. My career started in engineering and entrepreneurship. Over the following decade, I moved from building technology companies into larger organizational environments — industrial manufacturers, financial institutions and defence.

That combination shapes how I work today: with the curiosity of a founder, but with respect for the constraints of organizations that already have customers, systems, regulation and real operational complexity.

I have built ventures, led AI programs in large organizations, established an AI function during industrial restructuring, and worked on technology in confidential and regulated settings.

06

Working on something difficult?

I am interested in situations where technology matters, the operating environment is complex and the path from idea to execution is not obvious.

Felix Rascher

Munich, Germany

Mailfelix.rascher@pm.me

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