Full-stack AI leadership: from strategy to a running platform.

Built, rolled out, adopted by the team. I find where AI creates measurable business value, then deliver the complete system: data model, pipelines, agents, application. Compliant. In daily use, not in slide decks.

CV as PDF

Chapter 1

The Bridge

I don't just understand AI, I understand the business behind it. I translate business requirements into AI use cases whose impact can be proven with data instead of merely claimed.

Business leadership

At Consulteer I built a business unit from scratch, then led two business areas with P&L and 40+ people; before that, C-level B2B IT sales. I know the questions a leadership team asks before it approves an AI initiative.

AI strategy & governance

Use-case portfolios prioritised, build-vs-buy decided, guardrails and cost envelopes set: for leadership teams, a board, and investors. AI initiatives rarely fail on the technology. They fail on the missing decision about what not to build.

AI builder

And then I build it myself: since 2023 as founder of MySCALES for SMEs and large enterprises, as VP Growth in regulated fintech, and with a production AI platform for M&A due diligence.

I speak boardroom and developer – and translate AI hype into systems that pay off.

Chapter 2

Systems I built – the proof

Everything in production. None of this is a pilot.

From data room to finished DD report – in hours instead of months.

Document AIM&AIn production

majiq.ch ↗

Understand AI. Implement AI. – AI systems for SMEs and large enterprises.

ConsultingImplementationCompliance

myscales.ch ↗

Voice AI call agentsOnboarding, qualification & cold calls on the phone

Content & creative engineCampaign in – UGC videos, images, carousels out

Process automationCore processes automated end-to-end – almost every department

Support agentResolves up to 90% of requests on its own – around the clock

Contract review assistantReviews contracts against playbooks and flags risks

AI workshops & enablementTeams coached until AI became daily practice

Voice AI call agentsOnboarding, qualification & cold calls on the phone

Content & creative engineCampaign in – UGC videos, images, carousels out

Process automationCore processes automated end-to-end – almost every department

Support agentResolves up to 90% of requests on its own – around the clock

Contract review assistantReviews contracts against playbooks and flags risks

AI workshops & enablementTeams coached until AI became daily practice

Agentic AI & MCP serversAgents with direct access to internal systems

Claude Cowork rollout60 employees, all departments – governance, training, adoption

Document AI & RAGClassification, extraction, vector search – in production

KYB automationRegistries, sanctions, UBO – documented and auditable

Self-learning email campaignsSubject, timing, and content optimize with every send

Self-service websitesWebsites the team updates itself via an AI agent

Agentic AI & MCP serversAgents with direct access to internal systems

Claude Cowork rollout60 employees, all departments – governance, training, adoption

Document AI & RAGClassification, extraction, vector search – in production

KYB automationRegistries, sanctions, UBO – documented and auditable

Self-learning email campaignsSubject, timing, and content optimize with every send

Self-service websitesWebsites the team updates itself via an AI agent

Chapter 3

Leadership & how I work

Use cases over tools

For every use case I look for the best AI solution, never in a silo, but scalable enough to serve other areas tomorrow.

Understand, then build

I am not a pure planner. I understand the business and deliver quickly, so the company sees first-hand what AI does when it is used properly.

Data first

Before touching AI, I get the data and the infrastructure in shape. That is the difference between a demo effect and a solution that holds.

Compliance built in

GDPR, Swiss FADP and the EU AI Act from day one instead of repaired afterwards. In the Swiss market that is the difference between a pilot and production.

Cross-functional, not siloed

I look at every part of the company and build solutions that work together. No AI islands.

Business first

AI projects start where they measurably pay off, not with the model. The business case comes before the technology.

Cost transparency first, then efficiency

Most companies don't know what their AI spend is actually for, so they cannot show an ROI. I make usage and cost visible per use case, then build the agents to run at a fraction of that cost.

"Delegate the thinking, never the understanding."

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Contact

Let's talk

The fastest way to find out if it's a fit: a short conversation.

+41 79 609 39 98 LinkedIn CV as PDF

Neuhausen am Rheinfall, Schaffhausen (Switzerland)

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