About
About me
I am a Senior Cloud Solution Architect at Microsoft and a hands-on builder. My work sits where AI strategy has to become a real system: agentic applications, evaluation, observability, enterprise integration, and the engineering it takes to move from prototype to production. Before that I spent years across data platforms and machine learning consulting, which is where Relataly started. Outside customer work I build products and open-source projects, from source-linked AI research and ML-driven market tools to Swiss German speech benchmarks and an embodied-agent robotics simulator. Building things myself keeps my architecture advice honest.
- Role
- Senior Cloud Solution Architect at Microsoft
- Based in
- Zurich area, Switzerland
- Education
- PhD, University of Bremen (2018)
Focus
What I work on
- 01
Agentic systems and orchestration
- 02
AI evaluation and observability
- 03
Azure and Microsoft Foundry architecture
- 04
Speech and multimodal AI
- 05
Data platforms and ML engineering
- 06
Workshops, writing, and technical storytelling
Timeline
Background
- Current
Microsoft: applied AI and cloud architecture
Working with customers and teams on Azure, Microsoft Foundry, agentic applications, evaluation, and the path from AI prototype to production.
- Ongoing
Independent products and open source
Building and running public products and open-source projects: AIUseCaseHub, Rankoon, PerpXray, speech benchmarks, coding-agent evaluation, and robotics simulation.
- Since 2021
Public AI and ML publishing
Writing practical articles and notebooks about machine learning, data science, analytics, and generative AI on Relataly, based on topics I explored as a consultant and builder.
- Until 2018
PhD, University of Bremen
A research foundation that still shapes how I think about systems, adoption, innovation, and the gap between ideas and implementation.
Research
Academic background
My research at the University of Bremen explored service innovation, modularity, and collaboration in automotive engineering.
Speaking
Talks I give
- What it takes to move from AI demos to systems people can use
- Agentic systems, orchestration, and where the hard parts start
- Evaluating agents and models with evidence instead of vibes
- MCP and tool ecosystems: making enterprise knowledge usable for agents
- AI governance, sovereignty, and architecture trade-offs
- How data platforms change when AI becomes part of everyday work