AI Appliances
Local AI. Test safely before investing.
A pre-configured local AI environment, without cloud dependency, with your data, under your control. Low barrier to entry, guided onboarding, a clear recommendation.
I write and think about why well-reasoned decisions in organisations often lose their effect — and what AI changes about that. And what it doesn't.
Perspectives, observations and knowledge from practice.
It is rarely the lack of data or skill that makes AI lose its effect in organisations. It is unresolved goal conflicts and unspoken assumptions. Without a clear picture of the destination, you end up tool-hopping. Four observations on that:
Countless tools, models, concepts. Which of them actually makes a difference in a specific context? That question needs answering first — and is usually skipped.
Cloud services, sensitive data, compliance: that slows things down. Not because it is unsolvable, but because hardly anyone shows how it works locally and safely.
Technology only takes effect when the underlying decision logic is cleanly connected. The right framing comes before the right model. Always.
Before scaling, you need a safe space to experiment and learn. Skip that step, and what scales fastest are your own blind spots.
What it takes for AI to deliver impact in organisations — beyond tool selection and pilot projects. Understand, focus, translate.
To the topic →Local AI in practice: possibilities, limits and use cases for organisations that want to try AI without cloud dependency.
To the topic →Distilled statements on impact, clarity and context, drawn from more than three decades of technology and transformation work.
To the theses →Texts on AI, local LLMs, RAG systems and digital transformation. Published when something is genuinely relevant.
To the knowledge hub →Many talk about AI. Some test it. But between first experiments and real impact lies a transformation task. That is where I work with you: from understanding to integration into day-to-day operations.
Reduce complexity, place terminology, assess opportunities and limits realistically.
Identify the relevant application fields, set priorities, define the first transformation paths.
Gather experience with local AI appliances and clear pilots, without losing control over your data or direction.
Align leadership, teams and communication so that AI initiatives translate into real impact.
A pre-configured local AI environment, without cloud dependency, with your data, under your control. Low barrier to entry, guided onboarding, a clear recommendation.
The statements that shape how I think about AI, business and impact.
Impact is the actual measure. Not the number of tools deployed or experiments started.
Clarity creates orientation. Without it, even good technology generates more confusion than value.
Technology creates value only in context: when strategy, organisation and communication work together.
I am interested in why well-reasoned decisions in organisations lose their effect. The cause is rarely a lack of data or competence, but unresolved goal conflicts and unspoken assumptions. I make implicit assumptions explicit and reduce complexity to manageable options for action.
Effectiveness, to me, means enabling sound decisions today while creating the structures that will carry those decisions tomorrow too.