Hugdrif
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Independent enterprise and solution architecture

The strategy is clear
The systems do not follow

Systems do not follow strategy, they follow capability, process and data. I pin those down so decisions about technology and AI still hold up five years later.

Let's talk How I work
What I do

Problems do not arrive sorted by category. An AI programme stalls on undocumented process; a platform decision turns out to be a question about who owns the data.

Enterprise architecture and business processes

Capability maps, architecture layers and BPMN process descriptions: clear, consistent and maintainable.

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Data and information architecture

One unified and agreed picture of the organisation's core information.

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AI and agent readiness

An honest assessment of where you can safely apply AI agents, and what has to be in place first.

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Solution architecture and assurance

The right platform decision, and an independent read on a design or a proposal before it becomes irreversible.

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An ongoing arrangement

Fractional chief architect

Some engagements end in a decision. Others need someone who holds the context between them. A defined monthly commitment, participation in forums where decisions are made, and mentoring for your own people. The intent is to become unnecessary.

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Who this is for
Large enterprises

Transformation, system selection, and processes that need pinning down before the next system is bought.

Government and municipalities

Independent advice that outlives the procurement, capability-based specifications, and architecture the next team can inherit.

Software houses and partners

Product architecture, roadmap and ALM from an architect who has carried all of it himself.

Why the order of work matters

Transformation programmes rarely run aground because the wrong platform was chosen. The root cause is typically that nobody established what the organisation actually does, how it does it and what information it depends on, before the platform was selected. Architecture is then reverse engineered from the implementation, and every decision after that inherits that error.

That was survivable while the only consumers were people, because people compensate; they know the diagram is two years old and they adjust. AI agents do not compensate. They work with the vocabulary they are given and resolve inconsistency by guessing, which can quickly become a problem.

The seemingly optional work of pinning down processes and agreeing what a term means was always load-bearing. AI removed the tolerance for pretending otherwise.

A big decision ahead, or a programme that is not going to plan?

Does any of this sound familiar? An ERP or CRM decision to be made where the analysis so far has come from the bidders. An implementation that is not delivering what was promised. You are about to start something significant and want the foundation right from the beginning. Data in three systems that will not reconcile. A board asking what you are doing about AI.

Our first conversation costs nothing and usually helps clarify the question.

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