What we do
Our Services
We work across several focus areas: IT strategy, infrastructure, AI implementation, and product engineering. Depending on where you are, these interconnect or stand independently.
Most companies have an IT strategy. Few have one that matches reality. Over the years, a gap opens between what was once decided and what is actually running today. Decisions that were never implemented. Systems no one keeps in the target picture. Investments that have drifted away from the actual purpose of the business.
You walk us through your business strategy, and we capture the current state of IT as it is actually lived. We lay the two over each other and make the assumptions and trade-offs that fit your growth scenario. The result is a robust target picture: an architecture for the next three to five years, a roadmap with a clear order, and technology decisions that stand up to the business case.
For us, IT strategy is not a document for the drawer. It is the frame everything else fits into: what we find in the analysis and what gets built in the implementation both follow from this target picture.
The outcome
- A target picture for your IT over the next three to five years.
- Where IT should be, in a target architecture that fits your specific business.
- A roadmap with a clear order.
- What gets tackled in which order, prioritised by impact and dependency.
- Technology decisions with a business case.
- Make-or-buy and architectural direction, each weighed against the value it actually adds.
- An operating model that answers the questions ahead.
- Who decides, who operates, who is accountable, so the target picture does not fail at the first conflict over responsibility.
How a strategy engagement works
An engagement begins by taking stock of the existing strategy and IT as it is actually lived. Comparing the two produces the target picture, which we sharpen together with leadership and IT management. At the end there is a roadmap both sides stand behind. Not a document that disappears into a drawer.
Every infrastructure carries history. Workflows set up by someone who left years ago. Tools everyone routes around without quite knowing why. Decisions that still shape the architecture and were never revisited.
Knowing these structures is the prerequisite for building anything meaningful on top. An AI initiative built on a crumbling foundation does not fail because of the AI. It fails because of what it stands on.
We systematically analyse what is actually running: which processes exist, who uses them, which dependencies are undocumented. The result is an honest inventory and a prioritised plan. Not a generic audit.
The outcome
- A system map of your actual infrastructure.
- The current state: which processes exist, who uses them, which dependencies are undocumented.
- A ghost register.
- The concrete legacy baggage blocking your progress. Named, classified, each with a clear recommendation: keep, replace, or retire.
- A prioritised action plan.
- What has to be solved first for an AI or automation initiative to succeed. Sorted by impact, not by effort.
- A findings workshop with your technical team.
- We present the findings directly. A conversation where questions are answered on the spot, plus documentation to read afterwards.
How an analysis works
A typical engagement spans two to six weeks of structured discovery, followed by a findings workshop with your technical team. We present findings directly. No multi-round review process before you see results.
There is no shortage of proof-of-concepts. The difficult step is the one into the production system: stable integration into the enterprise architecture, an adequate quality bar, and operation under real conditions.
We take on the role of external product owner. That means technical decisions made with your requirements in view, not technology trends. AI implementation comes after the groundwork. In that order, for a reason.
Results you can measure. Short iterations on a two-week cycle with regular deliverables. No long silence followed by one big handover.
The outcome
- A production-ready solution, not a proof-of-concept.
- Stable integration, high quality standards, operation under real conditions.
- A shared definition of success that everything is aligned to.
- What should be measurably better in six months: agreed before the first line of code is written.
- Regular deliverables in short iterations.
- You see where the project stands at every step and can always take the wheel.
- The role of external product owner, for a defined period.
- We make technical decisions with your requirements in view. When we leave, the knowledge stays with you, not with us.
How a project works
Projects start with a shared definition of success: what should be measurably better in six months? Architecture and priorities follow from that, not from a predefined service portfolio or software partners.
The bootcamp is for individuals: PMs, POs, founders, and anyone else who has perhaps had their first go at AI-assisted coding and found that the result was not the one they had in mind.
Two days of bootcamp. Every participant works on a real problem they bring with them.
What you take away
- A working tool you built yourself.
- In two days, on a real problem, not a practice exercise.
- The shift from client to product owner, experienced in practice.
- Having done it yourself once changes how you see it.
- An approach you can use again next Monday.
- What worked in the bootcamp works on your own projects too.
How admission works
Participation is by application. We select attendees by their experience and the problem they bring, not by company size or job title.