Opportunity Assessment
We look at how your teams work today and where the same effort repeats. Each candidate is written up with the value it would release, the risk it carries, and what it would take to build, then ranked against the others.
Services
Decide what AI is actually worth to you
We work with your leadership and your practitioners to find where AI earns its keep, what it would cost to get there, and in what order to do it. The output is a decision you can defend, not a pilot that goes nowhere.
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What advisory covers
The hard part is not the technology. It is knowing which of forty possible projects is the one to fund.
Most AEC companies we meet have already tried something. A chatbot nobody uses, a tool a supplier demonstrated, a pilot that never left one department. What is missing is a view of the whole business: where the money and the hours actually go, which of those problems AI can move, and what the first working system has to look like. That is what we are there to produce.
Architecture and Sourcing
What to buy off the shelf, what to build, and what to leave alone. We take a position on models, hosting, data access and integration, so the first project does not lock you out of the second one.
Regulation and Governance
The EU AI Act, GDPR, and the client agreements that govern your project data. We establish what applies to your use cases and what has to be in place before a system touches real work.
* Scope and duration depend on the size of the organisation, how many workflows are in question, and how much of the groundwork your team has already done.
How an advisory engagement runs
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Orientation
We spend time with the people who do the work, not only with the people who commission it. Project managers, engineers, estimators, the back office. We want to know where the hours go, which questions get answered over and over, and which handovers cost you rework. In parallel we review the systems you already run, because what is realistic depends heavily on what your data looks like and where it sits.
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Assessment and Prioritisation
Every candidate use case gets written down the same way: who or what it serves, the task it performs, the data it needs, and the constraints it works under. We then rank the list by business value, implementation effort, and risk, and put a business case behind the top entries. This is the part most companies skip, and it is why their pilots stall.
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Decisions and Roadmap
We come back with a position, not a menu. Which use case goes first and why, what the architecture behind it should be, which parts you should buy and which you should own, what the regulatory work is, and a sequence for the twelve months after that. Where it helps, we build a working prototype so the decision is made against something real rather than a slide.
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Support Through Delivery
Advice that ends at the recommendation is easy to give and hard to act on. We stay available while the first project is delivered, whether your own team builds it, a supplier does, or we do. Plans meet reality quickly, and someone has to make the call when they do.
Client experience
"We came in with a vague idea that AI could help us somewhere. We left with five concrete use cases and an agent that was already answering technical questions from our project documentation."
Project Engineer
Advice from people who also build the systems.
We are not a strategy house that hands over a deck and leaves. We build AI and software for construction companies for a living, which means our recommendations carry an implementation cost we have actually paid. When we say a use case is harder than it looks, it is because we have built that one before.
- Grounded in your workflows, your data, and your client agreements
- Every recommendation priced against what it takes to build and to run
- You own the assessment, the roadmap, and the freedom to deliver it without us
Not sure where AI belongs in your business?
Tell us how your teams work today and which processes cost you the most. We will come back with an honest read on what is worth doing and what is not.
