CONSULTANCY
AI Consultancy
For organisations that need a decision, not another pilot.
Independent advice on where artificial intelligence is worth applying, how the system around it should be designed, and who stays accountable once it runs. Nine disciplines, four phases, and an architect who stays involved after go-live.
AI consultancy is independent advice on where artificial intelligence creates measurable value in an organisation, how those systems should be designed, and how they stay governable once they run. W69 AI Consultancy works from Amstelveen as architect and advisor across nine disciplines, from AI Enterprise Architecture to Boardroom Advisory. Every engagement follows the same four phases, Discover, Design, Deploy and Scale, and ends with a system in production rather than a report in a drawer.
McKinsey, fieldwork November 2025: 88 percent of organisations use AI in at least one business function, yet nearly two thirds have not begun scaling it across the enterprise. PwC asked 4,454 CEOs across 95 countries in January 2026: 56 percent had seen neither higher revenue nor lower cost. The gap between those two figures is the work an AI consultancy exists to close.
Why organisations bring in an AI consultancy
Almost nobody calls us because they cannot find an AI tool. They call because the tools are already there, the pilots work in isolation, and nothing adds up to a capability the organisation can rely on.
Pilots that never become production
A pilot proves that a model can do something. Production asks a different set of questions: who owns the output, what happens when the model is wrong, how the system is monitored, and where the data lives. Those questions are architectural, so a pilot that was never designed to answer them cannot be promoted. We design for production from the first week and treat the pilot as the first increment of it.
Regulation that moves faster than the roadmap
The EU AI Act applies in stages, and the transparency obligations under Article 50 take effect on 2 August 2026. Classifying a use case afterwards is expensive, because the obligations that follow from the classification shape the logging, the oversight and the user interface. We classify in the design phase, so the compliance work is a property of the system instead of a project bolted on later.
Architecture decisions that are hard to reverse
Where your knowledge lives, which model runs which task, how systems are connected and who may call what: these choices are cheap to make and expensive to undo. A supplier has an interest in one answer. An independent architect does not, which is the whole reason the role exists. We write the architecture first and let it decide which products fit.
One architect, five lines of work
Architecture, governance, security, agents and adoption are not separate projects. They are five views of the same system, which is why one architect holds them together.
Nine disciplines, one engagement
An engagement rarely needs all nine at once. It almost always needs more than one, and that is precisely why they sit under a single roof instead of with nine separate suppliers.
AI Enterprise Architecture
The structural design: where knowledge lives, how systems connect, which model serves which task, and how the whole thing survives the next three years of change.
AI Enterprise Architecture →AI Governance & Compliance
Policy, classification and accountability. Who may approve what, which use cases fall under which obligation of the EU AI Act, and how you can evidence it when asked.
AI Governance & Compliance →AI Security & Data Sovereignty
Where your data physically resides, which model may see it, and what leaves your tenant. Designed to the ISO/IEC 27001:2022 management system we are certified against.
AI Security & Data Sovereignty →Agentic Systems Design
Designing AI agents that carry out work rather than answer questions: roles, tool access, permission boundaries, escalation paths and human checkpoints.
Agentic Systems Design →LLM Orchestration & Integration
Model selection and routing. Large models where reasoning is needed, small models where volume and cost dominate, and a single integration layer so you can swap either.
LLM Orchestration & Integration →Process Intelligence & Automation
Finding the processes where automation actually pays: high volume, clear rules, measurable output. And naming the ones where it does not, before anyone builds them.
Process Intelligence & Automation →AI Adoption & Change
A system nobody uses is a cost. We train the teams, build AI literacy in line with the obligations of Article 4 of the EU AI Act, and make the new way of working the easy way.
AI Adoption & Change →AI Readiness & Assessment
The honest starting position: data quality, technical estate, governance maturity and the capacity of your own people. Usually the shortest and most useful phase.
AI Readiness & Assessment →AI Strategy & Boardroom Advisory
Translating AI into board language: investment, risk, liability and sequencing. Including the uncomfortable recommendation to wait, where waiting is the right call.
AI Strategy & Boardroom Advisory →Two of these have a front door of their own. The AI Navigator is a short structured scan that produces a prioritised use case list in minutes, and the Agentic AI Suite is the platform we build on when the outcome is a working set of agents rather than a document.
Discover, Design, Deploy, Scale
The same four phases for every engagement, large or small. Each one has named deliverables, so you can stop after any phase and still own something usable.
Discover, one to two weeks
Stakeholder interviews, a readiness assessment, and an analysis of your processes and data. The output is an AI Readiness Report, a prioritised use case portfolio and a business case per use case. This is also where we tell you which ideas to drop.
Design, two to four weeks
The architecture blueprint, the governance policy, the agent specifications and the integration and data plan. Classification against the EU AI Act happens here, because the obligations shape the design rather than follow it.
Deploy, four to eight weeks
A working system in your own environment: agents configured and tuned, integrations with your existing software in place, users trained, and a measured performance baseline you can hold us to afterwards.
Scale, ongoing
Rollout beyond the first team, a governance dashboard, adoption metrics and continuous optimisation. Models change, integrations break and regulation moves, so this phase has no end date by design.
The timeline assumes your stakeholders are available for the interviews in phase one. In practice that availability, not the technology, is what decides whether a project runs to plan. The full method is described on our approach.
Independent, certified, and still there after go-live
No reseller margin
We do not resell licences and we hold no vendor quota, so the recommendation can be a tool you already own, an open model, or nothing at all. Where a product is the right answer we say so, and you buy it directly.
ISO/IEC 27001:2022
W69 AI Consultancy is certified to ISO/IEC 27001:2022 for the management system covering AI advisory and implementation consultancy, certificate IQ002141S0926WAC. The certification applies to the company and its management system, not to individuals, and is independently verifiable through IAF CertSearch.
A small team on purpose
You work with the people who did the design, not with a delivery layer underneath them. That limits how many engagements run at once, which is a deliberate trade rather than a growth problem.
Documentation is part of the deliverable, in a form your own team can keep working from after the engagement closes. The test we hold ourselves to is simple: if we stopped tomorrow, could your people still run and change the system. Where the answer is no, the engagement is not finished.
What you should know about AI consultancy
It answers three questions in order: where AI is worth applying in your organisation, how the system around it should be designed, and who stays accountable once it runs. In practice that means assessing readiness, writing the architecture and governance, building a working system with your teams, and staying involved while it operates. The advice is independent of any vendor, because the architecture decides which tools fit, not the other way around.
A developer builds what is specified. A consultancy decides what should be specified, and what should not be built at all. Most failed AI projects are not coding failures but scoping failures: the wrong process was automated, the data was never fit for the purpose, or nobody owned the result. We do the scoping and the architecture first, and we build only what survives that test.
Discover takes one to two weeks, Design two to four weeks, and Deploy four to eight weeks, so a working pilot in production is a matter of two to three months rather than a year. Scale runs from there and has no end date, because models change, integrations break and regulation moves. The timeline assumes your stakeholders are available for interviews in the first phase, which is usually the real constraint.
Both, and deliberately in that order. The advice is worthless if nobody can implement it, and the implementation is dangerous if nobody designed it. We write the architecture, build the agents and integrations, connect them to your existing systems through the Model Context Protocol where possible, and hand over documentation your own team can work from. Where you prefer your in-house team or an existing supplier to build, we stay on as architect and reviewer.
Governance is part of the design phase, not a document written afterwards. We classify each use case against the EU AI Act, record the obligations that follow from that classification, and build the logging, human oversight and transparency markers the system needs to evidence them. The transparency obligations under Article 50 apply from 2 August 2026. W69 AI Consultancy is certified to ISO/IEC 27001:2022 for the management system covering AI advisory and implementation consultancy, which is the standard we work to on your data as well.
Start with the scan, not with the quote
The AI Navigator takes a few minutes and gives you a prioritised view of where AI is worth applying in your organisation. It costs nothing and it makes the first conversation a great deal shorter.
Looking for growth, marketing and visibility instead of architecture?
Our sister company W69 AI Growth covers the commercial side of AI: agents for marketing, sales and customer journeys, plus search and answer engine visibility.
Visit W69 AI Growth on w69.nl →