AI consultant and AI consultancy in the Netherlands

An AI consultant helps you decide where AI adds value in your organisation and where it does not, and makes sure the execution holds up. In practice that means: structured discovery of processes and data, prioritising use cases on impact and feasibility, vendor and build-vs-buy advice, an AI Act classification per application, and oversight during implementation. A good AI consultant does not bring a platform, they bring knowledge of what works and what does not. We do this from DataDream as a tool-agnostic party: we work with Claude, GPT, Gemini, open-source models and on-premise stacks depending on what the use case demands. The difference between an AI consultant and an AI specialist sits mainly in scope: the consultant looks at strategy, governance and portfolio, the specialist goes deeper into the technology or a specific model family.

We do not publish a price on the website, because the scope per engagement varies so much that a number on a page creates more confusion than clarity. An AI Quickscan for an SMB with a handful of processes is something very different from a multi-year AI consultancy role at an organisation with hundreds of staff and an AI Act track. We work in defined phases (Quickscan, roadmap, vendor advice, implementation guidance) and agree a fixed price or day-part rate per phase. You can decide after each phase whether to continue, so you are never locked into a large upfront budget. In a free intake call (the free AI Readiness Scan) we can quickly estimate which phase makes sense for you and what a realistic budget looks like.

Classic IT consultancy works with systems that are deterministic: an ERP, a CRM, a data warehouse. Input in, output out, behaviour predictable. AI consultancy works with models that are probabilistic: the same model can answer the same question differently tomorrow, it can hallucinate, and it is sensitive to how you phrase the question. That changes the work fundamentally. An AI consultant must not only understand the technology, but also how to build reliability on top of an unreliable building block: monitoring, evals, fallbacks, human-in-the-loop, audit trails. Classic IT projects you measure on delivery date and functionality; AI projects you measure on success rate and escalation rate over time. That demands a different steering method and a different governance structure.

An AI roadmap is a phased plan that sets out which AI applications you tackle in which order, with per phase the intended value, the required team, the dependencies and the decision points. You need one as soon as you are weighing more than two or three use cases at once, or as soon as multiple departments start with AI independently and the choices begin to diverge. For an SMB with a first pilot an extensive roadmap is overkill; a Quickscan with a list of three to five concrete candidates is enough. For an organisation with multiple business units, a data landscape that needs cleaning up first, or an AI Act portfolio that needs classifying, a roadmap is essential. Our AI roadmap approach is phased without fixed timelines: per phase we prove the value before we move to the next step.

All three, but the approach differs. For startups AI consultancy is often a short sparring role on architecture and model choice: which stack, which vendor, which evals, which pricing strategy. For SMBs the centre of gravity is operational: which two or three processes can be sped up today, which tooling fits, and who keeps it running. For corporates the focus is governance and portfolio: AI Act classification, vendor management, a central AI policy and the relationship between business units and a central AI team. We work not only in Zeeland but nationally too. For regional engagements see our AI agency in Middelburg or AI advisory in Zeeland; we also keep dedicated sector pages for accountants, legal, education, real estate, tourism, marketing agencies and HR.

The AI Act forces organisations to classify each AI system by risk and document the corresponding duties: transparency, logging, human supervision, data quality, and for high-risk applications also conformity assessment. For an AI consultant that means looking not only at what is technically and commercially possible, but also at what is legally permitted and which documentation duty comes with it. We do a short risk classification per use case and link it to a documentation checklist you can actually fill in. For SMB applications most fall into limited or minimal risk with manageable obligations; for HR, credit, biometrics, education or medical advice it can be high-risk and then it gets more serious. The broader context lives on our AI Act page, the self-check tool at AI Act check.

Tool-agnostic. We are not a reseller, not a platform partner and not a vendor affiliate. That is a deliberate choice, because an AI consultant with a commission interest cannot, by definition, advise independently. We work daily with Anthropic Claude, OpenAI, Google Gemini, open-source models (Llama, Mistral, Qwen), vector databases (PGVector, Weaviate, Pinecone), workflow engines (n8n, Make, LangGraph) and on-premise stacks. Per use case we pick what fits, not what we have to sell. If you have already bought a platform (Microsoft Copilot, Salesforce Einstein, a Google or AWS AI stack) we advise how to get the most out of it before proposing anything new. The difference with platform-only consultancies is that we define the use case first and pick the tool second, not the other way round.

With a free one-hour intake call, no obligation. In it we discuss what you do, where the pain sits and which processes are AI candidates. Sometimes after that hour it turns out you are not yet ready for AI or that the upside is smaller than expected; that is then an honest answer and you owe nothing. If we do find something concrete, we propose an AI Quickscan with a defined budget and a fixed deliverable: a shortlist of use cases with the impact estimate, the vendor direction and the risk classification per item. After that you choose whether to continue with an AI roadmap, an implementation, or neither. No annual contract, no retainer obligation, no thick strategy report you cannot use. You can start via the free AI Readiness Scan or the contact form.