AI · Implementation · 2026

AI that produces results.

I help companies move from curiosity about AI to systems that hold up in production, with the experience of someone who builds with these tools every day.

What it is

There are two relationships with AI in this studio, and they don't contradict each other. When I build websites, AI is a tool of mine — quiet, in service of curation. Here it's the opposite: AI is the work itself that you ask me for, implemented in your product or taught to your team. One is the AI I use to do my work; the other is the AI I build for you. This page is about the second.

01 — Where I come in

From strategy to production.

01

AI strategy and roadmap

Where AI genuinely solves a problem of yours — and where it's an expensive distraction. You leave with a prioritized roadmap, not a list of trends.

In practice

  • Audit of real opportunities
  • Prioritization by impact and effort
  • Roadmap by quarter
  • Cost and risk estimate

02

AI workflow automation

Processes that eat hours today — triage, replies, classification, drafting — start running assisted, with a person in control where it matters.

In practice

  • Triage and routing
  • Assisted drafts and replies
  • Classification and extraction
  • Human oversight where critical

03

AI features in your product

Semantic search, assistants, generation, recommendation — built inside your product, with evaluation, guardrails, and cost under control.

In practice

  • In-product search and assistants
  • Evaluation and quality testing
  • Guardrails and limits
  • Per-usage cost control

04

Team enablement and training

Your team learns to use these tools with judgment — what they do well, where they fail, how to trust them without trusting too much.

In practice

  • Hands-on sessions by role
  • Internal playbooks and prompts
  • Criteria for when (not) to use
  • Post-training follow-up

02 — How I work

How a project usually goes.

01

Diagnosis

I see how you work today and where AI has real return.

02

Roadmap

I prioritize by impact and risk — what to do first, what to leave.

03

Pilot

We build one small, measurable case before widening it.

04

Scale and handover

What works moves to production and into your team's hands.

03 — Representative work

Only what I can prove.

I don't show AI numbers I can't prove. On a call I'll tell you plainly what's realistic for your case and what isn't.

Book a discovery call

04 — Frequently asked

The right questions.

From0From €7500 per engagement

How we scope

A floor, not a ceiling.

Each discipline has a floor — the honest minimum for a serious project. From there, the proposal is scoped to yours: the floor is clear, the ceiling is set with you.

  1. The conversation first

    A free discovery call. I learn your context, goals and timeline before we talk numbers. If it isn't a fit, I say so — and point you to someone who'll do it better.

  2. Then the scope

    I turn the conversation into a written proposal: what's in, what's out, the timeline, the instalments. A scope you recognise as yours, not an off-the-shelf pack.

  3. One figure, no fine print

    The proposal carries a fixed price for that scope. No meter running, no surprises on the invoice. What you sign is what you pay.

Start with 30 minutes, no obligation.

Book a discovery call

Next step

Let's find where AI actually serves you.

A free discovery call. You bring the context; I leave with an honest read and a bespoke proposal.