Your first AI agent in production in 30 days. Fixed scope, fixed price.
Level 2 · AI Transformation

Change how the company runs, not just how one workflow runs.

The first agent proves one workflow. Transformation is the next thing: your strategy with AI built into it, the operating model redesigned around people and agents, and a way of working that keeps compounding.

What we mean by AI transformation.

Changing how a company executes its important work, so that AI shows up in business results rather than in individual productivity.

That means more than one workflow and more than one agent. It means the strategy is rewritten with AI in it, the operating model is redesigned around what people and agents each do well, ownership and approvals are explicit across the company, and measurement becomes a habit rather than an afterthought.

None of that is a technology project. It is a change to how the business is run, and the technology is what makes it executable.

The 30-day sprint proves one workflow works. Transformation changes how the company works.

We start from your strategy, and put AI inside it.

We do not write you an AI strategy. Companies that have one usually have a document that sits beside the real strategy and never touches it.

We take the strategy you already have and work through it with you: what does AI now make possible that was not possible when this was written, where would it move the metrics you are already measured on, and what does that change about the choices in the plan.

What comes out is one strategy with AI built into it, and a ranked view of where AI earns its place first, second and third.

  • Your existing direction and objectives, brought in as the starting point
  • What AI now makes possible against each of them
  • Where it would move a metric the business already tracks
  • The gaps in strategy, operating model, data, people and governance that would stop it
  • A priority order, by business value rather than by enthusiasm

How the platform structures this →

Then the operating model changes.

This is the part most AI programmes skip, and it is the reason most of them produce activity instead of results. If the work is redesigned but the org chart, the approvals and the incentives stay exactly as they were, the old workflow quietly reasserts itself within a quarter.

So the transformation is explicit about who does what now.

  • Every task in a workflow sorted into people-only, people-with-agent, or agent-only
  • A named owner for each redesigned workflow, accountable for its metric
  • Approval points, escalation thresholds and suspension rules, agreed before anything runs
  • Management practice adjusted to run work that people and agents share
  • Measurement built into the workflow rather than reported on afterwards

The six links in detail → Where a person stays in the loop →

Questions about AI transformation.

How we differ, what it costs as it grows, and what you keep.

Do we need an AI strategy before we start?

No, and we would rather you did not write one. A separate AI strategy tends to end up as a document sitting next to the real strategy, agreeing with nobody and changing nothing.

We take the company strategy you already have and put AI inside it. We work through what AI now makes possible that was not possible when the plan was written, where it would move a metric you are already measured on, and what that changes about the choices in the plan.

You end up with one strategy that has AI in it, and a ranked list of where AI earns its place first. Not two documents to reconcile.

How are you different from strategy consultants and AI agent developers?

Strategy consultants set the direction, then hand you a document. AI developers build the technology, then hand you a tool. Everything in between is the work that decides whether any of it pays, and that is the layer we work in.

It is one chain: a priority worth moving, the workflow redesigned, who does what and who approves, the agent inside guardrails, monitoring you can see, and a metric that moved. Transformation is that chain, run again and again, across the workflows that matter.

Strategy consultants

Set the direction, then hand you a document.

  1. A priority worth moving

  2. The workflow, redesigned

  3. Who does what, who approves

  4. The agent, inside guardrails

  5. Monitoring you can see

  6. A metric that moved

AI developers

Build the technology, then hand you a tool.

How is this different from the 30-day sprint?

The sprint proves one workflow. It is deliberately narrow, fixed price, fixed scope, and it exists so you can find out whether this works without committing to anything.

Transformation is the level above: the strategy rewritten with AI in it, several workflows redesigned, the operating model changed to match, and agents that compound instead of piling up. It is a different size of decision and it should be taken after you have seen a result, not before.

How is AI transformation different from AI automation?

Automation makes an existing step faster. Transformation changes the workflow that produces the business outcome, changes who is responsible for it, and then measures it.

A fast tool inside an unchanged workflow just accelerates one fragment. That is why the workflow gets redesigned before the agent is treated as the answer.

Does this get cheaper as we add agents?

Yes, and it is the whole economic argument for doing it this way. The first agent is expensive because you are not really buying an agent. You are paying to work out the priority, redesign the workflow, decide who owns what, agree the approvals and establish the baseline. That work is the hard part, and it does not have to be done twice.

The second agent inherits all of it. The strategy is already structured, the operating model already says how people and agents divide work, the governance pattern is already agreed, and the platform compiles the new agent’s harness from the same context. So the second one is faster and cheaper, and the tenth is cheaper still.

Disconnected automations do the opposite. Each one is built from scratch, by someone else, in a different way, and the tenth costs more than the first because now somebody has to maintain nine others.

What do we keep if we stop?

We are not leaving in the first place. Our people get lighter over time and the engagement does not end. It keeps running with or without us in the room, and that is the difference between a project and an operating model.

If you do stop, the work stays yours. The agents keep running in your environment. The redesigned operating model is how the company works now, with ownership, workflows, agent behaviour, controls and measurement explicit enough that the work does not depend on the people who set it up.

The platform is the part tied to continuing. It holds the strategy, the gaps, the priorities, the actions and the agent configuration in one place, so the next person to pick this up does not restart from a blank page.

Does this require replacing our existing systems?

No. There is no rip-and-replace and no six-month IT programme.

The agents run in your environment, on your credentials, with access to only what each workflow needs. What changes is how the work is organised, not what software you own.

How long does a transformation take?

Longer than 30 days, and it is honest to say we cannot put one number on it. It depends on how many workflows are in scope, how clear the strategy already is, and how quickly the company can actually change how it works.

What we can do is make it visible: the platform puts the transformation work on a timeline with owners and estimates, so you are looking at a sequence rather than an open-ended programme. Transformation and Scale runs monthly from €3,000, and you can stop.

Who has to be involved from our side?

Someone senior enough to change how work is done, and the people who own the processes in scope.

This is the part that decides whether a transformation lands. If the only sponsor is IT, the operating model will not change and the old workflow comes back. We would rather say that at the start than discover it in month four.

Find where AI can create measurable value first.

Next day you get a one-page map of where an agent pays first, the metric we'd aim to move, and a fixed price and date.

45 minutes. You keep the map either way.

No preparation required. No commitment.

It's the first step into the 5% that really transform. The gap between the 5% and everyone else widens every month.