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Services

AI Enablement for Teams

Assess, rebuild, hand over. The capability stays with your team.

Most AI programmes fail in the same place. Not at tool selection and not at enthusiasm. They fail because nobody agreed what good looks like before the licences were bought, and because the processes the tools were meant to accelerate had never been written down.

An agent will execute an undocumented process quite happily. It improvises one, at speed, and the output looks exactly like what you wanted, so nobody notices for six weeks.

This work runs in the order that prevents that. Leadership sets the measures, the team rebuilds real flows around agents in their own environment, and then the support is withdrawn on a schedule agreed at the start.

When this is the right call

Your team is using AI and you cannot tell if it is working

Tools are in place, some people are enthusiastic, and there is no measure that would tell you whether any of it has moved the organisation.

You want the capability in-house, not on retainer

You are willing to be taught, and you are not willing to depend on an outside party for how your own organisation operates.

Your processes live in people's heads

Nothing is documented well enough to automate safely, and the mapping exercise keeps being deferred because it is nobody's job.

How the engagement runs

  1. 1

    Assess before programming

    Mapping comes first, always. Real processes, with the people who run them, using a fixed set of questions that surface handovers, single points of knowledge and undocumented judgement calls.

  2. 2

    Set measures with leadership

    KPIs and OKRs agreed with the leadership team before any tooling decision. What has to move in six months for this to have been worth doing.

  3. 3

    Rebuild on live work

    The team rebuilds an actual process around agents, in their own stack, with someone experienced in the room the first time it goes wrong. Not a sandbox and not a toy dataset.

  4. 4

    Fade the support

    Handover documented, and the support withdrawn on a schedule agreed at the outset rather than whenever it happens to tail off. Independence is the measured outcome.

What’s included

  • Process mapping and AI readiness assessment
  • KPI and OKR definition with leadership
  • Agentic workflow design for development and operations
  • Hands-on implementation with the delivery or operations team
  • Data sovereignty, self-hosting and governance guidance
  • Documented handover and scheduled withdrawal of support

How engagements work

Day rate

£1,500–£2,000 per day

Engagements are usually scoped as a fixed-length programme with a defined end rather than open-ended days.

Availability

Flexible

Flexible, agreed per engagement and confirmed on a first-come basis once a start date is set.

Location

Remote-first

Remote-first. Face-to-face across the UK and EU is possible by arrangement.

Who this is not for

This does not work if leadership will not commit to a measure they can be held to. Without that, the implementation phase has no destination.

It does not work if the people who actually do the work are not in the room. Operational knowledge sits with them, and a process map built without them describes how the work is supposed to happen rather than how it does.

It does not work if what you want is someone to run this for you indefinitely. That is a legitimate thing to want. It is a different service.

And I will not take an engagement that involves building a direct competitor to SportERP. Everything else is open.

Common questions

Do you build the agents for us?

Only where it is needed to demonstrate the pattern. The point of the engagement is that your team can build and maintain them afterwards.

We have no engineers. Is this still relevant?

Yes. A large part of this work is operational rather than technical, and federations and governing bodies are a regular part of it. Coach licensing, competition administration and reporting are typical starting processes.

What if we have no documented processes?

That is common and it is handled inside the work. Mapping is the first phase for exactly this reason.

What happens to the knowledge when someone leaves?

Mapping pulls judgement and criteria out of individual heads and into something the organisation holds. That is worth doing even if you never automate a single step, and it is usually the first benefit clients notice.

Does our data have to leave our infrastructure?

No. Self-hosted and locally run options are a normal part of this work, particularly where athlete data, minor data or safeguarding records are involved.

Does the framework depend on your software?

No. It is stack-agnostic and works on whatever you already have. Where the right answer is not one of my products, I will say so.

How is this different from a training day?

A workshop ends when everyone goes home. This ends when the framework is running in your stack on your real work, with your team maintaining it.

Not sure where you stand? Take the technology readiness audit

10 questions, about five minutes, and your score is on screen before you are asked for anything.

Start the audit

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Discuss an AI enablement engagement

Tell me the situation and the timing, and I will tell you honestly whether this is the right fit.

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