We’re a small business. Is this for us?

The same questions apply at any size: which tools staff may use, what data can go into them and who checks. For a small team the answer might be a short policy and one well set-up platform, not a programme.

Do you write the AI policy?

We write the technical parts: platforms, access, data controls and the risk assessment. The rest, such as HR and legal wording, belongs with the people who own those areas.

Won’t this slow AI down?

It should do the opposite. Once platforms and controls are in place, each new use case has a clear route to approval instead of starting the argument again.

Usually with a look at what is in use today and a written recommendation. That sets the scope of anything that follows, so you know what you are committing to.

Systems we build

Consultancy · AI + automation

AI governance and adoption

Approved tools, real controls and teams who use them well.

People are already using AI at work, approved or not. We help organisations choose platforms they can trust, put technical controls around them and get teams using them well, so saying yes to AI doesn’t mean taking on risk nobody can see.

Start a project Talk it through first

Who it’s for.

Organisations where staff use AI without clear rules
Leaders who need to approve AI with the risks in view
Teams that handle personal or sensitive data

What it has to get right.

Platforms chosen on evidence: Each candidate compared on security, data residency, cost and fit, with a recommended platform for each purpose.
Secured before anyone signs in: Single sign-on, role-based access, audit logging and no training on your data, signed off by whoever owns information security.
Controls on personal data: Personal data redacted or blocked before it reaches a model, usage logged and access tiered by role.
A route from idea to approval: A risk assessment every use case goes through, a register of what AI is used for, and the technical sections of a usage policy.
People who know how to use it: Hands-on sessions where teams build their own use cases, worked examples they can copy, and a shared prompt library for the approved platforms.
New tools brought in carefully: Specialist tools such as AI notetaking reviewed for data flows and security, with a measure of success agreed before any pilot.

Work that shows it.

What we built, how it runs and where each piece stands.

In-house work: our founder leads AI engineering at a multi-site UK organisation, which isn’t named here.

Questions.

We’re a small business. Is this for us?: The same questions apply at any size: which tools staff may use, what data can go into them and who checks. For a small team the answer might be a short policy and one well set-up platform, not a programme.
Do you write the AI policy?: We write the technical parts: platforms, access, data controls and the risk assessment. The rest, such as HR and legal wording, belongs with the people who own those areas.
Won’t this slow AI down?: It should do the opposite. Once platforms and controls are in place, each new use case has a clear route to approval instead of starting the argument again.
Where does it start?: Usually with a look at what is in use today and a written recommendation. That sets the scope of anything that follows, so you know what you are committing to.

Planning something like this?

Tell us what you’re trying to build or fix. A few sentences is plenty; we’ll ask about the rest.

What happens next

1We read your message and reply by email.
2We talk it through on a short call.
3If we’re a good fit, you get a written plan.

AI governance and adoption

Who it’s for.

What it has to get right.

Work that shows it.

AI guard rails: Governance that every use of AI runs through

AI adoption: Hands-on sessions, worked examples and a self-serve toolkit

Specialist AI tools: Bringing in AI notetaking and image analysis safely

Questions.

Planning something like this?

What happens next

AI governance and adoption

Who it’s for.

What it has to get right.

Work that shows it.

AI guard rails: Governance that every use of AI runs through

AI adoption: Hands-on sessions, worked examples and a self-serve toolkit

Specialist AI tools: Bringing in AI notetaking and image analysis safely

Questions.

Planning something like this?

What happens next