AI & Automation

The boring wins first.

Most SMEs don't need an AI strategy. They need two or three genuinely repetitive processes taken off their team's hands — and someone honest about which ones are actually worth it.

Where to start

"Can AI save us money?" is the wrong first question.

The right one is: which of your repetitive, rules-based tasks eats the most hours every week? That's where automation pays — not in the demos filling your feed.

  • Repetitive admin that follows fixed rules — invoice handling, onboarding, the same report every Monday.
  • Handoffs that get forgotten, where a form should trigger a task and doesn't.
  • Data your team re-types from one system into another by hand.
  • Large volumes of documents or case data that need summarising before a human decides.
If you can write the rule down in one sentence, it's a candidate for automation. If it starts with "it depends", it still needs a person. Our test for what's worth automating
Being straight about it

What we'll tell you not to do.

We build automation. We also talk clients out of it regularly, because a project that doesn't pay back costs you more than the problem did.

"AI that runs your business"

It doesn't. Current tools assist with narrow, well-defined tasks. Anything sold as a general replacement for how you operate is being oversold.

Automating a broken process

If nobody can describe the process step by step, it isn't ready. You'd be making the mess faster, not smaller.

Replacing judgement

Anything requiring context, nuance or accountability still needs a person. Automation supports the decision; it shouldn't make it.

Starting big

Multi-system builds are where budgets disappear. Start narrow, prove it works, then expand.

How we scope it

Five questions before anyone writes code.

Most failed automation projects were lost in the scoping, not the build. These are the questions we work through with you — and the ones you should ask any supplier.

What does the process look like today?

Step by step, as it actually happens rather than as the manual describes it. If nobody can say, that's the first piece of work.

What does success look like in numbers?

Hours saved, errors reduced, days off a cycle. If there's no number, there's no way to know it worked.

What happens at the exceptions?

Every process has cases that don't fit the rule. How those get handled decides whether people trust the automation.

Who owns it afterwards?

Automation isn't a delivery, it's a thing that now exists in your business and will need maintaining.

Questions

Common questions

How much does AI automation cost?

It depends on scope more than anything else. A single, well-defined automation with clear rules sits at the low end and can pay for itself quickly. Costs climb when the process is messy, spans several systems, or nobody has agreed what it should do. The parts people forget are tool licensing, cleaning up data first, and maintenance after go-live. Any figure quoted before scoping is a guess.

Do we need to be on Microsoft 365?

No, but if you already are, a lot becomes cheaper — we can often build on the platform you're paying for rather than adding another subscription.

Is our data safe?

That depends on the tools and how they're configured, and it's a question worth asking hard. We'll tell you where your data goes before anything is built, and design around keeping it inside your own environment where we can.

What if we don't know what to automate?

That's normal, and it's the most useful part of the first conversation. Write down the five tasks your team does every week that never change — that list is usually the answer.

Is your IT actually working for you?

If nobody in your business owns that question, a half-hour conversation is worth having. No obligation, and no pitch if we're not the right fit.