AI consultancy
Readiness audits, workshops and a plan you can act on, from a team that builds the thing afterwards rather than handing you a slide deck.
Book an AI readiness auditAdvice from people who have to live with it afterwards tends to be more honest.
Plenty of firms will tell you what AI could do. Fewer will still be there when it has to work on a Monday morning. We audit what you actually run, score the use cases on value against effort, and tell you which ones are not worth doing. If the answer is that you should not build anything yet, that is what the report says.
A short, structured look at your workflows, website, enquiries, content, data and tools.
A working session with your team to map processes, find bottlenecks and score use cases.
Value against effort against risk, so the order of work is decided on evidence.
What staff may use, what data must never go near a model, and who signs off.
What to build first, what it takes and what it should return.
If implementation is the right next step, the same people carry it out.
Who it is for
Tick anything that sounds familiar.
How the audit runs
A few hours of your team’s time, and a written plan at the end of it.
We look at your workflows, website, enquiry handling, content, data and the tools you already pay for, and note where AI could help and where it plainly could not.
A working session with the people who do the job. They know where the time goes better than any audit does, and the best use cases usually come out of that room.
Every candidate scored on value, effort and risk, so the order of work is decided on evidence rather than on whichever idea had the loudest advocate.
What to build first, what it takes, what it should return, and what to leave alone for now. If implementation is the right next step we can carry it out, and if it is not, the report says so.
You get the approach, what is in, what is out, a timeline and a price before anything starts. No hourly rate quietly running in the background.
How much of it is bespoke, how many systems it has to talk to, and how much content needs moving across. We will tell you which of those is driving the cost.
A monthly plan covering updates, backups and small changes, priced separately so you can see exactly what the ongoing commitment is.
Start with the free audit
A short online version you can run yourself, before committing to anything.
Answer a handful of questions about how your business runs and get a scored read on where AI could help, what would need to change first, and which of it is worth doing at all. It takes a few minutes and there is nothing to install.
Take the auditAs someone that is not tech savvy they are a pleasure to work with and I never feel awkward about asking any questions if I don't personally understand something, which is a big deal to me. No matter what we have as an idea, we know they will have the best ways to do it to hand and always give us realistic timelines and expectations.
Common questions
What people ask before booking one.
What is AI consultancy?
Working out where AI would actually create value for a business, what risk needs managing, and what should be built first. For us it is a practical exercise rather than a strategic one: we audit what you run, score the options and hand over a plan somebody can act on.
Do we need an AI readiness audit before building?
Usually yes. A short audit costs a fraction of a build and regularly stops one happening, either because the process needs fixing first or because the tool would not have earned its keep. That is a good outcome, not a wasted one.
What is the difference between AI consultancy and AI implementation?
Consultancy defines the opportunity, the risk, the scope and the order of work. Implementation is building the chatbot, automation or integration that puts the plan into production. We do both, but you are not obliged to use us for the second.
Can you help if our team is already using ChatGPT or Copilot?
Yes, and most teams are, whether or not anyone has agreed to it. An audit identifies where that use is helping, where it is creating data or accuracy risk, and what a sensible policy looks like.
What do we actually get at the end?
A written report: what we looked at, the use cases scored on value against effort against risk, what to do first, what it should cost and what it should return. Plain English, not a slide deck full of diagrams.
Will you tell us not to build something?
If that is the honest answer, yes. We have to live with what we recommend, and a project that should not have started is worse for us than a report that says wait.
The rest of our AI work
Where an audit usually leads.