A view of the current work
A review of agreed workflows, systems, data sources and current AI usage.
Let’s talk
A practical starting point for AI
Start with the way your business works. Identify useful AI opportunities, understand what stands in the way, and leave with a prioritised plan.
Discuss an AI auditIndependent advice. Direct access to the people leading the work.
The assessment draws on hands-on AI delivery across insurance, retail and research, including real data and operational constraints.
Delaware / Cape TownThe useful opportunities are often hiding in familiar places: repeated document handling, information people struggle to find, manual handovers, and decisions made without the right context.
An AI audit examines those workflows before recommending a tool. I look at what people do today, the information they depend on, and where a change could make a meaningful difference.
I also look at the conditions for making it work. Is the data available? Who can access it? How would the output be checked? What happens when the system is uncertain or wrong?
The result is a prioritised view of the opportunities, with the likely effort, dependencies and risks made visible. Where value is uncertain, I define what to measure in a focused test instead of inventing a return on investment.
You should finish with a decision you can act on: what to test first, what needs preparation, and what to leave alone for now.
Matt Watson
A clear scope
The details are agreed around your business.
These are the foundations of the engagement.
A review of agreed workflows, systems, data sources and current AI usage.
Candidate interventions assessed against business relevance, feasibility, effort and dependencies.
Practical findings on access, data quality, evaluation, human oversight and operating constraints.
Recommended first tests or interventions, with proposed success measures and implementation considerations.
Have a challenge in mind?
Discuss an AI audit ↗AI tools & integrations
Your existing AI tools are part of the starting point. We look at how your team uses them, where information gets stuck and which connections could make the work easier.




How we get started
We establish fit before proposing an engagement. Scope, fees and responsibilities are agreed before work starts.
Agree which teams, workflows and business questions the audit will cover.
Review the work with the people who do it and inspect the relevant systems and information.
Present the findings, explain the trade-offs and agree a practical next step.
Before we talk
Rather ask than read?
No. This is an operational and technical assessment of AI opportunities and readiness. Security and data risks are considered, but it does not replace a specialist security assessment or legal advice.
No. An audit can establish a starting point. If teams are already experimenting, we can assess the current work and help prioritise what should happen next.
We agree the access and information needed before the audit begins. Initial discussions can use descriptions, anonymised examples or representative samples. Please keep sensitive material out of the enquiry form.
The audit produces findings and recommendations. A focused intervention or bespoke build can follow under an agreed scope, with its own deliverables and fees.
Start a conversation
Tell me about the workflows, teams or recurring problems you would like the audit to examine.

What happens next
A few lines is plenty. No brief or deck needed.
Around 30 minutes with the person who would lead the work.
A proposal, a plan, or a straight answer if we’re not the right fit.