The AI Adoption
Method
How we work.
Start with a free Strategy Review. If there is a fit, the paid Audit covers both the work and the people who do it. From there you choose training for your team, the workflows we build for you, or both.
The audit
Before anything is decided, you get a clear view of the work, what it costs you to run by hand, where AI realistically fits, and where each person on your team actually stands with it.
Map how the work really happens
We map your real workflows with the people who run them. Not a generic template, the way your invoicing, reporting and reconciliation actually happen. You see your own work laid out clearly, often for the first time.
Read where each person actually is
We sit with the people in the Audit and see what they already do with AI, what they get wrong and what they are missing. Some of them will be able to build their own once they are taught properly. Others need the work built for them. Knowing which is which is what decides what each person gets.
Quantify and rank the opportunities
We rank your workflows by what they quietly cost you: the hours they eat, the errors they let through, the delays they create. The ranking combines operational value with feasibility, so the recommendation is based on evidence rather than novelty.
Leave with a blueprint and a clear choice
You leave with a blueprint, the Workflows and Projects worth building, a training plan for each person who needs one, and the reasoning behind both. During the Audit we also coach stakeholders live and improve the Claude or OpenAI setup where needed.
What you choose after the Audit
The Audit makes the options visible. Some people are ready to build their own AI once they are trained, and some work is better built for them. You choose training, the build, or both.
AI training
Training built for each person, on the work they actually do, rather than a standard course everyone sits through.
Best forPeople who will use AI every day and need to get properly good at it.
What changesEach person gets their own programme, from what they already know up to what they need. The sessions are one to one on their real work, with a collective part kept for the basics everyone needs.
AI Workflows
Rebuild a repeatable business task around the way your team already works, with a written operating guide and practical handover.
Best forA repetitive task that creates manual effort, rekeying or inconsistent hand-offs.
What changesThe agreed task is rebuilt, tested and handed over in a form your team can run.
AI Projects
Deliver a wider outcome that may combine workflows, data, interfaces and internal tools in one defined project.
Best forA business outcome that needs more than one workflow or a single hand-off.
What changesThe relevant workflows, data and internal tools are brought into one defined scope. A Project can also pull several workflows into one scope when they depend on each other and should move together.
Training and build together
Teach the people who can carry it themselves, build the rest for them, under one plan.
Best forA team where part of the work should be built for them and part of it should be learned.
What changesYour people get better at using AI while the heaviest repetitive work gets rebuilt around them.
Delivery stays in your environment
Delivery runs in the client-owned Claude or OpenAI environment. Access is limited, acceptance is explicit, and measurable changes use a before-and-after basis the client can inspect.
You follow the build, live.
From the day the build starts, you open a register and see where delivery stands. Each piece and its current state, so you never have to ask for an update.
Illustrative example of the register clients follow while we build.
After it goes live
Workflows drift when the business changes. On maintenance, small changes and improvements are covered, and bigger ones are quoted. Without it, nothing is included and keeping the work alive is yours.
Start with the Strategy Review.
The free review looks at your current situation and whether a paid Audit is the right next step.
AI Strategy Review