Case studies · From the build

Real builds, plainly explained.

Data platforms, business intelligence, CRM rollouts and right-sized AI adoption — written up the way I'd want to read them: the problem, the approach, what shipped, and what it actually changed. No vendor gloss, no vanity metrics.

Case study 001 Agentic AI · Shadow AI AI adoption

Before you write an AI policy, ask the people already using it.

The workforce is already using AI on personal and business accounts. Rather than a policy written in the dark, we ran an anonymous workforce survey — and handed the build to an AI agent that designed and configured it through a browser in about fifteen minutes.

~150
Shadow AI users
~15 min
Agent build time
12
Survey questions
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Case study 002 Data platform · Integration Multi-site · 1,400–1,800 sites

Before you overlay AI, build the single source of truth.

A group of 1,400–1,800 sites taking till and app sales, running on disconnected systems and load-bearing spreadsheets — joined up into one governed warehouse (finance, CRM, sales and more), so AI finally had trustworthy data to stand on.

1,400+
Sites/stores
£180–300m
Revenue
~£2–3m
To one source
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Case study 003 Agentic AI · Virtual agents AI adoption

Bolster the team — hire a semi-autonomous agent.

"Charles" — named after Charles Babbage — is my first virtual hire: he runs my Jira backlog, drafts meeting notes and books meetings. When the email and Teams connectors turned out read-only, a Power Automate, OneNote and SharePoint bridge did the sending. No engineers required.

001
First agent
Jira
Backlog owned
No-code
Send bridge
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Happy to talk through any of this in more detail, or answer a question about the work — drop me a line at [email protected].

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