Founder-led AI consultancy for UK businesses
Make AI earn its place in your business.
We find the workflow where AI can save time, protect margin or sharpen decisions. Then we build the working system and help your team make it stick. Blueprint. Build. Embed.
Built for founder- and MD-led UK businesses, typically between £3m and £30m turnover.
Two minutes, no sign-up, and the result is on screen before we ask you for anything.
The problem is rarely the technology. It's knowing where to start.
Five things we hear, in some form, in almost every first conversation.
“We don't have the expertise in-house — and hiring it is brutal.”
The most common reason businesses hold back — and the obvious fix is the slow one. A “Head of AI” search runs for months, the title means something different at every company, and the few people who've genuinely run AI inside a business are gone before most ads close.
“We wouldn't know where to start.”
In one survey of 1,000 UK small-business leaders, 41% said they want to adopt AI but don’t know where to start. Not “AI is useless” — just no obvious, sensible first step.
“We tried a pilot and it went nowhere.”
Most pilots never reach production — the widely-cited studies put failure rates for AI projects above 80%, roughly double the rate for ordinary IT projects. A failed attempt can cost an SME £20,000–£80,000 in direct spend alone, before the internal time.
“Our people are worried it's here to replace them.”
Adoption stalls on fear, not technology. When researchers trace these failures back, the cause is overwhelmingly organisational maturity rather than the models — and the failure rate for the least-prepared organisations is higher still.
“We can't tell the real thing from the hype.”
Every product now claims AI. Without someone independent in the room, it's hard to know which claims survive contact with your business.
If any of that sounds familiar, you're who we work for.
Sources: Indeed survey of 1,000 UK small-business leaders (41% want to adopt AI but don't know where to start); BT Business, The AI Opportunity for Small Business (60% cite lack of understanding); RAND, The Root Causes of Failure for Artificial Intelligence Projects (RR-A2680-1, 2024); Melbourne Business School Centre for Business Analytics, Why do analytics and AI projects fail? (2024). Implementation cost ranges are typical UK SME figures from 2026 industry reporting.
Find where it pays. Build it. Land it with your people.
Blueprint · two weeks
Find where AI actually pays.
We map your workflows, separate the genuine opportunities from the noise, and hand you the operating plan — including what not to automate.
Build · about six weeks
Get the working system, not a deck.
Agents, approval queues, dashboards and integrations — with governance built in: the autonomy your team grants, spend caps, audit trails, human escalation.
Embed · ongoing
Land it with your people.
Training, cadence and the culture change that makes the system stick — so it survives after we leave.
The Woodlark Academy
AI, explained without the theatre.
Practical learning for teams who want to understand what AI can help with, where the risks sit, and how to use it responsibly.
Book a conversation ↗- UnderstandPlain-language guidance on where AI can add value — and where it cannot.
- DecidePractical ways to choose useful use cases before buying or building anything.
- AdoptSimple governance and team habits that turn experimentation into confident use.
Real business problems. Useful systems.
Anonymised client engagements. The names and sensitive details are withheld; the operational substance is not.
Fulfilment · 3PL
Sales visibility
Capacity-aware forecasting for a leading UK logistics business.
Read the engagement ↗
Creative agency
Daily profitability
Job-level P&L for a creative agency.
Read the engagement ↗
Financial services
Governed company brain
Shared, accountable knowledge for a finance business.
Read the engagement ↗
We don't advise on this from a distance. We build with it every day.
The numbers below aren't projections. The first two are a client's, from their own management accounts; the rest are counted from the systems we built and run inside our own business.
six months against the previous six
and hand it over
around the clock
every agent, every day
part-time, alongside the day job
Client figures: a leading UK logistics business, from its own management accounts, comparing six months of trading with the previous six. Approved for publication; the company is not named. The remaining figures are our own, counted from systems we run.
The autonomy–stakes matrix.
How do you hand real work to AI without losing control? In our own company, every agent sits somewhere on this board: three tiers of autonomy, against three levels of stakes. Clean approvals move it up. One bad call moves it straight back down.
- Approve — the right call. One approval closer to the next tier.
- Edit — close, not quite. Your correction is fed back into the agent; its tier holds.
- Reject — you say why, in a line. The agent learns from it — and drops straight back down.
Every move on the board is reversible. When you correct a draft, that correction is written into the rules the agent works to next time, so the same mistake gets caught once rather than every week. Ours have earned the top row: last night, while we slept, they answered support in 13 languages, reconciled the day's numbers and drafted this morning's content.
Book a conversation.
Thirty minutes with the founders. We'll tell you where AI would pay in your business — and where it wouldn't. Plain answers, no pitch.