Everyone is trying tools
ChatGPT, Copilot, plugins, templates. Useful in pockets, messy as a business system.
We make AI useful for real businesses.
With all the noise, news, and tools around AI, we help you understand what matters, where it fits in your business, and how to implement it properly.
Client work and experience
A note from Levi
Cornwall-based. Working UK-wide and remote.
Dear business owner,
Your team is probably already using AI. The real question is whether the business is actually changing.
Leads still need chasing. Reports still need stitching together. Support replies still need checking. Useful knowledge is still buried in docs, emails, and people’s heads.
That gap is where Quilliam AI fits.
We help UK businesses turn scattered AI use into one useful workflow at a time: find the work worth fixing, build the system around your existing tools, add the controls, and train the team to own it.
You do not get a black-box system that depends on us forever.
You get a practical AI workflow your team understands, uses, and improves.
You do not need another AI tool. You need a clearer way to use the ones you already have.
Most teams already have access to powerful AI. The hard part is knowing where it fits and how to turn experiments into useful working habits.
The workflow is still manual
Leads, reports, support, documents, and admin still move by copy-paste and memory.
No one owns the rules
People are unsure when AI is safe, when it needs approval, and who checks the output.
The value is vague
AI sounds important, but the first project has not been tied to time saved or work improved.
What we do
We show you what AI can do. Then we help you use it.
You get plain-English training, a clear plan, and practical help turning AI into everyday work.
01
Find the work worth fixing
We look at the repeated admin, slow follow-up, customer questions, reporting, and handoffs that already cost time or money.
Output: Plain-English AI map
02
Choose where AI helps
We pick one useful workflow, decide what AI should do, and agree what should be left alone.
Output: Scoped build plan
03
Build it around your tools
We connect the workflow to the tools and data your team already uses, then test it against real examples before rollout.
Output: Working workflow
04
Train your team to use it
We show the people doing the work how to use the tools, check the output, and keep improving the system.
Output: Team training and handoff
Services
Three ways to get AI out of theory.
Start with an opportunity analysis if you are unsure. Start with team training if staff need confidence. Start with implementation if the workflow is obvious.
For owners
AI Opportunity Analysis
We show you where AI can help, where it cannot, and what to do first without wasting money on random tools.
- Your best AI opportunities, ranked
- What to train, build, or leave alone
- Risks, controls, and ownership before work starts
- A clear first move instead of tool shopping
For staff
Team Training
We train your team to use AI properly in day-to-day work, using examples from their actual roles rather than generic prompt tips.
- Hands-on training for real roles
- Prompt, policy, and process playbooks
- Clear rules on what AI can and cannot do
- Confidence using AI without guessing
For owners and operations
AI Implementation
We turn the best opportunities into working workflows, automations, and internal tools your team can own.
- Lead intake, qualification, and follow-up
- Customer support triage and draft replies
- Research, reporting, and briefing workflows
- Admin between email, docs, CRM, and spreadsheets
Case study
Helping VetVision AI turn a strong AI product into a clearer system.
VetVision AI is a University of Nottingham spin-out using camera systems to monitor animal welfare across equine and dairy environments.
Client
University of Nottingham spin-out
They already had the hard part: a serious AI product. Our work was to make it easier to sell, onboard, operate, and improve. That meant clearer positioning and search, but also branded onboarding and operations workflows around farm mapping, camera setup, and internal implementation.
40 -> 95
SEO score moved from roughly 40 to 95
AI product
equine and dairy welfare monitoring made clearer
Live portal
branded onboarding and operations workflows launched
More leads
visitor numbers, visibility, and lead flow have increased
AI product positioning
Made the camera-based animal welfare product easier for equine and dairy buyers to understand and trust.
Branded onboarding workflow
Built a VetVision AI portal that gives customers a clearer journey from first setup through to rollout.
Operations workflow
Mapped the internal process for farms, camera placement, and camera replacement planning.
Internal AI implementation
Supported internal AI use cases and workflow improvements around the way the team operates and delivers.
Use cases
Practical jobs AI can help with now.
Lead enquiry comes in, gets qualified, and a draft reply is ready fast.
Support questions are triaged, matched to policy, and drafted for approval.
Weekly reports pull the right notes, numbers, and commentary into one place.
Internal knowledge is searchable without digging through old docs and messages.
Good fit
Strong AI projects have boring signals.
The best opportunities are repeated, owned, bounded, and painful enough that fixing them matters.
You have repeated work
The same kind of email, decision, report, triage, update, or handoff happens every week.
The work has rules
People use judgement, but there are examples, policies, constraints, or patterns the system can learn.
Someone owns the outcome
A real person can approve, test, improve, and be accountable for the workflow after launch.
The cost is visible
Slow admin, missed follow-ups, inconsistent quality, or overloaded founders are already creating pain.
Founder-led
Built by someone who understands broken operations and shipping software.
Levi Quilliam
Quilliam AI is led by Levi. He started in turnaround and restructuring at Deloitte, then moved into technology through Halter and XGX.AI.
Workflow-first implementationPlain-English training and handoffDirect founder access
FAQ
Straight answers before you book.
What does Quilliam AI actually do?+
We help UK businesses understand where AI is useful, build the workflows or tools that are worth building, and train the team so the work does not depend on one technical person.
Do you only advise, or do you implement?+
Both. Advice without implementation creates more notes. Implementation without clear thinking creates fragile demos. We map the workflow, build the system, add controls, train the team, and hand it over properly.
Do you work with small businesses?+
Yes. Small and growing UK businesses are often a strong fit because repeated admin, owner bottlenecks, and manual follow-up are easy to see and valuable to fix. You do not need an internal AI team before starting.
How quickly can we see something working?+
A focused workflow can usually reach a usable pilot in weeks rather than months. The first build is deliberately narrow: prove the work, test it with real examples, then harden and expand what works.
What should we budget for AI work?+
We quote by scope because useful AI work depends on the workflow, data, systems, risk, and handoff needs. As a guide, training usually starts from £500. Small implementation projects can sit around £2,000-£3,000, medium projects can range from £5,000-£50,000, and larger programmes are usually £50,000+. Every paid engagement is scoped clearly before work starts.
How do you stop AI going wrong?+
We design for supervision. That means limited permissions, scoped access, human approval for risky actions, test examples, logs, fallback paths, and clear owners. The goal is useful help, not reckless automation.
Where are you based?+
Quilliam AI is based in Cornwall and works UK-wide and remote. In-person discovery, workshops, or rollout sessions are available where they genuinely help.
Start simple