Services

AI consulting for startups and SMEs: practical, not hype

Everyone is telling you that you need AI. Some of it is genuinely useful and some of it is an expensive demo. I help you work out which is which, then build the useful parts properly, with your data kept safe and a human in the loop where it matters.

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How I help you use AI sensibly

AI opportunity review

A short, structured look at how your business really runs, to find the handful of places where AI could save real time or money, ranked by effort and payoff.

Automating the boring stuff

Document and email processing, data entry, reporting, summarising calls. Often a well-placed automation beats a grand AI project.

Assistants that know your business

Chatbots and internal assistants that answer from your own documents and policies, for customers or staff, with answers that point back to the source.

AI features inside your product

Search, summarisation, recommendations or agents built into your Laravel or web application, using leading models from providers like Anthropic and OpenAI, chosen for your use case rather than the logo.

Safe, sensible adoption

UK GDPR and data privacy, clear guidelines for staff, human review where it matters and proper testing so you know the output is good enough to rely on.

Cost and vendor control

Choosing the right model for the job, setting usage limits and avoiding lock-in, so the bill doesn’t surprise you in six months.

Worth knowing

I’ll tell you when you don’t need AI

Sometimes the honest answer is “this doesn’t need AI”. Sometimes it’s a spreadsheet and a £20-a-month automation tool. I’d rather save you money than sell you a project.

A simple, low-risk way in

Discover
One or two short workshops to map where time and money go and which opportunities are worth pursuing. You get a ranked shortlist, not a 60-page report.
Prototype
A small, quick proof of concept on your real data, so you can see whether it works before you commit serious budget.
Build and hand over
If it earns its keep, I build it properly: tested, monitored, documented and with sensible guardrails, then hand over or support it.

Ways of working together

Every business is different, so I keep this flexible. I’ll recommend the simplest option that gets you what you need.

Option 01

AI readiness workshop

A fixed-scope session (or two) to find and prioritise opportunities and to set out the risks and costs plainly.

Best when: You want clarity before spending money.

Option 02

Prototype / proof of concept

A focused build to test one idea on real data and measure whether it’s worth taking further.

Best when: You have a specific idea and want evidence.

Option 03

Ongoing AI leadership

AI strategy and delivery as part of a fractional CTO arrangement, so it stays tied to your wider technology plans.

Best when: You want AI woven into the business, not bolted on.

FAQ

AI Consulting: your questions answered.

What can AI actually do for a small business?

The most reliable wins tend to be unglamorous: drafting and triaging emails, pulling data out of documents and forms, summarising calls and meetings, answering common customer or staff questions from your own documents, and turning raw data into readable reports. The right starting point depends on how your business runs, which is what an opportunity review is for.

Is it safe to put our business data into ChatGPT or Claude?

It depends on the product, the plan and the settings. Business and API plans from the major providers generally have stronger privacy commitments than free consumer tools, but you should always check the provider’s terms and be careful with personal or confidential data under UK GDPR. I’ll help you set sensible rules for your team and choose tools that fit your risk appetite.

Do we need to hire data scientists or machine-learning engineers?

Almost certainly not. Most practical business uses of AI today build on existing models through an API, which is a software engineering task rather than a research one. That’s why a senior software engineer is often a better guide than a data scientist.

How accurate is AI? What about “hallucinations”?

AI can produce confident but wrong answers. The solution is design: grounding answers in your own documents, showing sources, keeping a human reviewing anything high-stakes and testing the system against real examples before it goes live. I build those safeguards in from the start.

How long does an AI project take?

A focused prototype can often be built in a few weeks; a production-ready system takes longer depending on integrations, data quality and how much testing it needs. I’ll give you a realistic timeline once I understand the problem.

Will AI replace my staff?

In the projects worth doing, AI usually takes over the repetitive parts of people’s jobs so they can spend more time on the work that needs judgement, relationships and creativity. I’ll always be open about what a system will and won’t do.

Get in touch

Tell me about your project.

No sales script and no pressure. Share a few details and I’ll reply personally, tell you honestly whether I can help and, if I can’t, point you to someone who can.