AI Consultancy Services
for UK Business.

Our AI consultancy services

Five service lines. Most clients start with a discovery assessment, then run training and governance in parallel before the build.

AI development and project-based work

Not every engagement is a retainer. A lot of what we build is scoped, delivered and handed over as a project, with a defined start, a defined finish and your team owning it afterwards.

Process mapping and workflow support

Before anything is automated it has to be described. We map the process as it actually runs rather than as the handbook says it runs, which is usually where the first surprise lives. That map is the deliverable whether or not you go on to build anything, because a process nobody can describe cannot be automated, improved or handed to a new starter either.

Workflow automation and integration

Connecting the tools you already pay for so work stops being re-keyed between them. Most of the recoverable time in a small business sits in the gaps between systems rather than inside any one of them, and closing those gaps rarely requires new software.

AI agents and Claude agents

An AI agent is a system given a goal and a set of tools, which then works out the steps itself rather than following a fixed script. That is really useful for work that varies each time, and really risky for work where a wrong step is expensive. We design agents with the boundary drawn explicitly: what it may do unattended, what needs a human before it proceeds, and what it must never touch. The boundary is the design decision. The rest is configuration.

Prototypes and pilots

A working prototype in front of the people who will use it settles arguments that a specification document will not. We build small, deliberately, and agree beforehand what result would justify going further and what result would mean stopping. If you would rather see one than read about one, the Build Layer is a live worked example → — a single pane of glass over an e-commerce brand's sales, marketing, ERP and stock data, with an agentic decision layer on top, running on composite data in your browser.

Bespoke AI solutions

Custom AI solutions shaped around your processes rather than a product everyone buys off the shelf. For most organisations of 15 to 200 people that means configuring an existing platform rather than commissioning software. The honest version of what bespoke should mean →

The Claude toolchain, and where each part fits

We are a Claude specialist, so it is worth being precise about which product does what. These are different tools for different jobs, and buying the wrong one is a common and avoidable waste.

Claude

The assistant most people mean when they say Claude: a conversational interface for drafting, analysis, summarising and reasoning over documents. This is where most teams start and where most of the day-to-day value sits.

Claude, given a job

In January 2026 Anthropic brought the agentic behaviour of Claude Code to everyday knowledge work. You give Claude access to a folder and describe the task in plain language, and it carries the work out rather than suggesting how you might. It is the difference between asking for advice and delegating the job. We have run our own business on Claude this way since February 2026, which is where our founder case study comes from.

Claude Code

The agentic coding tool, and the foundation that way of working was built on. Relevant to you if you have developers, or if your operations team has grown into scripting and automation without quite calling it that. We train teams on it and use it ourselves.

MCP and connectors

The Model Context Protocol is the open standard for giving an AI assistant access to your own systems and data, rather than only what you paste into a chat window. It is what turns a capable assistant into one that knows about your business. Connecting it correctly is a governance decision as much as a technical one, which is why we scope the data boundary before we scope the integration.

Claude for UK SMEs

Most published guidance on Claude assumes either an individual power user or a large engineering organisation. Very little of it is written for a 40-person business with no internal AI team, a real compliance obligation and no appetite for a twelve-month programme. That gap is the whole of what we do. See how the six layers fit together →