Evaluation before generation
We build the scoring set before the system. Without a graded set of real cases there is no honest way to say whether a change made things better, and no safe way for your team to keep changing it after we leave.
About
We build the thing we recommend. Which is the main reason our recommendations are worth something.
Atomiq is an AI consultancy in London working with mid-market and enterprise teams across the UK and Europe. Small, senior, and deliberately constrained in how much we take on at once.
- AI systems shipped to production
- 40+
- sectors, from regulated finance to healthcare
- 6
- of builds run on the client's own infrastructure
- 100%
- typical time from first call to work starting
- 2 weeks
AI systems shipped to production
sectors, from regulated finance to healthcare
of builds run on the client's own infrastructure
typical time from first call to work starting
Why we exist
Three demos and nothing in production. It is the same story often enough that we built a practice around it.
Atomiq exists because of a pattern we kept running into: capable teams, real budget, genuine executive support — and an AI programme that had produced three impressive demos and nothing in production. The blocker was almost never the model. It was that nobody had decided what the system needed to be right about, so nobody could tell whether it was working.
So we built the practice around that gap. Every engagement starts by making the problem measurable, whether that means a graded evaluation set for a build, a sized opportunity map for a strategy piece, or an honest baseline of what a team can currently do with the tools they already have.
We are deliberately small and senior. The people who scope your engagement are the people who build it — there is no layer between the conversation and the work. That constrains how many clients we take on at once, which we think is the right trade.
We work with mid-market and enterprise teams from London, mostly across the UK and Europe, and we are model-agnostic by construction rather than by preference: the evaluation harness is what lets you change providers later on evidence instead of on faith.
How we work
Six things we will not trade away. Each of these costs us something — in margin, in the size of engagement we can take, or in deals we do not win. That is what makes them worth stating.
Fixed scope, fixed price, fixed end date
You get a written scope with a price and a date before anyone commits. No hourly billing, no change-order economics, and no incentive on our side for the work to take longer than it should.
Your infrastructure, your code
Everything runs in your cloud accounts, your repositories and your CI, from the first commit. There is nothing to migrate when an engagement ends because nothing was ever hosted with us.
Built in the open
A weekly demo of the working thing and a shared channel throughout. You see the system as it takes shape rather than at a reveal, which is when problems are still cheap to fix.
We say when the answer is no
A meaningful share of our consulting engagements end with a recommendation not to build. That is a cheaper outcome than finding out six months into a build, and it is why the recommendations we do make are worth something.
Handover is the deliverable
The engagement is not finished when the system works. It is finished when your engineers have the runbook, the documentation and the pairing time to own it — and when we are no longer needed for the second use case.
The firm
How we are set up. The structure is the reason the weekly demo is real rather than aspirational.
Small and senior by design
Engagements are run by the people who scope them. There is no account-management layer and no bench of juniors being learned on at your expense.
Two or three engagements at a time
Capacity is a deliberate constraint rather than a growth problem. It is what makes a weekly demo of real progress possible instead of aspirational.
A specialist network, named up front
For clinical governance, regulated-sector compliance and specific domain modelling we bring in specialists we have worked with before. You are told who they are before they start.
Working together
What a first conversation looks like.
Thirty minutes, no deck. You describe the problem in whatever state it is actually in — including the parts that are political rather than technical, because those usually matter more. We ask about the data, the constraints and who would have to sign off on a change.
You leave with a view on whether it is worth doing, which of the three services fits, and roughly what it would cost. If none of them fits, we say that too, and where we can we point you at someone better suited.
Get started
Let’s find out what AI is actually worth to you.
A 30-minute call, no deck. Bring the workflow that frustrates you most and we will tell you whether it is worth automating.
Typically replies within one business day.