For thirty years, software was a 90% fit and you bent the business around the other 10%. Agents end that — but only if they have a legible business to run. That layer is what we build.
What a typical ops / finance team stops losing to manual data work once the layer is live — and it's not just the hours. Because everything sits unified and queryable, the agentic layer reasons over the whole business in context. Decisions and outcomes come faster and sharper — instead of someone pulling numbers from a dozen tools, re-keying them, and acting on a stale, error-prone picture.
Every source — finance, ops, sales, the spreadsheets, the rest of your software stack — brought into a unified source of truth. No more data stranded in one tool, out of context with the rest of the business. The numbers are the numbers, everywhere.
Ask the business anything, in plain language, over the spine. Margin, cash, which accounts are slipping — answered in seconds and in full context, by a person or an agent, without waiting for month-end or re-keying data by hand.
The connective tissue between the dashboards. They don't just report — they act: draft the pack, flag the lapse, reconcile, chase the exception. The work, done.
A tool is a feature you switch on. A role is something someone is accountable for. We give every agent we build a named remit, a human owner and a review trail — which is what makes handing it real work safe. It takes on the routine processing, so your team spends its time on the judgement.
One job, a tight scope. Not “an AI that helps” — a role with edges.
It answers to a human owner who is accountable for its output.
It starts gated, every output reviewed, and earns trust the way a hire does — never correcting the same thing twice.
You can reproduce what it does, unaided, in thirty minutes. You never lose understanding of your own business to a black box.
The same work — the difference between a person's afternoon and an agent's seconds.
We built tm for our own company first — a drinks manufacturing business. Four agents now run on the layer, reading the same unified data. Here's what they actually do.
The next decade of companies are hybrid — humans and agents working the same problems, on the same data. They don't run on more tools. They run on a layer that makes the business legible to both.
We built tm inside our own company before we offered it to anyone else. The layer running our operations today — the data model, the agents, the reporting the board sees — was designed and deployed by the two of us, and it has been in production ever since.
Our backgrounds are technology and finance: AI deployment on one side, investment banking on the other. We have each built and run companies, carried a P&L, and been accountable for systems that had to work on Monday morning. We do the engineering ourselves, and we are named on every engagement.
We work to fixed scope and fixed price, take read-only access wherever the data allows, and build so that we can be removed without you losing anything. We deliver AI-native software for organisations across the UK, in the private and public sectors.
We take on a handful of projects at a time.