What we do

We solve the four problems that stop AI from working.

Every engagement is some mix of these four, sized to where you are. Our approach explains how we decide where to start.

The knowledge problem

What your company knows is stuck in people's heads.

Proof: a shared memory an entire client company asks every day, built by us.

Your best people spend their days re-answering questions they've answered before. Documents go out of date the week after they're written. And when someone leaves, what they knew goes with them.

What we do: We build your company one shared, living knowledge base. Sales, product, engineering and leadership can all ask it questions and add what they know, and it stays current, because it's connected to the tools where the work already happens.

  • Capture from the tools you already use: docs, tickets, chat, meetings

  • One place to ask, with answers that cite their source

  • Kept current automatically

The workflow problem

The same job gets done a different way every time.

Proof: 71 AI skills running at that same client, a construction-tech company, from planning a feature to shipping it.

How long a piece of work takes depends on who picks it up. The best way of doing things lives in one person's habits, which is fine, right up until they're on leave.

What we do: We take how your best people work and turn it into simple, repeatable workflows, with the boring parts automated, so the same job comes out right no matter who runs it.

  • Your best ways of working made repeatable

  • Automation that does the work inside your tools

  • The full path from request to done, standardised

The guardrails problem

AI without guardrails is a risk you can't see.

Proof: currently building this layer for a global identity-data company operating in 30+ countries.

Who used AI today? On which customer's data? What did it cost? Most businesses can't answer. And here's the honest part. This problem mostly arrives with AI: if the safe way is slower than pasting into a free chatbot, people take the shortcut.

What we do: We build the guardrails in from day one. Your data stays yours, every action is written down, costs are visible, and the safe way is also the easiest way, so people actually take it.

  • Personal details stripped before they leave

  • A full record of who did what, when

  • Costs visible per team and per workflow

The adoption problem

Most AI tools get tried once, then forgotten.

Proof: three months after launch, every function at the construction-tech client was putting its work through the system.

The demo goes well, a few people try it for a week, and then everyone quietly goes back to how they worked before. The tool wasn't the problem. Nothing changed about how the work gets done.

What we do: We work inside your team's day-to-day until the new way is the normal way, and we teach your own people to run and improve it, so it never depends on us.

  • Training by doing, on live work

  • Your team taught to run and extend the system

  • Nothing that depends on us after we leave

Other engagement types

Two other ways we engage

  • AI product build

    Full product engineering where AI is the core of the product, from idea to live users. Bowerbird, our own product, built end to end and now in pilot with newsrooms, is the proof.

  • A senior AI engineer, by the day

    Day-rate capacity for teams already mid-adoption: reviewing what's being built, unblocking hard problems, pairing with your team.

Start here

Not sure which problem is yours?

A 30-minute call is enough to work out where your business is and what the first useful step would be. No deck, no pitch. Just an engineer looking at your real situation.