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Most of the enterprise work in AI is not about AI.

Your Practical AIPractical AI is AI applied to real problems inside real organisations. Machine learning, computer vision, language models. Embedded into live systems to automate work, sharpen decisions, and deliver measurable value. The art is in the building. team, as a service. Chief Technology Officers, Chief Data Officers, Heads of Engineering, and Heads of Product and Design who embed inside your organisation and ship software end to end. From business processes to data to the code that builds the systems that run them.

Fixed monthly pricing. Unlimited projects. One project at a time.

The pattern is familiar. A pilot is commissioned. A proof‑of‑concept impresses the steering committee. Then it is quietly shelved, because nobody solved how it would run inside real risk controls, pass a compliance audit, or be owned by an operations team on a Monday morning. The technology worked. The business did not change.

This is what we were built to prevent. We embed inside your organisation and ship software that holds up and delivers value. Not decks. Not pilots that last a quarter. Software your people use, on your stack, inside your regulatory perimeter, from the week we arrive.

We work end to end because each of us has run one of the disciplines involved: business architecture, data engineering, machine learning, working software. On our team those are not separate conversations. They are one.

We are opinionated about process. Governance is part of the design from day one, not something bolted on at the end. We have built inside PRA‑regulated insurers, FCA‑regulated firms, and a UK government department with national‑security concerns. We know what auditors ask before they ask it. We choose AI that can be explained to a board, not technology from a paper published last month. When we say shipped, we mean it runs inside your infrastructure, monitored, documented, and ready for your team to own.

AI is a new capability, but shipping software inside a regulated institution is an old craft. What separates a useful AI project from an expensive one is not the AI. It is whether the team building it knows how to work inside a financial institution.

That craft is what you are buying when you bring us in.

Our team has built inside

  • Allianz
  • SEFE
  • Lancashire
  • Montagu
  • Foreign, Commonwealth & Development Office
  • SITA
  • Finli

How we work

Practical AI, in three waves.

We work in six‑week cycles. Long enough to build meaningful software end to end. Short enough to feel the pressure of a deadline. That balance is velocity.

  1. Shape

    We sit with leadership and stakeholders across risk, compliance, operations, product, and engineering to find the AI work worth doing. Not the flashiest idea. The one that moves a number, survives the regulatory review, and can actually ship.

  2. Build

    We build against your data, inside your environment. Not a notebook on someone’s laptop. Real software with audit trails, controls, and observability from the first commit. It meets PRA and FCA regulatory controls because we built it that way from the beginning.

  3. Ship

    We put it in your hands. We work with your team to own what we built together, and we document everything so the knowledge stays after we leave. A good engagement ends cleanly. A bad one becomes a dependency.

Paul Howarth

Paul Howarth, CEO and Founder

If this is the team you want inside your organisation, there are fifteen minutes on the calendar.

Let’s build AI together