3.2

AI Transformation

From AI awareness to something running in production

Most organisations have run the awareness session and stalled. This programme takes teams through to a working, deployed use case — with the evaluation, guardrails and ownership that production actually requires.

Engagement[PROGRAMME / PILOT]
Duration[e.g. 8-12 WEEKS]
Team size[e.g. 8-15]
Output[DEPLOYED USE CASE?]

What makes it different

Ends in production, not a deck

The programme is structured around shipping one real use case. Pilots that end in a presentation rarely lead anywhere.

Guardrails from the start

Evaluation, prompt hygiene, data handling and failure modes are built in rather than retrofitted after an incident.

Honest about fit

Part of the work is identifying where AI is the wrong tool. That judgement saves more than any implementation.

Ownership stays internal

Your team builds it with us. When we leave, the people who understand it are still on your payroll.

What you get

  • Use-case identification and prioritisation
  • Data readiness review
  • Hands-on build sessions with your team
  • Evaluation and guardrail framework
  • One deployed use case
  • Internal handover documentation

How it works

  1. 01
    Opportunity mapping

    We review candidate use cases against value, data readiness and risk.

  2. 02
    Select and scope

    One use case chosen and scoped tightly enough to finish.

  3. 03
    Capability build

    Your team learns the tooling by building the actual thing, not a toy example.

  4. 04
    Harden and evaluate

    Guardrails, evaluation and failure handling added before anything is exposed to users.

  5. 05
    Deploy and hand over

    Shipped to production with documentation and internal ownership agreed.

Who it is for

Organisations past the pilot stage

Turn experiments into something with real users and real oversight.

Engineering leaders

Build internal AI capability instead of buying an opaque black box.

Product teams

Learn what these systems can and cannot be relied on to do.

Common questions

No, but you need engineers who will own the result afterwards. We build with your people rather than delivering to them.
Then that is the finding, and we will say so early. A data readiness review is part of the engagement precisely to avoid building on sand.
Whatever suits the use case and your constraints. We are not tied to a single vendor, and we will explain the trade-offs.
Running in your environment, with evaluation and monitoring in place, used by real users. Not a notebook or a demo.
More for enterprises

Other services in this group

Not sure which engagement fits?

Tell us your team size, current capability and the outcome you need — we will recommend the right programme, even if it is not this one.

Talk to our corporate team