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Microsoft Partner

AI Transformation

Most AI pilots never reach production. We run the programme that gets them there — readiness assessment, then delivery on Azure AI and Microsoft 365 Copilot, with the evaluation, governance and adoption work an enterprise rollout actually needs.

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What it is

The Short Version

The counterpart to AI & Software Engineering, and the second of our two partner-delivered services. There, we place AI engineers inside your team and you direct the work. Here, we are accountable for the outcome against an agreed scope: assessing where AI is genuinely worth applying, prioritising the cases that pay back, and delivering them on the Microsoft stack we are already a partner for — Azure AI, Microsoft 365 Copilot and Copilot Studio — including the evaluation and adoption work that decides whether anyone ends up using what was built.

Who it is for

Organisations that have run an AI pilot, or been asked for an AI strategy, and now need someone accountable for turning that into production systems people actually use.

  • A proof of concept impressed everyone and then stalled before production
  • You have been asked for an AI roadmap and want one grounded in what pays back
  • You are paying for Microsoft 365 Copilot and want it adopted, not just licensed
  • Governance and data residency have to be answered before anything can ship

Capabilities

What That Covers In Practice

AI readiness assessment

Where your data, platform and processes actually stand, and which use cases are viable — established before anyone builds anything.

Use-case discovery and prioritisation

Candidate use cases ranked by payback and feasibility, so the roadmap opens with the ones that survive contact with production.

Azure AI delivery

Building on Azure AI Foundry and Azure OpenAI inside your own tenant, with the identity and networking posture your security team will ask about.

Microsoft 365 Copilot and Copilot Studio

Rollout and custom agents, including the permissions groundwork — Copilot surfaces whatever a user can already reach, so access hygiene is part of the work rather than a follow-up.

Evaluation and guardrails

Measuring output quality before and after release, so that it seems better is replaced by something you can put in front of a board.

Governance, residency and adoption

Usage policy, regional data residency, and the change management that decides whether a rollout is used or quietly abandoned.

Questions

Things Clients Ask First

  • That one places AI engineers inside your team and you direct the work. This one is delivered against an agreed scope with us accountable for the outcome. Plenty of clients run them in sequence: we deliver the first use case, then embed engineers to take it forward.

Let us talk

Stuck Between Pilot And Production?

Tell us what you have built and what is blocking it. If the answer is that you do not need a transformation programme, we will tell you that too.