AI Services
AI consulting services that actually work.
We help your team put AI to work safely and usefully, model-agnostic across Microsoft 365 Copilot, ChatGPT, and Claude. Strategy, adoption, governance, and automation from a senior team that has done the Microsoft 365 groundwork too.
What we do
AI is our lead practice, model-agnostic across Microsoft 365 Copilot, ChatGPT, and Claude. Pick any one to go deeper.
- 01AI assistant adoptionRoll out Copilot, ChatGPT, or Claude with licensing, training, and guardrails that turn AI into daily time saved.
- 02AI governance and securityPolicies and data protection so any AI tool never sees what it should not.
- 03AI automation and agentsCustom agents and workflow automation on Power Platform, OpenAI, and Claude.
- 04AI strategy and data readinessFind where AI pays off first, pick the right model, and get your data ready.
Vendor-neutral
Copilot is great inside Microsoft 365. ChatGPT and Claude shine for other tasks. We help you choose per use case instead of betting the company on a single tool, and we keep it all governed.
Microsoft 365 Copilot / ChatGPT / Claude / Azure OpenAI / Power Platform
Where AI actually pays off
Every organisation wants AI somewhere. These are the four spots where, in our experience, the hours come back quickly enough that nobody has to argue about the licence cost at renewal.
- 01
Documents that get read more than they get written
Contracts, policies, reports, bids, RFP responses. Anywhere your people spend their day finding the relevant paragraph in something long, an assistant grounded in your own files gives back real time. This is also the use case that most exposes a weak permission model, which is why we look at the tenant before we look at the tool.
CopilotRetrievalSummarisation - 02
The same email, written three hundred times
Client updates, status notes, first drafts of proposals, meeting recaps. Not glamorous, but it is where the minutes hide. We help teams build prompt patterns that produce something on brand and close to final, rather than a generic draft everyone rewrites anyway.
DraftingPrompt patternsEnablement - 03
Handoffs between systems that never got integrated
A form arrives, someone reads it, retypes it somewhere else, and emails a person to say it is done. Those chains are ideal automation candidates, and an agent handles the judgment steps a rigid workflow could never cover. We build these on Power Platform, Azure OpenAI, or Claude depending on where the data already lives.
AgentsPower PlatformAutomation - 04
Questions your team asks each other constantly
What is the current policy, which template is the approved one, who signed off on this, what did we quote them last time. An assistant pointed at properly organised internal knowledge answers those without interrupting the one person who knows. Getting the knowledge organised is usually the bulk of the work.
KnowledgeSearchGovernance
How an AI engagement runs
We do not start with a tool selection. We start with what is expensive about your week.
- 1
Readiness before rollout
We look at your data, your permission model, and your licensing, and tell you what would happen if you switched an assistant on tomorrow. Sometimes the answer is that you are ready. Often there is a fortnight of cleanup that saves months of trouble later.
- 2
Pick the use cases, not the vendor
We shortlist two or three workflows where the payoff is measurable and the risk is low, then choose the model that fits each one. Copilot for work inside Microsoft 365, ChatGPT or Claude where the task is better served elsewhere.
- 3
Pilot with a real group
A small cross section of the business uses it for several weeks against agreed measures. We document what worked, kill what did not, and build the prompt patterns and guardrails that the wider rollout will depend on.
- 4
Roll out, then keep it honest
Training that is about your work rather than the product, a usage policy people can actually follow, and a review cadence so the programme does not quietly become shelfware after quarter one.
We cover the full AI journey, end to end. First, strategy and readiness: where AI pays off first, and what to fix before you spend. Next, adoption: rollout, training, and guardrails that make assistants a daily habit. Then, governance and security, so AI never sees data it should not. Finally, AI integration services and automation — agents that clear the busywork from your team's week. Because enterprise AI adoption fails without a clean foundation, we also get your Microsoft 365 tenant structured and governed along the way. In short, one senior team owns the outcome from first call to steady state. That is why our AI consulting services deliver where DIY rollouts stall.
No, and buying them first is the most common expensive mistake. A readiness review costs a fraction of a year of licences and tells you whether an assistant would return useful answers on day one or surface files people were never meant to see. If the tenant needs work, we would rather you spend on the cleanup and buy licences afterwards.
Tell us where you are with AI and Microsoft 365, and we will share the clearest path forward.