AI Consulting & IntegrationNew
AI Consulting & Integration: AI that does a job,
not a demo.
We set up an AI assistant for your business, connected to Microsoft 365, Teams, and the systems you already run, and put it to work on the jobs your team repeats every week, with a person approving anything that reaches a client.
- Microsoft 365 Copilot rollouts
- Custom AI on Azure OpenAI
- Running in our own business
The work AI is actually good at
Not a chatbot in another tab. These are the jobs worth handing over, because they come round every week and the time saved is easy to count.
Write the first draft
Emails, proposals, ticket notes, and job posts started in seconds and finished by a person, in your company's voice.
Summarize the long stuff
Calls, email threads, meetings, and documents turned into the few lines that matter.
Answer from your own files
Questions answered from your policies, contracts, and manuals, with a link back to the source so anyone can check.
Pull data out of documents
Invoices, forms, and PDFs read and entered into your systems, with anything unclear flagged instead of guessed.
Sort what comes in
Incoming email, tickets, and requests sorted and sent to the right person before anyone has to read them.
Help during the call
Calls transcribed as they happen, with the account and its history surfaced, so nobody asks the customer the same thing twice.
Switched on safely, not just switched on
Copilot can see whatever each person can already reach. If permissions across SharePoint, OneDrive, and Teams have drifted, it will surface files people were never meant to find, so the work starts before the licenses do.
- 1
Find the oversharing
We review who can reach what across SharePoint, OneDrive, and Teams, and flag anything open wider than it should be.
- 2
Fix it, then license it
Permissions tightened first, then the right Copilot licenses assigned to the people who will actually use them.
- 3
Switch it on in stages
The people who will get the most from it go first, then the rest of the business, with clear rules on what it can see.
Every call we take writes its own ticket note.
Our phone platform records and transcribes each client call. Azure OpenAI drafts a client-ready note, and the engineer approves it in Teams before it is filed. Nothing reaches a client record without a person agreeing to it.
See how we built itAI with the guardrails on
The part that decides whether an AI project survives a review, and the part most providers skip.
A person approves it
Anything that reaches a client is reviewed by someone on your team first.
A written data policy
What the model can and cannot see, decided and written down before it sees anything.
An audit trail
What was generated, when, and who approved it, kept on record.
Measured in hours
Time returned, counted, so you can tell whether it is paying for itself.
From first conversation to AI at work
No strategy deck. A short path from where your time goes to something that gives it back.
- 01
Free consultation
Tell us where the week goes. We point to the jobs worth handing to AI, and the ones that are not.
- 02
Readiness check
A short list of workflows ranked by effort and return, plus the data fixes that have to come first.
- 03
Built into your tools
AI wired into Microsoft 365, Teams, or the systems you already run, with approvals where they matter.
- 04
Measured
Hours returned, tracked from the start, so you can see whether it is paying for itself.
Other ways we put software to work
Find out what AI could take off your team's plate.
A free, no-obligation consultation. We will look at where the time goes and tell you plainly what AI can do about it, and what it cannot.