AI that actually ships
Most AI projects stall between the demo and the day job. We take you from “we should do something with AI” to working tools your team uses every week — securely, and with your data staying yours.
What's included.
Strategy through to build and run, from one senior team.
AI readiness & strategy
Where AI genuinely saves you time and money — and where it's hype. A prioritised roadmap with costs and effort, not 90 pages of slideware.
Microsoft Copilot rollout
Licensing, data hygiene, security trimming and staff training so Copilot lands well — instead of becoming an expensive unused icon.
Custom AI assistants
Chat and automation built on your own documents and systems using Azure OpenAI — grounded, private, and auditable.
AI governance & safety
Usage policies, data-loss controls and monitoring so your people can use AI confidently without leaking the crown jewels.
From idea to daily habit.
Every AI engagement starts with your data, not the technology. Before a single tool is deployed we map what information you hold, where it lives, and who can see it — because the fastest way to ruin an AI rollout is Copilot cheerfully surfacing the salary spreadsheet to the whole company. Data readiness first, features second.
From there we run a short discovery to find the two or three processes where AI genuinely pays: usually document-heavy work like proposals, contracts, reporting, customer email and meeting follow-up. We prototype against real examples from your business, measure the time saved honestly, and only then scale what works. Anything built on Azure OpenAI stays inside your tenant — your data is never used to train anyone else's models.
Adoption is treated as part of the build, not an afterthought. Champions are trained in each team, prompt libraries are written for your actual workflows, and usage is reviewed monthly so licences that aren't earning their keep get reassigned. The measure of success is simple: are people still using it in month three?
What you'll walk away with.
Concrete artefacts, not just advice — everything documented and yours to keep.
- AI opportunity roadmap — scored and prioritised by value, effort and risk
- Data readiness report covering permissions, sharing links and sensitivity labels
- Copilot deployment plan with pilot group, training materials and prompt libraries
- Working custom assistant(s) with full documentation and hand-over
- AI usage policy and governance pack, ready for your staff handbook
- Monthly adoption and value report — usage, time saved, licences to reassign
Ways to work with us.
Start small and scale when it's earning its keep — every engagement is fixed-scope with a named senior engineer.
Two weeks. We map your data, interview key teams and deliver the roadmap plus one working proof-of-concept. Fixed price.
Four to six weeks. Tenant preparation, security trimming, pilot rollout, champion training and the governance pack.
Ongoing. We build custom assistants and automations sprint by sprint, and stay on to run, tune and report on them.
You're in the right place if.
- You've bought (or are considering) Copilot licences and want real adoption, not shelfware.
- You have repetitive document, email or reporting work that eats skilled people's time.
- You want AI on your own data without sending it to who-knows-where.
- The board keeps asking “what's our AI plan?” and you'd like a good answer.
Proposals in hours, not days.
An anonymised engagement — details available on a call.
An 85-person professional services firm in Leeds. Fee-earners were spending whole days assembling proposals and reports from past documents scattered across SharePoint.
Leadership had bought Copilot licences but adoption stalled at 20% — and an internal test surfaced a sensitive HR folder, so the rollout was paused.
Data readiness first: permissions trimmed, sensitivity labels applied. Copilot relaunched with champion training, plus a custom Azure OpenAI assistant grounded in the firm's own precedent library.
Proposal turnaround fell from days to hours, adoption stabilised near 80%, and the assistant now drafts first-pass reports that fee-earners refine instead of write.
Questions we're asked a lot.
Will our data be used to train AI models?
No. Anything we build on Azure OpenAI runs inside your own Microsoft tenant, and Microsoft's enterprise terms mean your prompts and documents are not used to train foundation models. The same applies to Microsoft 365 Copilot — your data stays yours.
Do we need Copilot licences before we start?
No. The discovery sprint works out where AI genuinely pays before you commit to licensing. If Copilot is the right answer, we'll size the pilot group so you only buy licences for people who'll actually use them.
How quickly will we see value?
The discovery sprint delivers a working proof-of-concept in two weeks. Copilot pilots typically show measurable time savings within the first month — and if the numbers don't stack up, we'll tell you and stop there.
What stops staff pasting sensitive data into public AI tools?
Governance is built into every engagement: an AI usage policy for your handbook, data-loss-prevention controls that block sensitive content leaving the tenant, and monitoring so you can see what's actually being used.
What if our documents and permissions are a mess?
That's normal, and it's exactly why we do data readiness first. We trim permissions and apply sensitivity labels before any AI tool is switched on — so Copilot never surfaces something it shouldn't.
Free AI & Cloud Audit.
A senior engineer reviews your cloud estate and AI readiness — costs, security, quick wins — and sends you a written report. No sales deck.