AI engineering consultancy
Most AI assistants stall at the demo. We build production AI that puts your own data to work — helping your teams sell, find answers instantly, and get things done for themselves — with every access secured and audited. Behind the work: twenty-five years of engineering at Microsoft and GitHub, shipping software used daily by billions.
One governed tool layer — built on the Model Context Protocol — connects your ERP, documents and operational data to every AI surface you use: Microsoft Teams, M365 Copilot, Claude, and whatever comes next. Build the tools once; every assistant gets them.
Assistants your staff actually use — quoting from live stock and customer pricing, answering from your own policies and product data, and letting people do for themselves what used to need a phone call. Cited, evaluated, governed.
Cloud AI reaching on-premises data over private networks — no public exposure, no shared secrets, every access authorised as a real identity and audit-logged.
Modern, secure API platforms in front of the systems your business already runs on — with existing integrations kept working, byte for byte.
Azure and AWS, infrastructure as code, full observability — and engineered for cost as deliberately as for capability.
Case study — logistics
A multi-branch building-materials distributor was paying dearly for failed deliveries: trucks arriving loaded with lumber and nobody on site to receive them. We built a notification platform that runs the whole delivery lifecycle over two-way SMS and email — confirming dates ahead of time, flagging when the truck leaves the yard and when it’s one stop away, and writing every confirmation straight back into the ERP.
Large shipments now arrive expected and attended — safely, with someone on site. The API platform behind it serves roughly 670,000 requests a day, and the legacy API it replaced was kept byte-for-byte compatible: not one existing integration broke.
Case study — enterprise AI
For a US enterprise, we built an AI assistant deployed company-wide in Microsoft Teams: cited, retrieval-grounded answers across training, HR, supplier and product sources — plus live stock and customer pricing queried from the on-premises ERP at the moment of asking. Every backing service sits behind private endpoints; even embeddings run inside the tenant boundary.
Frontline staff get instant, cited answers in the flow of work — under governance enterprise IT signed off on. No shared secrets anywhere, per-user authorisation with full audit trails, and every agent change regression-tested against a versioned evaluation suite before release.
Anyone can demo an agent. Shipping one that still works on a wet Tuesday in week forty is engineering.
A line about the problem is enough to start. You'll deal directly with the engineers doing the work — no account layer, no handover.