Managed AI · Custom apps

Custom AI apps on your data

Assistants, approvals and customer portals built over your own HubSpot, QuickBooks, Microsoft 365 and supplier data, with guardrails.

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What it is

The useful AI apps are rarely the clever ones. They are the ones that sit inside a process you already have, read what is already there, and take a job off someone’s desk without anyone having to trust them blindly.

That is the shape we build: a narrow job, real data, clear permissions, a person who approves, and a log of everything. We start read-only and widen it as it earns trust. Then we run it, because an app nobody watches is worse than no app.

Who it is for
  • Companies with a process that lives in someone's head and a spreadsheet.
  • Firms whose customers keep asking the same questions the data could answer.
  • Owners who want a portal for their own clients, without a software company's bill.
What is included

In plain words

  • An assistant that answers questions from your systems, with each user's own permissions
  • Approvals: the app prepares the action, a named person clicks yes
  • Customer-facing portals: orders, status, documents, self-service
  • Document handling: read, extract, file, and raise the exception
  • Connections to the suppliers and systems you already use
  • Running it afterwards: monitoring, changes, and an engineer accountable
In the portal

How it shows up day to day

The assistant in our client portal is one of these apps. It reads live data about your services and orders, prepares quotes for approval, and never sees another client's data.

See the portal →

Senior engineer

Sets the boundaries: what it may read, what it may do, who approves.

Assistant

Answers from your data, prepares the action, waits for the approval.

The same job, both sides. An engineer decides; the assistant does the running around.
2006
Established
20
Years, and counting
3
London-area offices
6
Regions with client sites
8
Services, one agreement

Live service numbers, measured weekly and dated, are coming to this strip. We publish nothing we have not measured.

Questions

Questions people ask

How do you stop it doing something wrong?
It starts read-only. Anything that changes data or money goes through an approval by a named person, and every action is logged. The boundaries are set by an engineer, not by the app.
Can we see one working before we commit?
Yes, on sample data, on a call. We do not show other clients' data and we do not ask you to imagine it from a slide.
What does it run on?
Microsoft Azure in the UK, with the same sign-in your staff already use. Your data stays in your systems; the app reads it with the permissions you give it.

Start with a conversation.

Let's Talk AI is a first call that ends with a short list of what is worth doing first.