Service
AI & Business Automation
Take manual work out of one workflow at a time, with controls.
The problem
If this sounds like you
- “People copy the same data from one system into another every day.”
- “We tried an AI pilot and it stalled when it met our real data.”
- “Approvals sit in inboxes for days.”
- “The answer is in a document somewhere, but nobody can find it.”
What we do
Most AI pilots fail on data, not on models.
So the work starts with one workflow and the data behind it. We look at where the data comes from, who trusts it and what happens when it is wrong. Only then do we choose what to automate.
We do three kinds of work: process automation, adding AI to the systems you already run, and narrow agentic workflows.
An agentic workflow is software that takes several steps on its own inside a tight boundary. Ours always stop for a person’s approval before anything is committed.
General examples
Four kinds of manual work that usually repay automation.
Each one keeps a human approval step.
Document handling
Reading invoices, purchase orders and forms, and preparing the entry in your system. A person checks and approves before anything is posted.
Approvals
Gathering what an approver needs into one view and drafting a recommendation. The approver makes the decision.
Reconciliation between systems
Matching records across two systems and listing the mismatches with a suggested correction. A person approves each correction.
Knowledge retrieval
Answering staff questions from your own procedures and documents, with the source shown. A person approves before an answer goes to a customer or into a decision.
On the shop floor
Manufacturing use cases
Quality inspection, maintenance, planning, energy and more, each with the measure it moves.
Rules first
AI governance and acceptable use
If staff already use public AI tools with company data, set the policy and the data boundary before you automate.
The prerequisite
An enterprise data platform
One governed place for business data. It is the step nobody budgets before starting AI work.
Before we start
What must be true first
If these are not in place, this may not be the right time. We would rather say so on the first call.
- One workflow with a named owner. Someone who does the work today and wants it changed.
- The data exists and we can reach it. If it lives in people’s heads or in scattered files, that is the first job, and we will say so.
- You are willing to agree a measure before we build. The review sets out how return on investment will be measured.
- There are rules for AI use, or you want them. If there are none, start with AI governance.
Matching entry offer
AI & Automation Opportunity Review
1–2 weeks, fixed scopeYou get: A workflow list, a feasibility view, one recommended pilot and how return on investment will be measured. Quoted after the first call. The written outputs are yours.
Talk it through with someone who has run it.
Thirty minutes. We will tell you plainly whether this is the right first step.