AI & Business Automation
Every business runs on a few tasks nobody should be doing by hand. They are rarely the ones anyone thinks to mention.
We start by watching what actually happens: who re-keys the same figures into two systems, which approval waits three days for a signature, what report somebody rebuilds by hand every month. The candidates are usually obvious once they are written down, and they are almost never the thing the business assumed. We cost them in hours before proposing anything, so the decision to automate is made against a number.
Most of it is built on tools you already pay for — Power Automate, the Graph API, SharePoint, Azure — with custom code where the platform runs out. AI goes in where the task genuinely needs judgment: reading an invoice that arrives in a different layout every time, summarising a long thread, answering a question out of your own documents. Where a rule will do, we write the rule. It is cheaper and it does not drift.
Automation nobody can fix is a liability. Everything we build is documented, runs in your tenant under accounts you own, and fails loudly rather than quietly — a workflow that stops silently is worse than one that was never built. We agree in advance what happens when it cannot decide, and who it hands to.
Process discovery
We map and time the task before quoting it, so the business case exists before the build does.
Document & data capture
Invoices, forms, and attachments read and posted into the system of record, without re-keying.
Approval & onboarding workflows
New hires, departures, and sign-offs routed, tracked, and closed out rather than chased by email.
Scheduled reporting
Figures pulled from several systems into one report on a schedule, instead of rebuilt by hand each month.
Q&A over your own documents
An assistant answering staff questions from your policies and files, and from nothing else.
Ownership & monitoring
Built in your tenant, under your accounts, documented, and alerting when a run fails.
Is this going to replace staff?
That is not usually what happens, and it is not how we scope it. What comes out is the repetitive part of a job, not the job — the re-keying, the chasing, the monthly rebuild. If headcount is the actual goal, say so at the start, because it changes what is worth building.
What happens when the AI gets it wrong?
It will, some of the time, which is why nothing we build acts unsupervised on anything that matters. Low-confidence cases route to a person instead of guessing, and what it did is logged so you can check it. Anything with money or a legal consequence attached keeps a human approval step.
Where do we start, and what does it cost?
One process, scoped and priced as a fixed project, picked because it repeats and because someone can tell us how many hours it takes today. That is a useful deliverable on its own, and it tells you whether the second one is worth doing.
Next step
Let's talk about ai & business automation.
Tell us what your setup looks like and what has been going wrong. We will tell you what we would do about it, and roughly what it costs.