AI &
AUTOMATION.
Practical AI and automated workflows designed to remove repetitive work and connect information across the business.
A demonstration with fictional sample data. Every company, person, reference and figure in these documents is invented.
PRINCIPLE
AI SHOULD DO SOMETHING USEFUL.
Use AI where it removes work, improves information or makes an existing process better — not simply because AI can be added.
WHAT IT COVERS
06 AREAS
- 01
DOCUMENT EXTRACTION
Pull the details that matter out of enquiries, invoices, forms and site notes, check them, and put them where they belong instead of re-typing them.
- 02
CLASSIFICATION & ROUTING
Sort incoming emails, requests and tickets by type and urgency, then send each one to the right person or system with the context attached.
- 03
AUTOMATED WORKFLOWS
Chains of small, dependable steps. When something arrives: check it, record it, tell the right person and create the follow-up.
- 04
SUMMARIES & DRAFTS
Condense long threads, call notes and reports into something a person can act on, and draft routine replies for someone to check and send.
- 05
AGENTS WITH LIMITS
Tools that can look things up and take bounded actions, with clear permissions, a full log of what they did, and sign-off where it matters.
- 06
SEARCH YOUR OWN INFORMATION
Ask questions of your documents, procedures and records, and get answers that point back to where they came from.
PEOPLE IN THE LOOP
KNOW WHAT IT DOESN'T KNOW.
A model that is right most of the time is only useful if the system can tell when it isn't. Every value it extracts carries a confidence, and anything below the line goes to a person rather than straight into your records.
That is the difference between a demo and something you can rely on on a Monday morning. The automation handles the routine volume; people handle the judgement calls, with everything they need in front of them.
WHAT I BUILD IN FROM THE START
- Confidence thresholds per field, not per document
- A review queue for anything uncertain or unusual
- A log of every input, output and decision
- Plain rules around the model for the things that must never change
- A way to switch it off and carry on by hand
APPROACH
HOW I'D APPROACH IT.
- 01
Find the repetitive work
Where does someone copy, re-key, sort or chase the same kind of thing every day? That is usually where the value is.
- 02
Test on real examples
Before building anything, I run a sample of your actual documents or messages through the approach and look honestly at where it struggles.
- 03
Build the smallest useful version
One workflow, end to end, connected to the systems you already use, with review built in from day one.
- 04
Widen it carefully
Once it has earned trust, raise thresholds, add document types and take on more of the routine work.
PLAIN ANSWERS.
Where does AI save the most time?
On reading, sorting, summarising, drafting and answering: emails and enquiries, documents and forms, call notes and customer records.
Can the AI make mistakes?
Yes, which is why every value it extracts carries a confidence, and anything below the line goes to a person for review instead of straight into your records. A log keeps every input, output and decision.
Does it work from my own data?
Yes. It works from your information, inside the systems you already have, with access agreed with you first.
Where do we start?
With a single, clearly defined job rather than an AI strategy. The result is then compared with how the job was done before.
What is worth automating?
Anything done the same way more than a few times a week: entering data, sending updates, chasing approvals and building reports.
What happens when something goes wrong?
Failures are logged and flagged, never silent. Cases that need a person are routed to one, with the context they need.
HAVE A PROBLEM WORTH SOLVING?
Tell me which job eats the most time each week. I'll tell you plainly whether AI helps with it, or whether a simpler rule would do the job better.
Start a project