"What did we quote the Boksburg customer for the last three brackets, and did we make money?"
The answer comes back in plain English with the quotes, job cards and invoices it came from — checkable, not remembered.
AI for manufacturers — how it works here
We build private AI brains for South African businesses — a system your company owns that knows your files, emails and history, and answers in plain English. In a factory, that means the job cards, the drawings, the quality records, and the thirty years of "how this machine actually behaves" that currently lives on the floor.
Begin the free diagnosticSound familiar
What it looks like on your floor
"What did we quote the Boksburg customer for the last three brackets, and did we make money?"
The answer comes back in plain English with the quotes, job cards and invoices it came from — checkable, not remembered.
"Why was batch 4711 released with that surface finish?"
The concession email, the inspection record, and who signed it — assembled in seconds, the way an auditor wishes you could.
The routine paperwork, drafted.
Overdue-invoice reminders, delivery-note chases, the monthly customer report — drafted by the system, signed by your people. Nothing reaches a customer without a signature.
Proof, honestly framed
Our proof is our own businesses — Attesté, an art-collection platform run by one person and an AI system; Practacular, practice management for South African accountants; and BlitzBox, our on-premise AI appliance. Our own products, not client deliverables — and not one of them manufactures anything.
That's the honest argument for the pattern: the brain isn't an industry template. It's built from your job cards, your drawings, your emails — which is why the same approach has worked across an art platform, an accounting practice, and an appliance. A factory's knowledge is different in content, not in kind: it lives in files, mailboxes and heads, and that's exactly what the system reads.
The diagnostic is where we test that claim against your operation specifically — and where we'll tell you if we're not the right fit. We'd rather lose the sale than install a disappointment.
Before you ask
The setter, the estimator, the bookkeeper — what happens when the one person who knows walks out the door.
Read the essay →Why nothing this system sends reaches a customer without a person signing it — and why that's a feature, not a speed limit.
Read the essay →What it costs, whether your data leaves the premises, and what happens if you stop paying.
Read the FAQ →Next step
Plain questions about how the plant actually runs. You get the first workflow we'd prove, the stage that fits, and the fixed price — before you commit a rand.
Begin the diagnostic