Services · AI that ships

AI that lands in production — or we don't build it

AI that works on your real data, is tested before you see it, and keeps working after launch. Or we tell you not to build it. AI drafts the routine work; a senior engineer reviews every line and puts their name on it.

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What actually ships

Six things we check before AI touches your business

Each box is a hard check we put on AI work — so what goes live is narrow, measurable, and owned.

One job, measured

We start small. If it doesn't save hours, we stop.

Built on your real data

Answers from your trusted numbers, not a pile of documents.

Tested before you see it

It passes a written exam before we demo it.

A person approves every change

AI drafts. Someone you name signs off.

Customer data stays private

Names, accounts, and passwords never leave your building.

Looked after once it's live

A predictable bill and a backup if the AI fails.

1 of 6 · One job, measured

We start with one task that saves real hours. If it doesn't, we stop.

One workflow, a clear success number, a short experiment — and a monthly running cost you see before you commit.

What it means

Today

A vendor promises 'AI across the business.' Six months later you have a pilot, no metric, and a bill that keeps growing with no cap.

With AKAF

We pick one job — invoice match, ticket draft, a report people hate writing. We tell you the monthly running cost up front and cap it. If it doesn't save hours in a fixed window, we switch it off.

Think of this as a trial shift, not a permanent hire. One job, measured. Cost known before you commit. If it doesn't earn its keep, we switch it off.

Focus on one job

One workflow with a clear owner — not a vague 'AI for everything' program.

Clear success metrics

Hours saved, errors avoided, or cycle time cut — written down before we start.

Cost capped

Monthly running cost before you commit — and a hard stop if it doesn't pay.

Which one task burns the most hours on your team right now?

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