Brisbane, Australia
Assess → Build → Adopt
We find where AI pays in your business, build it, and get your people using it.
Book an IntroWhat we do
Most companies have AI. Few get value from it. The difference is knowing what to build, building only that, and making sure people actually use it.
We map how your business actually runs — interviews, workflows, numbers — and hand you a ranked plan of where AI pays and where it doesn't.
We build only what the assessment justified — nothing speculative, nothing off the shelf that doesn't fit how you work.
Training and enablement until the tools are part of the day job. Access is not adoption — a tool nobody uses returns nothing.
The front door
Diagnose before you build. It's how you avoid spending implementation money on the wrong thing.
We learn your business before we walk in — market, model, systems, the lot.
Leadership sets the goals and the yardstick: what success has to look like in numbers.
We sit with the people doing the work and map where it's manual, slow, or breaking.
Every finding gets sized in dollars and ranked. Some of the answer is always "don't use AI here."
You walk away with a plan you could hand to any builder — including us.
From the blueprint — illustrative sample
| Opportunity | Hours/wk | Annual leak | Verdict |
|---|---|---|---|
| Quote & tender document assembly | 14 | $61,000 | Build first |
| Inbound enquiry triage | 9 | $28,000 | Build second |
| Monthly client reporting | 6 | $21,000 | Off-the-shelf tool |
| Customer-facing chatbot | — | — | Don't build |
Every line is sized the same way: hours per week × what you'd pay someone to do it × 52. Rank by the number, build the thing that pays first.
Proof
“On an average week, maybe about three or four hours [saved]. The end-of-month reports probably save me another four or five hours — and the quarterly report would save me a whole day.”
Operations lead, workplace-rehabilitation publisher
“I can’t say it’s perfect — but for me, it’s just fantastic at finding things. It’s enormous.”
Managing Director, same engagement
UCLA Health
UCLA Health needed to know where AI could actually help across a health system. The assessment pointed at patient education — so that's what got built: AI-generated patient-education video, deployed where it measurably paid. Clinicians got hours back; patients arrived better prepared.
Toby Fox-Mason is credited on the resulting peer-reviewed research paper.
Who it's for
Serving Australian industry — construction · resources · manufacturing · logistics · care
Next step