Auditor
We review records, processes and handovers to identify where time, money or accountability is lost.
001Homepage
It's earlier than you think.
Everyone feels behind on AI. The truth is it's just getting started — most organisations haven't moved a single workflow into production. We build your first one, then hand your own staff a system they can run after we leave. Every engagement starts with the A$500 AI diagnosis.
Only about a third of Australian AI pilots reach production. Roughly two-thirds stall on data, change and governance gaps, not the technology.
Same work, two ways to staff it9 people vs 4 + AI
Without AI
Manager
...and the next hires, as work grows.
Same output — 9 people
Coordination overhead compounds with every hire.
With AI
Manager
AI carries the leg-work; people direct it.
Same output — 4 people + AI
The margin becomes the advantage.
Both ship the same work — one pays for it in headcount.
003The difference
Our work starts with observed operations.
We review the way the organisation currently works before recommending a system change. This keeps the work tied to evidence, cost and operational responsibility.
H/00Three hats, one engagement
Builder
We build production systems with controls, ownership and documentation from the start.
Founder
We keep recommendations practical, cost-aware and linked to adoption by the people who run the process.
004How it works
The method follows the evidence.
- 01
OBSERVE
We observe the current process and review the records that support it.
- 02
MAP
We map the points where coordination, cost or accountability breaks down.
- 03
PRIORITISE
We identify the first system change that would have the clearest operational value.
- 04
BUILD
We build the selected system in production with defined controls.
- 05
DOCUMENT
We document ownership, operating steps and decisions so the process can be maintained.
- 06
REVIEW
We review whether the system is working and identify the next evidence-based improvement.
005Engagement sequence
The first engagement defines the work.
- 01
A$500 AI diagnosis
First engagementA documented assessment of the coordination gap, its operational effect and the practical AI use cases worth pursuing.
Follows → This is the paid first engagement before any build is scoped.
- 02
Build
The selected system is built in production with defined controls, ownership and operating documentation.
Follows → The build follows the diagnosis finding.
- 03
Retainer
We continue to review performance, improve the system and assess the next coordination problem.
Follows → This suits organisations that need ongoing review and delivery capacity.
006Live enterprise engagement
An enterprise client: a high-volume logistics operator
Engagement scopePre-launch · engagement scope
- ~230,000/day
- Calls now automated
- ~1,200 roles
- Call-handling reduced
- ~300 staff
- Redeployed to supervision
An enterprise client — a high-volume logistics operator — was running a manual calling operation by hand, averaging about 230,000 calls a day at 15–30 seconds each. We built and put into production an AI voice-notification system to run it. Live, the system reduced call-handling headcount by about 1,200 roles and let the operator redeploy about 300 staff into supervisory and quality roles with upskilling. The engagement covered the financial model, telecom vendor economics, integration design, the production command centre, and a security and go-live readiness review.
Engagement details are anonymised to protect the client. The figures are the operator's measured results.
007Client information
The main terms are stated plainly.
A fixed paid first engagement focused on one coordination problem. We review how that work moves today, where it loses time, money or accountability, and the practical AI use cases worth pursuing, including where AI should not be used. You leave with a ranked, decision-ready assessment. It is the only way to start with us, and it is fully refundable within 7 days if you are not satisfied with it.