SERVICES · AI
AI & Agentic Delivery
We take AI from pilot to production: your data, your model choice, and working software signed off every sprint.
Most organisations don't have an AI problem. They have a dozen pilots, a growing token bill, and nothing in the hands of users. We build agentic systems that ship, run them onshore where they need to be, and leave behind people who can direct the work.
$15M quoted,
$800K delivered.
An RPG mainframe migration, three months, agentic delivery.
7 working systems in 45 minutes.
Built by 25 executives, not engineers, at EDUtech 2026.
4 production apps in 12 weeks.
First MVP in two. 640 automated tests, WCAG 2.1 AA compliant.
From pilot purgatory to production
A proof of concept answers a question and stops. The failure mode most organisations hit is trying to promote the demo to production, which is how you end up with a dozen pilots and nothing live.
We build production-shaped from day one: real codebase, your infrastructure, an evaluation harness, and the security and accessibility standards your auditors expect. The pilot isn't a throwaway that proves the idea. It's the first working slice of the system.
Where this usually starts: Feasibility spike for the genuinely unknown, Rapid MVP (AI variant) when the fastest answer is to build it.
THE DIFFERENCE
The harness is the asset
The model is the commodity. The return on your AI spend is determined by what you build around it: evaluation, guardrails, context, review loops, and the judgement about when to let an agent run and when to pull it back.
That's the harness, and whether you own it or rent it is the decision most AI strategies quietly skip. We build harnesses our clients own. When the model market moves, and it moves every quarter, the asset stays yours and the model becomes a swappable part.
Frontier, open-weight or self-hosted: movable by design
The right model depends on the workload, and the right answer changes as prices, capabilities and rules change. We architect so load can move: frontier models where they earn their cost, open-weight models where economics or control favour them, self-hosted where the data can't leave your perimeter.
That portability is also your negotiating position. An organisation that can move workloads pays market price. One that can't pays whatever the invoice says.
Keep the data, the spend and the capability onshore
Sovereignty stopped being a preference and started acquiring legal weight. From 10 December 2026, organisations using automated decision-making that significantly affects people must disclose it in their privacy policies, and the regulator is already sweeping for compliance.
We deploy open-weight models on Australian infrastructure, inside your perimeter where required, with the data, the spend and the operating capability staying in the country.
Who directs the work
Ways to start with AI
FLAGSHIP REVIEW
AI Capability Review
The models you run, the harness around them, and the people who direct the work. One review, five answers.
BUILD
Rapid MVP, AI variant
An agentic feature or workflow, production-shaped from day one.
BUILD
Feasibility spike
One question, answered in code. If you'd call it a proof of concept, this is ours: it answers the question, then stops.
WORKSHOP
AI hackathon
Your people, one problem, agentic tooling, a short clock.
BRIEF YOUR EXECUTIVE TEAM
We brief boards and executive teams for free, with the material we take to stages like the Gartner IT Symposium: what agentic AI is doing to cost, sovereignty and team shape. No pitch, no slides about us. Request a briefing →
Latest Insights
Talk to a Co-CEO
One conversation, and you'll know whether we can help. No handover to a sales team.
Frequently asked questions
What is agentic AI delivery?
Software delivery where AI agents do a substantial share of the building, directed by senior engineers who own the outcome. The agents write and test code inside a harness of evaluations, guardrails and review; the judgement and the accountability stay human. It's how we delivered a $15M-quoted mainframe migration for $800K.
How do we get AI pilots into production?
Build production-shaped from the start. The gap between a demo and a system is the harness: evaluation, monitoring, guardrails, security review, and an operating model for when the AI is wrong. Pilots built without those have to be rebuilt to ship, which is why most never do.
Should we use frontier or open-weight models?
Both, usually, and the mix should be able to change. Frontier models where capability earns their cost, open-weight where economics, latency or control favour them. The architecture decision that matters is portability: if you can't move workloads, you can't respond when prices or rules move.
Can our data stay in Australia?
Yes. Open-weight models deployed on Australian infrastructure, or inside your own perimeter, keep data onshore and under Australian jurisdiction. From 10 December 2026, automated decision-making disclosure obligations make where and how your models run a compliance question, not just an architectural one.
What does an AI capability review cover?
Which models you should run and where, the architecture and harness around them, where your token spend goes, and which of your people can direct agentic work. Fixed scope, fixed price.
Do you build it for us or with us?
With you. Your people embed in the delivery team and capability transfers by shipping together. As your team grows in confidence, we reduce ours. If you want a system delivered and handed over, we do that too.
