We advise, design and build for energy and utilities, government and universities: sectors where AI has to answer to a regulator, an auditor and the public, not just a demo.
Our clients answer to regulated bodies and the public. Everything we design and build starts from that obligation, not from a demo.
Market operators, retailers, generators and networks: real time data, AEMO obligations, critical infrastructure (SOCI) and a safety case for everything.
Commonwealth and state agencies: PSPF, ISM and IRAP, onshore data, procurement rules and services the public has to be able to trust.
Universities and research institutions: student and research data, TEQSA and privacy obligations, and AI adoption that academics will actually stand behind.
Miners and resources groups: multi site operations, acquired businesses with their own systems, safety obligations and a licence to operate that depends on getting data and AI right.
Operators were reconciling dispatch, outage and market notices across a dozen systems by hand, under a compliance regime where a wrong answer is reportable.
A retrieval layer over the operational record, an agent that drafts the reconciliation with every claim cited to source, and an evaluation harness the assurance team runs before each release. Human sign off stays where the obligation sits.
Frontline staff spent most of a case on triage and drafting, with a backlog growing faster than headcount and no appetite for data leaving Australia.
An onshore, IRAP aligned platform with a triage and drafting copilot embedded in the case system, an AI register and controls mapped to the ISM, and role based enablement so the team owns it after handover.
Student, research and enterprise data sat in separate estates, so every AI pilot started from scratch and none could answer a privacy or ethics review.
A governed lakehouse with lineage and access controls, first data products for student support, and a conversational assistant with guardrails the ethics committee approved before it reached a single student.
Every acquired operation arrived with its own systems, data teams and definitions. Group level AI use cases stalled because nothing could be joined, and centralising everything would have stripped the sites of ownership and slowed them down.
An organisation wide data architecture on data mesh principles: each operation owns and publishes its data as governed products, landing in one group platform with shared identity, lineage and quality gates. Applied AI use cases in maintenance, safety and production now run across the whole group.
We don't sell a platform. We bring strategists, designers, data, cloud and security engineers who use AI in how they work, and leave your people able to run what we build together.
Where AI creates value, what your regulator will accept, and a funded, sequenced roadmap your board can approve.
Core systems modernised with your engineers: API first services, agentic workflows and copilots with a human where the obligation sits.
Lakehouse foundations, governed pipelines, retrieval and evaluation, with the lineage and audit trail an assurance review expects.
Research and design sprints for AI services that citizens, students and operators trust, understand and adopt. WCAG 2.2 AA from the first frame.
Onshore landing zones, hybrid and edge platforms, and GPU capacity engineered for resilience, sovereignty and cost control.
Threat modelling, zero trust architecture and continuous assurance aligned to the Essential Eight, ISM and IRAP.
Defined engagements with a clear scope, timeframe and deliverable, so you can start small, prove value, and scale what works.
Four weeks. Readiness assessment, value sizing and a prioritised, costed roadmap with the governance position your board and regulator will ask about.
Learn moreTwo week design sprint. Research, service blueprint and a tested clickable prototype of your AI enabled service, WCAG 2.2 AA from the first frame.
Learn moreSix week build pod. AI assisted engineering in your repo, delivering a production ready agent or application with tests, pipelines and handover.
Learn moreA governed lakehouse, first data products and retrieval layer stood up in eight weeks, with lineage, quality gates and cost controls in place.
Learn moreIndependent review of AI systems before and after go live: evaluation harnesses, red teaming, guardrails, an AI register and controls mapped to the Essential Eight and ISM.
Learn moreSix weeks. An onshore, IRAP aligned landing zone for running models and agents against your own data: identity, data classification, guardrails and GPU capacity, ready for your first production workload.
Learn moreNo discovery decks and no bench. A pod of four to six people sits with your team, works in your repo and your risk framework, and hands over something running, with the evidence your auditor will ask for.
Two weeks with the people who own the problem, not a discovery deck. We leave with a scoped brief, a data and risk map, and a go / no go your executive can sign.
A reference design that fits your estate: onshore hosting, identity, data classification and the controls your regulator expects, settled before any code is written.
A pod of four to six people working in your repo and your change process, shipping in short increments. Your people pair with ours so ownership transfers as we go.
Evaluation harnesses, red teaming and audit trails before go live. Then monitoring, drift alerts and a runbook your team can operate without us.
Tell us where your modernisation is stuck. We'll come back within a working day with a one page read on whether we can help.