Case studies
This is work we are able to describe.
Some of what we build sits inside environments we cannot write about, so these are the engagements where we can give you the detail.
Giving charity CEOs the confidence to use AI properly
Charity chief executives were being asked to make decisions about AI without the grounding to make them safely. We ran capability workshops with CEOs across the Canberra community sector on where the ethical and legal lines sit, and where AI can improve the services they deliver.
- We aimed it at the people making the decision
- CEO-levelWe aimed it at the people making the decision
- We grounded it in their actual obligations
- Ethical & legalWe grounded it in their actual obligations
- We delivered it across organisations at once
- Sector-wideWe delivered it across organisations at once
Building AI capability at two scales: the enterprise and the community
Policy does not make people AI-capable. We pair whole-of-agency sessions that reach everyone with a small, open Canberra practitioner community co-founded with an Australian university, because confidence is built by trying things rather than by reading guidance.
- One agency heard the same message at once
- Whole-of-staffOne agency heard the same message at once
- The partnership keeps sessions evidence-based
- UniversityThe partnership keeps sessions evidence-based
- AI in the Shadows meets regularly in Canberra
- ~30 peopleAI in the Shadows meets regularly in Canberra
Cold chain monitoring, reporting and alerting, built at speed
A national courier business needed visibility over temperature-controlled freight: continuous monitoring, reporting its customers could rely on, and alerting that reached someone while the load could still be saved. We used AI-accelerated development practices to build it in a fraction of the usual timeline.
- We went from start to a working system in weeks
- WeeksWe went from start to a working system in weeks
- Monitoring runs across temperature-controlled freight
- ContinuousMonitoring runs across temperature-controlled freight
- Alerts arrive while a load can still be saved
- Real-timeAlerts arrive while a load can still be saved
A whole-of-department AI Strategy, built on four pillars
A department operating at national scale needed an AI strategy that could satisfy its executive, its assurance functions and the public interest at once. We delivered a four-pillar strategy covering 2026 to 2029, linked end to end from mission risk through to costed milestones with named owners.
- We advanced all four pillars in parallel
- 4 pillarsWe advanced all four pillars in parallel
- We scoped, costed and assigned each milestone
- 18We scoped, costed and assigned each milestone
- The roadmap sequences the investment
- 2026 to 2029The roadmap sequences the investment
Your turn
If your problem looks like one of these, tell us about it.
We will be straight with you about whether AI fits and what the work would take.