ARQUA · SCIA Reference Architecture · Sectors · Request a Briefing
National logistics and public service organisations rely on AI to optimise transport flows, network operations, delivery commitments, inventory forecasting, and customer service functions. These decisions affect service performance, public trust, and operational resilience.
Many AI systems deliver optimisation gains, but struggle when decisions must be reviewed, explained, or defended — especially in high-impact, high-variability environments. The risk is not automation itself — it is opaque decisioning with unclear accountability.
Our architecture ensures AI supports logistics and service outcomes without weakening control, oversight, or human responsibility.
We embed governance directly into how AI systems operate — not as an afterthought.
Rather than relying on policy statements or retrospective analysis, our architecture ensures that:
This allows organisations like Australia Post to scale AI with confidence, knowing decisions can be reviewed, explained, and defended when required.
Our architecture is organised into three layers:
Each AI system operates within approved logistics and service contexts — defining what it exists to support, and where it must not be used. This prevents scope drift and unintended decisioning.
Human accountability is enforced for decisions affecting network performance, service delivery, or public outcomes. Approval, override, and escalation responsibilities are explicit.