Annie is the sovereign AI application layer for Australian data centres
Annie is a platform, not a model. Each enterprise customer brings their own models. More customers means more models means more racks consumed. A workload-generation partnership for sovereign compute operators — built on the application layer that makes the infrastructure valuable.
A sovereign orchestration platform, not a single model
Annie is a verified AI orchestration platform — a system of open pipeline roles (twelve today) that classifies, routes, judges, and verifies expert responses before any output ships. It ships with sovereign Workforce Foundation Models and is designed to run fully air-gapped on infrastructure the customer controls. The platform orchestrates your customers' domain expertise — and that's the workload.
Why this matters for sovereign compute
Frontier APIs concentrate inference on a handful of overseas hyperscalers. Annie is the opposite: a platform your customers deploy on their own racks, with their own models, behind their own perimeter. Every customer deployment is a long-term, sovereign inference workload — not a single API call that can be redirected by a provider decision.
Operators running Annie customers are running the application layer that Australia's regulated industries need to keep their AI in-country. That's a different proposition from commodity inference — and a durable one.
What runs on your infrastructure
- Verified multi-model inference, not a single black-box API
- Customer-owned specialist models, fine-tuned on customer data
- Cognition Stream fine-tuning cycles, off-peak
- Full audit trail, on-jurisdiction, regulator-ready
- Air-gapped deployments where required (defence, classified workloads)
More customers. More models. More racks.
Annie brings the application layer. Each customer brings their own specialist models. The compounding effect is structural: every new Annie customer is a new long-term inference workload on your infrastructure, and the more customers you host, the more models run side by side.
Each Annie customer brings their own models. A bank brings their risk model. A defence contractor brings a classified specialist. A health service brings clinical decision models. Each model is a long-running inference workload on your infrastructure.
Annie runs on standard inference GPUs at moderate power density. High revenue per rack without the capex and energy overhead of training clusters. The verification pipeline runs continuously, not in bursts.
Position as the data centre running Australia's sovereign AI platform — not just infrastructure, but the application layer that makes sovereign AI real for government, defence, financial services, and healthcare buyers.
The question every operator is answering right now
There is significant sovereign AI-optimised compute under development in Australia. The build is happening. The open question across the sector is the same: what runs on it that isn't a hyperscaler API call routed offshore?
What Annie customers actually need
- APRA-regulated inference that stays on-jurisdiction, with a full audit trail for the regulator
- PROTECTED workload environments, fully air-gapped, with no external API dependency
- Healthcare deployments where patient data must never cross the perimeter
- Defence and intelligence workflows running classified specialists that operators never see
Operators positioned to win the sovereign AI workload
Australian sovereign data centre operators
IRAP-assessed facilities, Australian-owned or sovereign-aligned ownership, governance frameworks that satisfy APRA, ISM, and PROTECTED requirements.
Standard inference GPU infrastructure
H100 / H200 / equivalent fleets. Moderate power density is enough — Annie runs on inference, not training workloads. No specialised cluster required.
Sovereign cloud and government-aligned providers
Operators already serving federal, state, or defence customers. Existing relationships in regulated industries. Compliance posture ready for AI workloads.
Operators building AI-native revenue lines
Looking for high-value inference workloads to differentiate commodity capacity. Want to participate in the application layer, not just rent racks.
Three steps from conversation to first customer workload
We walk through your facility, your GPU fleet, your sovereign and compliance posture, and the regulated industries you already serve. 60 minutes. We tell you whether the fit is real.
We design a deployment model matched to your infrastructure — pipeline configuration, customer onboarding flow, security boundary, and commercial structure. Presented to your technical and commercial teams.
We bring the first Annie customer to your infrastructure. You see the workload, the revenue, and the compounding effect. From there, it scales.
Build the application layer that makes sovereign AI real
Annie needs sovereign compute. Your facility needs high-value, long-term inference workloads. The partnership is the work.