Express workload intent.
Define compute, timing, budget, sovereignty and operational requirements once.
- AI and HPC profiles
- Policy and cost constraints
Sovereign by designPolicy applied before dispatch
Infrastructure neutralOne interface across venues
Decision traceabilityEvery placement recorded
AI + HPCTraining, inference and research
The platform
A control plane for distributed compute.
Omega AI is one place to plan and buy computing power. You tell us what you need to run, your budget, your deadline, and your rules (for example, “this must stay in Australia”). We score every venue in our catalogue against those rules, rank the best available one, and record the reasoning behind the decision so it can be audited later. Execution today runs on our Australian AWS venue.
You get one point of contact instead of many, tighter control of your budget, and a record of why each decision was made. And because your requirements travel with the job rather than being written into one provider’s contract, adding or changing a venue does not mean rebuilding your setup.
Platform capabilities
Built for infrastructure decisions, not demos.
The exchange model is designed around the controls enterprise and government buyers need before they trust a platform with material workloads.
01
Control planeOne workload interface
Submit workload requirements independently of any single infrastructure provider.
Reduce venue-specific integration and procurement friction.02
FederationDistributed supply
Coordinate eligible compute across a multi-venue fleet instead of treating each site as an island.
Create a broader operating envelope for variable demand.03
PolicyPlacement under constraint
Evaluate cost, performance, timing and sovereignty requirements before a workload is dispatched.
Turn governance requirements into operational rules.04
OperationsDecisions you can inspect
Record why a venue was selected and keep workload state visible through the Argus operating layer.
Support operational review with decision evidence.Reference architecture
Control separated from execution.
Omega AI coordinates workload intent and placement. Compute remains distributed across eligible infrastructure venues, avoiding a new centralised dependency.
OMEGA CONTROL PLANE01Workload intentCompute profile · budget · timing 02Policy engineSovereignty · eligibility · constraints 03ExchangeVenue match · dispatch · reassessment 04ArgusState · evidence · operational visibility
Policy-bound dispatch
FEDERATED EXECUTION VENUESAU / 01AI clusterTraining · inference AU / 02HPC facilityResearch · simulation AU / 03Private cloudEnterprise workloads AU / NNew supplyFederated as eligible
No forced venue lock-in. Workload intent remains portable across eligible supply.
Policy before placement. Requirements determine which venues can be considered.
Evidence after dispatch. Argus retains the reasoning behind each placement.
Who the exchange serves
One market layer. Different operating mandates.
The buyer is not asked to accept a generic cloud model. Placement can reflect the commercial, technical and sovereignty constraints of each organisation.
01
Government
Policy-controlled AI and HPC procurement with Australian operating context and traceable placement decisions.
Sovereignty controls made operational02
Enterprise
A consistent route to compute for teams balancing delivery deadlines, governance, cost and infrastructure availability.
Less venue-by-venue overhead03
Research
Access pathways for simulation, modelling and AI workloads with requirements that change by project and funding cycle.
More flexible capacity access04
AI builders
Training and inference placement across eligible infrastructure without coupling the product to one compute estate.
Portable workload intentAssurance
Trust should be inspectable.
We do not use unearned certification badges or vague claims of security. Enterprise assurance starts with explicit workload requirements, evidence, and a defined deployment path.
Procurement principleClaim only what can be evidenced.
Sovereignty controls
Data residency and venue eligibility requirements can be represented as workload policy before placement.
Operational governance
Cost, timing, performance and infrastructure constraints are evaluated as part of the dispatch decision.
Decision auditability
Argus records placement reasoning and operational state so decisions can be reviewed after dispatch.
Enterprise assurance path
Security, service levels and deployment requirements are assessed with each organisation during qualification.
The market layer
Australian compute is a coordination problem.
AI and research now demand enormous amounts of computing power. In Australia that power exists, but it’s scattered across separate data centres, clouds, and private facilities, each with its own price, its own rules, and its own spare capacity at any given moment.
So every buyer (a government department, a company, a research team) has to shop around, negotiate site by site, and hope they picked well. They often can’t guarantee their data stays on Australian soil, and they can’t easily prove why they chose one provider over another.
The strategic asset is not another data centre. It is the control plane that can coordinate many of them.
DEMANDWorkloads
- Government AI
- Enterprise platforms
- Research & simulation
OMEGA AICompute
ExchangeIntent · policy · dispatch · evidence
ExchangeIntent · policy · dispatch · evidence
SUPPLYInfrastructure
- AI clusters
- HPC facilities
- Cloud & private capacity
Start with a real requirement
Bring us a workload, or capacity.
Tell us what must run, where it can run, and what matters most. We will assess the operating fit and define a practical next step.
For enterprise, government, research and infrastructure partners.Useful starting information
- 01WorkloadTraining, inference, simulation or other HPC
- 02ConstraintsLocation, security, timing, budget and hardware
- 03Operating needPilot, recurring capacity, burst or supply partnership