AI Infrastructure: the digital intelligence layer
DNY combines technical evaluation, local integration, managed infrastructure and ongoing operations — so organisations can adopt suitable AI without assembling and governing the entire stack themselves. The same infrastructure powers DNY’s physical intelligence layer and ventures.
What the infrastructure is made of
Each module is model-neutral, licence-aware and auditable, and each has its own page with definitions, use cases and boundaries.
Trusted Data Space
Data source, permission, version, authorisation, audit and data sovereignty.
Explore Module 02Open Model Layer
Clear distinction between open-source, open-weight and source-available models — multi-model and licence-aware.
Explore Module 03Deployment & Integration
APIs, private and hybrid deployment, identity and enterprise system integration.
Explore Module 04AI Agents & Automation
Agent orchestration, human oversight and governed workflow execution.
Explore Module 05Trust, Identity & Audit
Trusted identity, action authorisation, model and data provenance, and audit.
Explore Module 06AI Transaction Readiness
Interfaces and architecture prepared for future AI-to-AI and machine-to-machine service settlement.
ExploreTrusted by design. Open by design.
Trusted AI
Data sources, versions, permissions and model provenance are verifiable and auditable — the foundation for trusted retrieval, reasoning, automation and physical AI.
Explore Trusted AIOpen Source AI
Selected open-source and open-weight models, clearly distinguished from source-available systems, with investment concentrated on deployment, integration, governance and support.
Explore Open Source AIProvenance, identity, permission, audit
One trust model for data, models, agents and devices.
- 1
Data provenance
Where data came from, when, which version, and under what licence.
- 2
Identity
Which person, agent, model or device is acting — verified, not assumed.
- 3
Permission
What that identity is authorised to read, decide or execute.
- 4
Audit
A tamper-evident record of inputs, decisions, actions and outcomes.
How the infrastructure is built
Multi-model by design
No structural dependency on a single model provider; models and agents are evaluated before production use.
Deploy anywhere
Multi-cloud, private and hybrid where commercially and technically feasible, with clear separation of customer, operational and third-party data.
Enterprise-grade
Identity, permissioning, observability and logging as first-class features, not optional add-ons.
Licence-aware
A component inventory and model licence register underpin every deployment.
API-first integration
Documented, standardised interfaces to legacy and modern enterprise systems.
Human oversight
Escalation and review where full autonomy is inappropriate or unsafe.
Adopt without assembling the whole stack
One Australian partner across model evaluation, integration, hosting, governance and support.
A structured path into Australia
A route for suitable open AI and hardware into Australian enterprise and industry environments.
Local innovation, global reach
Local capability combined with international distribution and ecosystem relationships.
AI Infrastructure — common questions
What is Trusted AI?
Trusted AI is AI whose data sources, model versions, permissions and actions can be verified, traced and audited. At DNY it is delivered through a Trusted Data Space and verifiable infrastructure rather than through claims of accuracy.
What is a Trusted Data Space?
A Trusted Data Space is a governed environment where data is shared under recorded provenance, versions, licences and permissions, so organisations can collaborate on data without giving up control of it.
Does DNY use blockchain?
Hashing, digital signatures, trusted timestamps and distributed ledgers are technology options for verification where they add value. They are tools inside the trust layer, not the identity of the platform.
What is the difference between open-source, open-weight and source-available AI?
Open-source AI grants the freedom to use, study, modify and share, including the preferred form for modification. Open-weight models publish weights but may restrict terms, data or modification. Source-available systems can be viewed or used only under specific conditions that may limit commercial use.
Is open-source AI always cheaper or safer?
No. DNY does not claim that open models are free of licensing or IP risk, or always cheaper or safer than proprietary ones. Every model is evaluated and licence-checked before production use.
Is DNY tied to one model or cloud provider?
No. The infrastructure is multi-model, multi-cloud and vendor-neutral by design, to avoid structural dependency on a single model, cloud or hardware supplier.
What is an AI agent?
An AI agent is software that uses an AI model to plan and carry out multi-step tasks — calling tools, systems or devices — rather than only answering a single prompt.
How does DNY govern AI agents?
Agents run under defined identities and permissions, with human oversight and escalation for decisions where full autonomy is inappropriate, and with their actions recorded for audit.