Trusted AI: trust is the foundation, not a feature
Access to a model is not the same as safe deployment. DNY builds a Trusted Data Space and verifiable infrastructure so that data sources, versions, permissions and model provenance are verifiable, traceable and auditable — the base for trusted retrieval, reasoning, industry automation and physical AI.
A verifiable record for every input
The platform applies unified trust governance across data collection, standards mapping, product records, testing and certification, project records, supply-chain information and the AI call process itself.
How it works
DNY uses a hybrid architecture: original business data, documents and large model materials are stored in secure databases or cloud environments that meet privacy and business requirements; for critical data, a unique hash, version, timestamp, source, authorisation status and verification information are recorded — enabling integrity checks and long-term traceability.
Blockchain, digital signatures, hashing, trusted timestamps, identity, permissioning, audit logs and distributed evidence are technology options for verification — not the platform’s external identity.
Trusted objectives
- Verify the creator, source and creation time of data
- Confirm version status and modification history
- Check access and authorisation rights
- Provide transparent, traceable, verifiable and stable data
- Underpin trusted AI reasoning, retrieval-augmented generation and agent execution
What we make verifiable first
Products & versions
Technical parameters, product versions and update records for building products and materials.
Testing & certification
Test reports, certification documents and their authenticity and validity information.
Standards
Building standards, standard versions and update records — with Australian-to-international mapping.
Identity & provenance
Supplier, manufacturer and professional body identity, and BIM / modular / 3D-print file versions.
Project & supply chain
Project data, construction stages, acceptance milestones, and supply-chain nodes and logistics.
AI call provenance
Sources, citations and versions behind AI outputs, plus data authorisation, change, sharing and access behaviour.
Governance is part of the product
Model licence register
Every model is classified and its licence recorded — commercial-use restrictions, attribution, redistribution, provenance and prohibited-use conditions — before any commercial deployment.
Standards mapping layer
An Australian Standards Mapping layer structurally maps products, technologies and standards from different countries to Australian-applicable requirements, preserving source, version and update records.
Data rights & authorisation
Contracts define ownership, permitted processing, retention, model-training permissions, cross-border transfer, sub-processors and deletion — customer data is not treated as a platform asset simply because it is processed.
Responsible & auditable
Human oversight, escalation and full audit logging make the platform consistent with Australian guidance on safe, responsible and well-governed AI adoption.
Outputs you can trace back to their source
On top of the trusted data space, open standards and product libraries, AI outputs are designed to trace back to verified data, standards and authorisation.
Intelligent selection
Recommend products by project requirements, performance parameters, budget and standards.
Standards matching
Assist matching of products and technical solutions to Australian-applicable standards, with risk prompts.
Structured cost analysis
Combine materials, logistics, schedule and project data into structured cost estimates.
Intelligent procurement
Generate procurement suggestions from project plan, budget, inventory and supply conditions.
Compliance assist
Provide assisted review against trusted standards and certification data, keeping citations.
Supply-chain agent
Product lookup, supplier matching, pricing, comparison, delivery analysis and risk prompts.
The same trust model governs devices
When AI drives drones and robots, the same four checks apply to every action.
- 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.
Trusted AI — 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.