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Reference architectures for AI governance and assurance, AWS, Azure, Google Cloud, Salesforce, Dynamics 365, HubSpot and integration platforms, plus operational resilience and compliance patterns for APRA CPS 230, each with design decisions and trade-offs, security controls, failure modes and recovery targets.
Every architecture has a diagram, a numbered flow, design decisions, security mapping and failure modes.
AI governance and assurance · Operating model · control framework
How an organisation governs every kind of AI: leadership sets direction, an AI register and risk tiers decide how much review each system needs, an approval workflow gates release, platform guardrails enforce policy and assurance closes the loop with evidence.
AI governance and assurance · LLM guardrails · policy engine
A layered guardrail pattern around an LLM application: authenticate and screen the request, redact personal data, retrieve only what the user may see, call the model, then validate grounding and policy on the way out, with every step logged for audit.
AI governance and assurance · AI agents · safety controls
How to let an AI agent act without letting it do harm: a permission broker issues narrow, short-lived tool access, risky code runs in a sandbox, high-impact actions wait for human approval, budgets cap spend and a kill switch stops everything.
AI governance and assurance · ML · model risk · MLOps
A governed lifecycle for scoring and prediction models: reproducible training from a feature store, independent validation including fairness and explainability, a registry with approval status, controlled deployment, drift monitoring and champion and challenger comparison.
AI governance and assurance · Automated decisioning · human review
A decisioning pattern for decisions that affect people: rules and model scores combine in a versioned decision service, every outcome carries reasons, uncertain or adverse cases go to a trained reviewer and affected people have a clear route to challenge.
AI governance and assurance · Evaluation · red-teaming · CI
A pipeline that turns testing into a release gate: golden sets and adversarial suites run in CI against every change, scores are compared with thresholds by risk tier, failures block promotion and results become evidence.
AI governance and assurance · Observability · incident response
How to see what AI systems are actually doing and respond when they misbehave: end-to-end tracing, quality and safety scoring on sampled traffic, drift and cost detection, alerting tied to runbooks and post-incident learning that feeds testing.
AI governance and assurance · Data governance · privacy · lineage
How data is governed across the AI lifecycle: sources are classified and assessed for lawful use, consent and purpose are enforced, lineage tracks data into training sets, indexes and prompts, and retention and deletion apply to every derived copy.
AI governance and assurance · AI governance · LLMOps
The operating system for AI in an agency or enterprise: versioned models and prompts, automated evaluations and red-teaming as release gates, responsible AI approval with a risk register, and production monitoring of quality, drift, safety and cost.
Cloud platforms · AWS
The default for marketing sites, documentation and public information: a private S3 origin behind CloudFront with WAF, managed TLS and a pipeline that deploys with short-lived credentials.
Cloud platforms · AWS
A scale-to-zero API for web and mobile apps. Cognito authenticates, API Gateway enforces, Lambda runs the business logic, DynamoDB stores state and SQS or EventBridge decouple the slow work.
Cloud platforms · AWS
The workhorse for line-of-business web apps: public load balancer, containers across three Availability Zones, a private Aurora PostgreSQL cluster, ElastiCache for sessions and S3 for files.
Cloud platforms · Azure
The Azure equivalent of the three-tier pattern: Front Door with WAF, Container Apps or App Service on a private network, Azure SQL, Entra ID for identity and Key Vault for secrets.
Cloud platforms · AWS and Azure
The foundation every other pattern sits on: separate accounts or subscriptions for blast-radius control, preventive guardrails, central identity, central logging and a security account that workloads cannot switch off.
Cloud platforms · AWS and Azure
A delivery pipeline with no long-lived credentials: pull requests plan, merges apply, images are scanned and signed, and releases shift traffic gradually with automatic rollback.
Cloud platforms · AWS and Microsoft
A governed analytics platform: raw, curated and consumption layers on object storage, a catalogue with column-level access control and a semantic layer that business users can trust.
AI, LLM and real-time · AWS and Azure AI
A grounded question-answering system for internal knowledge: governed ingestion, hybrid retrieval with permissions, a guarded model call, citations, an audit log and a repeatable evaluation harness.
AI, LLM and real-time · AWS and Azure AI
An agent that can do things, not just answer: a bounded planner, a registry of narrowly scoped tools, policy checks outside the model, human approval for consequential actions and a full action ledger.
Cloud platforms · AWS and Azure
Choose recovery capability by business impact, not by habit. Three patterns with honest RTO and RPO, a cross-Region data path, an immutable backup vault and a failover that is rehearsed rather than hoped for.
Cloud platforms · AWS and Azure
One way to see every workload: OpenTelemetry instrumentation, central storage per signal, SLO-based alerting that wakes people only for user impact, and runbooks linked from every alert.
AI, LLM and real-time · WebRTC · LiveKit
A WebRTC platform for mobile apps built on the LiveKit SFU: token-based access, UDP and TURN/TLS connectivity, server-side recording to S3, webhooks, ingress for streams and scaling across nodes and regions.
AI, LLM and real-time · WebRTC · Amazon Chime SDK
A managed real-time platform on AWS: a Meetings API backend, mobile and web clients, media regions close to users, SIP media applications for phone calls and media pipelines for recording, all driven by Lambda and EventBridge.
AI, LLM and real-time · Google Cloud
A private, governed Gemini and Model Garden inference platform: Cloud Armor at the edge, Cloud Run for the application, Vertex AI over Private Service Connect, Pub/Sub for async jobs and BigQuery for audit and cost analytics.
AI, LLM and real-time · Azure
A governed Azure OpenAI platform: Front Door and API Management as the AI gateway, private endpoints, Entra ID managed identities, AI Search for retrieval, Content Safety, Cosmos DB for conversation state and Monitor for cost and quality.
AI, LLM and real-time · AI platform
A reusable platform, not a single bot: channels, an agent runtime, a model gateway, retrieval, a tool registry with policy, a durable workflow engine, human approvals, CRM and ERP connectors, evaluation and cost control.
AI, LLM and real-time · AI gateway · multi-cloud
A central AI gateway that every agency application calls instead of a model provider. It authenticates the caller, applies policy and PII redaction, routes each request to an approved Australian-region model, enforces budgets and writes a tamper-evident audit record.
AI, LLM and real-time · AWS · Kubernetes · vLLM
A private inference service running open-weight models with vLLM on EKS GPU nodes: queue-aware autoscaling, a governed model registry, weights loaded from encrypted S3 over a gateway endpoint, and a VPC with no route to the internet.
AI, LLM and real-time · Agentic AI · MCP
A platform for agents that act in enterprise systems: a supervisor and specialist agents, an MCP gateway that holds every tool credential, a policy engine deciding each call, human approval for consequential steps, continuous evaluation and red-teaming, and a complete audit trail.
AI, LLM and real-time · RAG · Government records
An assistant that answers staff questions from agency records. Retrieval enforces each user's access and classification before text reaches a model, answers carry citations to the authoritative record, and every interaction is logged so it can be managed under the State Records Act and produced under FOI.
AI, LLM and real-time · AWS · chatbot · guardrails
A customer-facing chatbot with flow control and guardrails kept apart. A deterministic engine owns intents, slots, validation and retries. A catalog of controls across six layers (input, context, model, tool and action, output, human oversight) screens every message in and every reply out, and a small Bedrock model is called only between questions, all on pay-per-use serverless services.
Risk, resilience and compliance · AWS · CPS 230 · Resilience
A technical design that traces each critical operation to the services behind it, sets recovery capability from tolerance levels, replicates to a second region, and proves the result through game days and continuous service-level monitoring.
Risk, resilience and compliance · Multi-cloud · Exit planning · CPS 230
How to depend on cloud, SaaS and AI providers without being trapped by them: a provider register tied to critical operations, a portability layer you own, tested data export and a second-provider path for the services that matter most.
Risk, resilience and compliance · AWS · Azure · Continuous compliance
Turn point-in-time audits into continuous assurance. Cloud configuration, findings and policy results flow into one evidence store, are mapped to named controls across several standards, and reach owners and auditors through dashboards and read-only access.
Risk, resilience and compliance · Incident response · Regulatory notification
A detection and response design that starts the right notification clocks from one incident record: materiality assessment against tolerance levels, pre-drafted regulator forms, approvals, evidence capture and a post-incident review that feeds back into the risk register.
Risk, resilience and compliance · API security · Tokenisation · Zero trust
A controlled edge for partners, fintech suppliers and SaaS platforms that need regulated data. Each partner is authenticated, authorised per scope, rate limited and logged, sensitive fields are tokenised, and everything is encrypted with keys you hold.
CRM and business systems · Salesforce
API-led connectivity between Salesforce and a finance or ERP system: system APIs wrap the ERP, process APIs hold the business rules, Salesforce calls one stable contract, and events keep both sides in step.
CRM and business systems · Microsoft
A Microsoft-centric business platform: Dynamics 365 apps on Dataverse, Power Apps and Power Automate for tailored processes, governed environments and DLP, integrated with Entra ID, Microsoft 365 and Azure.
CRM and business systems · HubSpot
A lean marketing and sales stack: consent-aware forms and tracking on the site, HubSpot as the system of engagement, and a warehouse for reporting that does not live inside the CRM.
CRM and business systems · Xero and MYOB
Quote, invoice and payment data moving safely between a CRM and Xero or MYOB: OAuth, idempotent writes, GST-correct line items, reconciliation and clear ownership of every record.
CRM and business systems · Data platform
One governed customer profile built from the systems you already have: identity resolution, consent-aware activation and privacy controls, with a clear line between what is analysed and what is acted on.
CRM and business systems · Zendesk and ServiceNow
Zendesk or ServiceNow as the system of record for tickets, a chatbot that answers from approved knowledge with citations, and a clean hand-over to a person with full context when it cannot.
CRM and business systems · Entra ID and Okta
One identity provider for staff, partners and customers: SAML and OIDC federation, SCIM provisioning, Conditional Access, role mapping and a leaver process that really removes access.
CRM and business systems · Microsoft 365
A Microsoft 365 tenant for councils and small organisations that is safe before AI arrives: Entra ID with Conditional Access, Intune-managed devices, Purview labels and DLP, oversharing cleaned up, and a backup copy outside the tenant.
Integration and multi-application · AWS and Azure
A small number of governed APIs and an event backbone in front of many systems, so each application integrates once with the hub instead of with every other application.
Integration and multi-application · Web, mobile and back office
Web, mobile and staff back-office experiences on one API platform. A backend-for-frontend per channel and a micro-frontend portal let several applications look like one product without becoming one codebase.
Integration and multi-application · Master data
Agree who owns each core entity (person, organisation, product, cost centre), publish the golden record to the systems that need it and reconcile the differences before they reach a report or an auditor.
Integration and multi-application · Modernisation
Replace a legacy system one capability at a time. A routing facade sends each request to the old or new implementation, anti-corruption layers protect the new design and RPA covers the gaps until APIs exist.
Integration and multi-application · Partners
Secure, auditable exchange of orders, invoices and reports with partners that still send files: managed SFTP, validation, translation, acknowledgements and monitoring that proves nothing was lost.
Industry patterns · State government
A public channel for an application, a payment and a case, with the decision kept with an officer and a full audit trail, hosted in Australian regions.
Industry patterns · Local government
Residents lodge requests on web or mobile, crews work offline in the field and the council system of record stays authoritative, with AI used only to triage and summarise.
Industry patterns · Health
Structured digital referrals into a clinical service, with consent, secure messaging and clinical system integration, hosted in Australia with strong audit.
Industry patterns · Education
One front door for enrolment, support requests and communications, integrated with the student information system and learning platform, with safeguarding built in.
Industry patterns · Not-for-profit
Case notes, referrals and outcomes tracked securely by small teams, with funder reporting generated from the same data and strict access to sensitive client information.
Industry patterns · Professional services
Clients upload documents, the platform classifies and extracts the key data, and a professional reviews the result before it reaches the practice system.
Industry patterns · Retail and distribution
Orders from web, marketplace and in-store channels flow to one order management layer, with inventory, fulfilment and accounting kept in step and a clear view of stock.
Industry patterns · Utilities and field services
Inspectors capture evidence on mobile devices, offline if needed. Findings flow to the asset register and generate work orders with a complete, timestamped evidence trail.
Industry patterns · Aged care and community services
Client records, rosters, care plans and incident reporting connected on a Microsoft stack, with consent, family access and regulatory reporting handled deliberately.
Use ap-southeast-2 (Sydney) on AWS and Australia East on Azure as the primary location, with ap-southeast-4 (Melbourne) or Australia Southeast for recovery. Confirm each service is available in the second region before you design a failover.
Global edge caching (CloudFront, Front Door), identity metadata, support access and SaaS sub-processors can involve data outside Australia. Review them against APP 8 and your agency policy, and keep confidential content off global caches.
Check where inference runs for the exact model and endpoint, since cross-region inference options exist. Choose in-region endpoints when residency matters, and verify the provider’s data-use terms.
Our guide to Australian data residency for SA Government ICT goes deeper on questions buyers ask in tenders. For backup and recovery objectives, see backup and disaster recovery for SA Government ICT.
These are general reference architectures, not client case studies, and nothing here is a statement of certification or IRAP assessment.
No. They show how to design and evidence the technology controls behind critical operations, service provider management, testing and incident notification. Compliance is determined by the regulated entity against the current standard, with its own advisers and assessors. This is general guidance, not legal advice, and EITSAA does not assess or certify compliance.
They are educational patterns for AWS, Azure, CRM platforms and integration, plus resilience and compliance patterns. Each one covers the services used, design decisions with trade-offs, security mapping and failure modes so architects and buyers can discuss options in plain English.
No. They are general reference patterns, not descriptions of a named client engagement, and nothing here is a statement of certification or IRAP assessment. Adapt them to your risk appetite, residency rules and existing estate.
Yes as a starting conversation. Real delivery still needs discovery: current systems, RTO/RPO, identity, data classification and cost constraints. Bring what you already have and the outcome you need.
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Bring the systems you already have and the outcome you need. We will walk the architecture with you. The first conversation is free.