AI and automation that the public service can trust
We help Canberra government agencies and businesses implement AI and automation responsibly. From robotic process automation that eliminates manual drudgery to AI-powered decision support that improves policy outcomes — built with transparency, safety and accountability at the core.
Robotic process automation for the APS
The Australian Public Service runs on process — approvals, data entry, reconciliation, correspondence management and compliance checks. Many of these processes involve staff manually copying data between systems, checking records against spreadsheets, or generating routine documents from templates.
Robotic process automation (RPA) uses software robots to perform these repetitive tasks faster and more accurately than humans. We identify high-volume, rules-based processes within your agency, build automation workflows, and deploy them with appropriate oversight and exception handling.
Our RPA implementations are not black boxes. Every automated decision is logged, every exception is routed to a human operator, and every workflow is documented so that your team understands exactly what the automation does. This transparency is essential for maintaining accountability in a government context where decisions affect citizens' lives.
AI strategy and readiness assessments
Not every problem needs artificial intelligence, and not every organisation is ready to adopt it. Before investing in AI, Canberra agencies need to assess their data maturity, technical infrastructure, workforce capability and governance frameworks.
Digital Nachos provides AI readiness assessments that evaluate your organisation across these dimensions and produce a practical roadmap. We identify the use cases where AI will deliver the greatest value — and equally importantly, the use cases where simpler solutions would be more appropriate.
Our strategy work is grounded in the Australian Government's AI Ethics Framework and the National AI Centre's guidance. We help agencies navigate the emerging policy landscape around AI in government, including procurement considerations, bias mitigation requirements and the transparency obligations that accompany automated decision-making under the Administrative Decisions (Judicial Review) Act.
Responsible AI and algorithmic transparency
When government agencies deploy AI systems that influence decisions about citizens — eligibility assessments, risk scoring, resource allocation, compliance targeting — the stakes are high. The Robodebt Royal Commission underscored the consequences of automated decision-making implemented without adequate safeguards.
We build AI systems with explainability, fairness and human oversight as foundational requirements. Every model we deploy includes documentation of its training data, known limitations, performance metrics across demographic groups, and the conditions under which it should and should not be used.
Our approach to responsible AI includes bias testing before deployment, ongoing monitoring for model drift, clear escalation pathways for contested decisions, and regular human review of automated outputs. We help agencies develop their own responsible AI governance frameworks so that these practices endure beyond any individual project.
Intelligent document processing and knowledge management
Government agencies process enormous volumes of documents — ministerial correspondence, freedom of information requests, grant applications, compliance submissions and policy papers. Much of the time spent on these documents involves reading, classifying, extracting key information and routing to the right team.
We build intelligent document processing pipelines that use natural language processing (NLP) and large language models to automate classification, extraction and summarisation. A freedom of information request can be automatically triaged by subject matter. A grant application can have its key eligibility criteria extracted and pre-assessed against program rules.
These systems augment human judgment rather than replacing it. The AI handles the initial triage and extraction, presenting results to a human officer who makes the final decision. This approach reduces processing times from days to hours while maintaining the quality and accountability that government work demands.
Workflow automation and system integration
AI and automation deliver the most value when they are woven into existing workflows rather than bolted on as separate tools. We integrate automation capabilities into the systems your team already uses — whether that is ServiceNow, Microsoft 365, SharePoint or custom-built case management platforms.
Our integration approach uses event-driven architectures that trigger automated actions based on real events in your systems. When a new application is submitted, the automation pipeline begins processing immediately. When a compliance threshold is breached, an alert is raised and an investigation workflow is initiated. When a reporting deadline approaches, data is automatically gathered and a draft report is generated.
We also help agencies build internal automation capability through low-code platforms like Power Automate, enabling business teams to create and modify simple automations without relying on developers for every change. This distributed approach scales automation across the organisation without creating bottlenecks.
AI safety and ongoing model governance
Deploying an AI model is not the end of the project — it is the beginning of an ongoing governance responsibility. Models can degrade over time as the data they were trained on becomes stale. User behaviour changes. Policy settings shift. Without active monitoring, a model that performed well at launch can produce increasingly unreliable outputs.
We implement model monitoring frameworks that track prediction accuracy, data drift, fairness metrics and system performance in production. Automated alerts notify your team when any metric falls outside acceptable thresholds, triggering a review and potential retraining cycle.
Our governance frameworks include model cards, risk registers, incident response procedures and scheduled review cadences — all aligned with the Australian Government's AI Ethics Principles and the evolving regulatory landscape. This ensures your AI investments remain trustworthy, effective and compliant as the technology and policy environment continues to evolve.
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