AUS AI Technical Standards

Silverpond's Highlighter platform is in alignment with the Australian Government's AI Technical Standards, positioning it as the Enterprise Perception System for government agencies seeking compliant AI deployment.

Comprehensive Lifecycle Management

Highlighter operates as the world's only Enterprise Perception System (EPS), providing a centralized platform that merges human expertise and AI capabilities to analyze data from various sources and take appropriate actions. This comprehensive approach directly supports the Australian Government's AI lifecycle requirements across all stages from discovery to retirement.

Whole of AI Lifecycle Compliance:

Statement 1 (Operational Model): Our Services Methodology encompasses complete ML solution delivery with clear definitions of success, accuracy expectations, and feedback mechanisms
Statement 3 (People Capabilities): Highlighter enables decentralized workflows empowering human and AI agents to collaborate, with comprehensive staff training and capability development through our SDK
Statement 4 (AI Auditing): The platform provides end-to-end auditability with comprehensive documentation across the AI system lifecycle, ensuring traceability of decisions from requirements through to operational impacts

Quality Management and Information Security Framework

Silverpond is committed to delivering high-quality solutions through our certified Information Security Management System (ISMS) grounded in ISO 27001 and alignment with ISO 42001. This approach directly addresses the Australian Government's requirements for:

Process-Oriented Compliance

Secure Software Development Lifecycle (SDLC) with comprehensive testing, formal bug tracking, and root cause analysis
Continuous monitoring, measurement, and evaluation through in-process metrics, code reviews, and post-deployment monitoring
Structured risk management principles applied to ensure reliability, availability, and integrity

Design and Human-Centered Approach

Statement 10 (Human-Centered Approach): Highlighter's Assessment subsystem enables data analysis tasks by both human experts and automated AI agents, ensuring human oversight and control mechanisms are embedded throughout. Our platform supports:
Human values integration through expert collaboration
Transparent AI interactions with clear provenance and context
Feedback mechanisms and human oversight controls
Inclusive design meeting accessibility standards

Data Management Excellence

Statements 13-19 (Data Lifecycle Management): Highlighter's Schema component tracks and organizes important data concepts through structured hierarchy, ensuring relevant information is accessible to AI and human agents alike. The platform addresses:

Data supply chain management with comprehensive traceability
Data quality assurance and validation processes
Bias management in datasets through diverse stakeholder engagement
Secure data orchestration and integration capabilities

Model Training and Evaluation

Statements 20-25 (Training) and 26-30 (Evaluation): Our Agent Development & Deployment subsystem provides tools for training and deploying both human and machine agents, with continuous performance monitoring through our Evaluation component. This supports:

Systematic model architecture planning and validation
Comprehensive testing strategies adapted for AI systems
Bias evaluation and mitigation throughout the training process
Continuous improvement frameworks with feedback loops

Production Deployment and Monitoring

Statements 31-39 (Integration, Deploy, Monitor): Highlighter's Actions component enables appropriate action execution by human experts or automated agents once decisions are made. The platform ensures:

Secure integration with existing government systems
Phased rollout capabilities with rollback mechanisms
Comprehensive monitoring across performance, safety, and compliance metrics
Real-time alerting and incident response processes

Maturity-Based Implementation

Highlighter supports an enterprise's journey through distinct maturity levels, from ad-hoc Level 0 operations to highly optimized Level 3 systems with quantitative decision-making and predictive insights. This structured approach aligns with the Standards' emphasis on:

Standardized workflows and taxonomies (Level 1)
Data-driven decision making with comparative analysis (Level 2)
Optimized, feedback-driven systems with dynamic protocols (Level 3)

Comprehensive Documentation and Compliance

All documents relating to establishment, design, and governance of AI implemented solutions are retained to comply with information management legislation, with clear source of truth for project details that everyone has signed off on. This directly supports the Standards' requirements for:

Version control practices across the development lifecycle
Audit trail maintenance and compliance monitoring
Transparent documentation for regulatory review
Decommissioning planning and impact analysis

Proven Service Delivery Methodology

Our machine learning services methodology includes Pre-engagement meetings, structured workshops, internal planning, roadmap development, agent development, and showcase presentations with staff training. This comprehensive approach ensures:

Clear success criteria definition and business case validation
Stakeholder engagement and requirement gathering
Iterative development with continuous evaluation
Knowledge transfer and capability building

Highlighter's comprehensive Enterprise Perception System framework, combined with Silverpond's ISO-certified quality management approach, provides government agencies with a proven platform that not only meets but exceeds the Australian Government's AI Technical Standards requirements. Our solution offers the transparency, accountability, and risk management capabilities essential for responsible AI deployment in government environments.