The 5C Framework establishes a comprehensive governance structure that enables JurisTab to harness the transformative power of AI in legal research while maintaining the highest standards of ethics, security, privacy, and operational excellence. As a legal technology provider serving Australian legal professionals, we hold ourselves to the same rigorous standards our users expect in their practice.

This framework ensures our AI systems—including natural language search, JurisMap, JurisSummary, JurisLink, and DocuDive—operate transparently, accurately, and in compliance with Australian regulations and international best practices.

Framework Definition

WHY

To ensure all AI features deliver accurate legal insights while protecting users, their data, and maintaining the trust essential to legal practice.

WHAT

A governance framework covering 5 pillars: Compliance, Controls, Capability, Calibration, and Continuity for all AI systems.

WHEN

Applied throughout the AI lifecycle: from feature initiation, through development and deployment, to ongoing operations.

HOW

Through standardised risk assessments, the 5C Checklist, continuous monitoring, and regular governance reviews.

WHO

AI Head's implementation with oversight from leadership. All team members share responsibility for governance.

WHERE

All JurisTab products and services including JurisTab platform, DocuDive, and any future AI-powered features.

The Five Pillars

Adherence to Australia's AI Ethics Principles, Voluntary AI Safety Standard (10 Guardrails), and Guidance for AI Adoption in delivering legal research tools

COMPLIANCE

Australian AI Policy

Privacy Act 1988 compliance, Australian Privacy Principles (APPs), OAIC guidelines for GenAI; ensuring user queries and legal research remain confidential

Privacy by Design

Strict handling of user data across storage, processing, transmission, and retention; data minimisation; no training on user queries without explicit consent

Data Governance

Ensuring accuracy and currency of legislation, case law, and legal references; clear provenance and citation standards for all AI-generated insights

Legal Data Integrity

Alignment with legal profession expectations; appropriate disclaimers; ensuring AI assists rather than replaces professional legal judgment

Professional Standards

Legal, Privacy & Policy

Security integrated from inception through design, build, test and release; threat modelling; vulnerability assessments; penetration testing

Security by Design

Multiple security layers; network segmentation; access controls; encryption at rest (AES-256) and in transit (TLS 1.3); AWS security best practices

Defence in Depth

Prompt injection prevention; output filtering; content safety controls; model access restrictions; prevention of legal misinformation or hallucination

AI-Specific Guardrails

Input validation; output verification against source documents; citation accuracy checks; confidence scoring; human review thresholds

LLM Safety Controls

Role-based access control; API key management; rate limiting; audit trails for all system access; secure credential storage

Access Management

CONTROLS

Security & Guardrails

Microservices architecture; serverless compute; API Gateway; scalable infrastructure aligned with legal tech requirements

CAPABILITY

Platform Architecture

Embedding generation for legal documents; vector search; LLM integration; model versioning and rollback capabilities

AI/ML Pipeline

RESTful API standards; consistent data formats; service mesh requirements; event-driven architecture using SQS for async processing

Integration Standards

Legal document storage (S3); structured data (PostgreSQL/DynamoDB); search indices; data lineage tracking for all legal sources

Data Architecture

Consistent patterns across JurisMap, JurisSummary, JurisLink, JurisTree; shared component libraries; documentation requirements

Feature Standards

Architecture & Standards

Validation of AI outputs against authoritative legal sources; citation accuracy; case law reference verification; legislation currency checks

Legal Accuracy Testing

Model evaluation standards; benchmark definitions; relevance scoring; hallucination detection; bias assessment for legal outcomes

Evaluation Framework

Load testing; latency benchmarks for search and analysis features; throughput requirements; stress testing for concurrent users

Performance Testing

Comprehensive monitoring; CloudWatch integration; alerting thresholds; dashboards for system health and AI performance metrics

Observability

Acceptance criteria for AI features; go/no-go decision frameworks; release certification; accuracy thresholds before deployment

Quality Gates

CALIBRATION

Testing & Evaluation

High Availability (HA) architecture; Disaster Recovery (DR) procedures; defined RTO and RPO targets; multi-AZ deployment

CONTINUITY

Operational Excellence

Incident response procedures; escalation paths; post-incident reviews; communication protocols for service disruptions

Incident Management

Comprehensive audit logging; OpenTelemetry implementation; full traceability of user queries and AI responses; S3 log storage

Logging & Auditing

Log retention aligned with legal requirements; user data retention policies; secure deletion procedures; compliance with privacy obligations

Retention Policy

Analysis of user interactions; query patterns for feature enhancement; feedback loops; regular model updates based on legal source changes

Continuous Improvement

Operations & Resiliance