AI behaves differently from traditional software. It learns, changes and responds in probabilistic ways. KJR’s Testing AI service applies modern evaluation techniques to ensure AI systems function safely, reliably and consistently throughout their lifecycle.
Testing AI
Evaluate AI behaviour, reliability, accuracy and safety
using modern testing methods that ensure dependable performance over time.
Prove your AI works - and keeps workingusing modern testing methods that ensure dependable performance over time.
Business challenges this service solves
Organisations worry about unpredictability, hallucinations, performance issues, drift, and fairness concerns. Traditional testing methods don’t address these risks. Without rigorous evaluation, businesses face operational, regulatory and reputational exposure.
KJR’s approach
We combine quality engineering discipline with AI-specific testing.
This includes scenario-based evaluation, behavioural analysis, safety testing, data quality checks, data governance assessments and model evaluation.
We test not just the model, but the entire AI workflow.
What we deliver
- Model performance evaluation
- Hallucination and safety testing
- Bias and fairness analysis
- Drift monitoring frameworks
- Human-in-the-loop design
- Practical governance processes & controls
- Model drift management framework
Customer impact
Organisations gain confidence that their AI behaves as intended. They reduce risk before deployment, maintain reliability over time, and demonstrate due diligence to stakeholders and regulators.
Featured case examples
Age Assurance Technology Trial (Australian Government)
Independent testing and evaluation of AI-based age assurance technologies
Water Authority
End-to-end testing of AI-driven chatbot behaviour, including identity verification, response accuracy and fallback handling
Large Victorian Water Utility
Identification and mitigation of model drift and data risks in large-scale public sector AI platforms
Experience. Execution. Excellence.
Backed by the VDML Methodology
VDML (Validation Driven Machine Learning) is KJR’s practical framework for building reliable, responsible AI. It gives organisations a structured way to train, validate and refine Machine Learning models with confidence.
By applying strong principles of risk management, governance, compliance and performance assurance, VDML supports safer, more predictable AI outcomes across the entire model lifecycle.
Why KJR
KJR has one of Australia’s strongest reputations in software testing and assurance. We apply that expertise to AI, ensuring systems are dependable, safe and trustworthy.
Test Your AI. Before It Puts Your Organisation to the Test.
Ensure reliability, safety and governance readiness with KJR’s AI assurance experts.
Request a consultation today using this form
or contact your local KJR General Manager.
Strengthen your AI strategy from every angle





