News
Across Melbourne, Canberra and Brisbane, our Collective came together to celebrate achievements, take on team challenges, recognise peers through the Kudos Awards, and strengthen the connections that make KJR unique.
KJR has been named the OpenText and NEXTGEN DevOps Partner of the Year for FY26, recognising our focus on customer outcomes, capability development and collaboration across the DevOps ecosystem.
KJR podcast episode 27 with special guest Beau Tydd from ACS explores why AI adoption depends on workforce capability, not just technology access.
KJR partnered with five Griffith University students through a Work Integrated Learning placement to build a real-time situational awareness system, integrating live DJI drone telemetry, AI object detection, and ATAK mapping software.
This article examines how one hospital AI implementation improved billing workflows while maintaining human oversight, traceability and explainability, highlighting why testing and quality engineering are essential for successful AI adoption.
KJR’s VIC General Manager, Dinuka Mallawaarachchi, discusses AI governance with ACS and explores why trust, validation and quality engineering are critical to building dependable AI systems. Read more.
A joint report by KJR and Age Verification Providers Association reveals that the challenge in Australia’s social media minimum age law is not technology, but inconsistent implementation and weak assurance practices across platforms.
This article explores how AI governance is being applied in practice through age verification systems in Australia, and why testing and QA are critical to building trust, compliance, and reliable AI at scale.
Applying AI and test automation in safety-critical rail systems requires strict governance, traceability, and deep domain expertise to ensure safety is never compromised.
AI governance is no longer just a compliance exercise, it is becoming a core testing responsibility. Drawing on insights from KJR’s Trusted AI podcast, this article explores how AI systems fail differently, why data quality and automation bias matter, and how emerging standards like ISO 42001 are reshaping testing, DevOps, and quality engineering practices.
As AI moves into real-world applications, traditional testing approaches fall short. This article explores how KJR’s Validation-Driven Machine Learning (VDML) methodology helps organisations test AI systems, reduce risk, and build trust through continuous validation, governance, and real-world assurance.
KJR is proud to be Great Place to Work® Certified™ and we ranked #15 in Australia’s Best Workplaces™ in Technology 2026, reflecting a culture built on trust, strong values, and empowered people. From software quality assurance to trusted AI adoption, we help organisations de-risk technology while delivering meaningful outcomes. Discover how our people, culture, and expertise drive long-term success.