With Y2K approaching, demand was high for technology and software testing. K.J.Ross and Associates was established in a garage on the Gold Coast by Kelvin J. Ross.
Steven Butler became Kelvin’s first hire and he’s still on board as a loyal employee and Principal Consultant up in the Brisbane office.
Y2K didn’t cause the world to implode – perhaps because KJR saved so many computer systems from crashing…!
SMARTCat was ‘on the prowl’ – proactive production monitoring tests for web applications at a time when most other offerings would do little more than ping the server.
We founded the Test Manager Forum – an annual event to celebrate and educate the software testing industry. TMF ran until 2015 under the new name Software Quality Forum.
After servicing Sydney clients since inception, we officially marked KJR territory on Sydney soil.
We set up permanent roots in Canberra to service our growing federal government clients.
This year marked the first release of a multi-year project wit the Department of Education and Training Queensland.
KJR founder, Kelvin Ross won the Achiever award for taking risks and making a difference within the Queensland ICT community.
Our industry benchmark report was released annually until 2014.
KJR became one of only two Test Labs in Australia to be able to certify medical software for conformance to NEHTA specifications.
KJR commenced it support for TourXOz and Black Dog Institute. The Yellow Jersey has appeared in 2013, 2015, 2017 and 2019.
The NDIS scheme was launched on a high-quality platform, on-time – thanks to KJR.
K.J.Ross & Associates re-branded to KJR.
Named in Australia’s Top 100 Coolest Companies to work for (and again in 2017 and 2018). Although we didn’t need an award to tell us that!
KJR took up a spot right next to the hoop at Qudos Bank Arena as a Sydney Kings sponsor.
Celebrated KJR’s 21st birthday! An immense achievement for a smaller technology-based firm.
And watched them take out the WNBL Championship (in 2019).
As a founding Platinum sponsor, KJR is making a focused effort to address the inherent bias that exists in the development of artificial intelligence and machine-learning algorithms.