Booth Q31 | 27-29, ICC Sydney
Meet our team and discover our award-winning DataMind AI™
predictive maintenance solution for Fixed & Mobile assets

Co-Founder & CEO

Co-Founder & CTO

Chief Business Officer

VP Sales

Director of Growth Marketing
Explore the latest features of DataMind AI
with hands-on demos and real case studies from global mining leaders.

Monitor crushers, mills, conveyors, pumps, fans, compressors and more with AI-powered predictive maintenance.

Detect failures across engines, hydraulics, tires, electrical systems, contamination and more - before they impact production.

AI-powered vision for conveyors, crushers and remote mining operations.
Book a demo session with our team to see how DataMind AI™
can help your site reduce downtime and improve reliability
IMARC 2024 Recap










“By providing early warnings and actionable insights, we aim to prevent equipment failures before they occur, significantly reducing unplanned downtime and maintenance costs. DataMind AI™ also helps us maintain a safer working environment by minimizing the need for manual inspections in hazardous areas. ”
“The major shift is from unplanned to planned maintenance. Being able to take those unplanned maintenance events out of the picture, in some cases, you might be able to achieve that 100% or to reduce them. You save both the cost of lost revenue, which has a huge impact on your NPV, as well as the cost, the avoidance of component costs as well.”
“We were amazed when DataMind AI not only indicated a bearing failure in one of our crushers, but that it was caused by the use of incompatible oil. Having switched to the correct type of oil, the bearing failures stopped altogether.”
“DataMind AI has been a valuable tool for our operation. It has helped us minimize unplanned downtime, boost the reliability of our assets, increase throughput, and reduce the need for costly parts replacements.”
“Out of 20 pumps on site, 6 were scheduled for replacement over the past six months.
Thanks to DataMind AI, none were replaced. We avoided downtime and saved $500,000 in replacement costs only.”

