Major platform release expands predictive maintenance beyond fault detection, helping mining companies turn AI insights into faster maintenance decisions and improved asset reliability
SYDNEY, July 28, 2026 /PRNewswire/ — Razor Labs (TASE: RZR), a global leader in AI-powered predictive maintenance for mining, today announced the launch of DataMind AI™ 5.0, a major evolution of its predictive maintenance platform that expands predictive maintenance beyond early fault detection to support the complete maintenance decision-making process.
As mining operations become increasingly digital and equipment fleets grow in size and complexity, maintenance teams face mounting pressure to improve reliability while reducing unplanned downtime and maintenance costs. While artificial intelligence has transformed the ability to detect developing equipment failures, identifying a fault is only the beginning. Engineers must still investigate the issue, determine the appropriate response, coordinate maintenance activities, execute repairs, and verify that equipment has safely returned to operation.
The new version bridges that gap by connecting AI-powered insights with the operational workflows that maintenance and reliability teams rely on every day. Powered by Razor Labs’ proprietary AI Sensor Fusion™ technology, the platform delivers a more connected approach to equipment health management, helping organizations move seamlessly from early detection through investigation, maintenance execution, and verification across both mobile fleets and fixed assets.
“Predictive maintenance doesn’t end when AI detects a fault – that’s where the real work begins,” said Raz Roditti, CEO of Razor Labs. “DataMind AI™ 5.0 represents an important milestone in our vision for AI-powered predictive maintenance in mining. Mining companies need more than earlier detection – they need technology that helps maintenance teams make faster decisions, collaborate more effectively, and confidently turn insights into action. This release strengthens that connection, enabling organizations to maximize the value of predictive maintenance across their operations.”
The release brings together AI-powered diagnostics, engineering investigation, maintenance collaboration, and complete fault lifecycle management within a unified environment designed around the way maintenance organizations operate. By reducing the disconnect between identifying potential failures and resolving them, the platform helps improve maintenance efficiency, operational visibility, and decision-making at scale.
“Maintenance teams don’t need more alerts – they need greater clarity, context, and better workflows,” said Assaf Eden, VP Product at Razor Labs. “Version 5.0 was designed around those day-to-day realities, helping teams investigate issues faster, collaborate more effectively, and move from detection to resolution with greater confidence.”
This release reflects Razor Labs’ continued investment in advancing AI-powered predictive maintenance for mining and reinforces the company’s commitment to helping mining organizations improve equipment reliability, reduce operational risk, and transform maintenance through practical, scalable AI solutions.
Version 5.0 is now available to Razor Labs customers worldwide.
About Razor Labs
Razor Labs (TASE: RZR) is a global leader in AI-powered predictive maintenance for mining. Through its proprietary AI Sensor Fusion™ technology, the company’s DataMind AI™ platform continuously analyses operational, condition monitoring, and maintenance data to identify developing equipment failures before they impact production.
Supporting both mobile fleets and fixed assets, Razor Labs helps mining organizations reduce unplanned downtime, improve equipment reliability, and optimise maintenance decision-making. With operations across Australia, South Africa, the United States, Colombia, and Israel, the company partners with leading mining organizations worldwide to transform maintenance through artificial intelligence.
Learn more: www.razor-labs.com
Follow Razor Labs on LinkedIn: https://www.linkedin.com/company/razor-technologies-inc
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Razor Labs
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