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Razor Labs Launches DataMind AI™ 4.5, a Major Leap Forward in Predictive Maintenance and Fleet Management for Mining Operations
  • Israel - English


News provided by

Razor Labs

11 Dec, 2025, 05:00 CST

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SYDNEY, Dec. 11, 2025 /PRNewswire/ -- Razor Labs (TASE:RZR) announces the launch of DataMind AI™ 4.5, a powerful upgrade to its predictive maintenance platform designed for mobile fleet management and fixed assets across mining operations. Built through continuous collaboration with dozens of global mining sites, Version 4.5 delivers clearer diagnostics, faster insights, and stronger visibility for maintenance and reliability teams.

"Version 4.5 was shaped together with dozens of mining sites operating a wide variety of mobile fleets and fixed assets," said Raz Roditti, CEO. "It delivers exactly what maintenance teams need: clearer visibility, faster diagnostics, and stronger predictive maintenance capabilities."

Advanced Diagnostics Environment for Mining

The new version provides engineers with a unified view of asset health, combining fault diagnostics derived from sensor health data with maintenance information. By bringing everything together, teams can pinpoint root causes faster and take action sooner.

Full Raw Sensor Data Access for True Engineering Transparency

Version 4.5 now provides full access to raw vibration, oil, temperature, and pressure data, along with advanced envelope RMS and full-spectrum insights, including harmonics and sidebands. This enriched health data foundation supports deeper, more accurate fault diagnostics and asset health assessments for reliability engineers.

For reliability engineers, this means deeper condition monitoring, more accurate diagnostics, improved failure prediction, and higher confidence for maintenance decisions.

This makes DataMind AI™ one of the most advanced predictive maintenance and fleet monitoring platforms in the mining industry.

Faster Investigations Across the Entire Mine

With upgraded thresholds, flexible alarm filtering, enhanced work-order visibility, and stronger links to investigation workflows, DataMind AI™ 4.5 improves day-to-day monitoring and accelerates issue resolution. Improved sensor search, timestamp comparison, and smoother navigation help teams understand events and validate equipment issues in minutes, speeding up investigations and reducing unplanned downtime across both mobile fleets and fixed plant assets.

Together, these improvements deliver a highly precise and configurable monitoring and alarm system among predictive maintenance solutions.

Fully Connected Predictive Maintenance Ecosystem

DataMind AI™ 4.5 combines raw sensor intelligence, full diagnostics, advanced alarm management, fault aggregation, AI insights, and maintenance history into one seamless experience.

These improvements make DataMind AI™ a predictive maintenance platform that delivers deep insights, transparency, and cross-asset connectivity across mobile fleets and fixed assets across the industry.

"We focused on the improvements that create the greatest impact in the field," added Assaf Eden, VP Product. "DataMind AI 4.5 gives reliability engineers a simpler, more powerful way to manage the vast amount of sensor data in reliability, delivering clearer asset health visibility across all mining equipment. This enables fast work from investigation to maintenance actions, ensuring issues are resolved sooner, and operations stay productive."

DataMind AI™ 4.5 is now available for all customers globally, supporting predictive maintenance for mobile fleets and fixed industrial assets.

To request a demo, visit www.razor-labs.com.

About Razor Labs

Razor Labs (TASE: RZR) is a global leader in mining technology, specializing in predictive maintenance solutions powered by advanced AI Sensor Fusion for Mobile Fleet, Fixed Assets, and Visual AI. With operations across Australia, South Africa, the United States, and Colombia, Razor Labs enables industrial teams to elevate reliability, efficiency, and safety.

Follow us on LinkedIn. Subscribe to our YouTube Channel.

Media inquiries: Ms. Liel Anisenko at [email protected] or +972 (03) 561-0901

SOURCE Razor Labs

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