What happens when AI gets trained like a doctor—only for your mining equipment?

In this episode of Reliability 4.0 , we sit down with Michael Zolotov, Co-Founder and CTO of Razor Labs, to explore how his team is using AI sensor fusion to detect failures weeks before traditional systems sound the alarm. Michael shares how they built an “automated doctor” for fixed and mobile assets, and how it’s already helping clients like Glencore save millions.

We dig into:

🔸 Why most legacy AI models fail in mining—and what to do instead

🔸 How Razor Labs reduced failure detection time by 3–5 weeks

🔸 The two ROI stories that win over execs: less downtime, lower maintenance cost

🔸 How their platform integrates with SCADA, SAP, oil analysis & more

🔸 Where RCA software fits in for long-term strategy

If you're curious about how AI can solve real equipment issues—not just produce pretty dashboards—this episode delivers.

This episode is available on:

📺 YouTube

🎧 Apple Music

Or wherever you get your podcasts!

Want to explore how AI and RCA can work hand-in-hand to solve your toughest reliability challenges? Message us or connect at: https://easyrca.com/engage

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