For years, predictive maintenance was treated as a “nice-to-have.”

Today it’s becoming the core infrastructure of competitive manufacturing — and the shift is happening faster than most companies realize.

What’s driving this change?
Edge AI, ultra-low-latency connectivity, and accessible learning paths that empower teams to build real systems instead of just talking about AI.

That’s exactly where Tachyon comes in.

Why Tachyon Matters

Tachyon finally gives creators and engineers a reliable way to run AI at the edge — not in a lab, not in a cloud demo, but directly on machines.

With:

• real-time sensor streaming,

• secure 5G connectivity,

• and on-device inference,

…maintenance teams can detect failures hours or days before they happen, with no need for complex IT overhead.

This is the moment where predictive maintenance moves from “experimental pilot” to repeatable product.

A New Approach: Teach, Build, Deploy

I believe the next wave of industrial AI success will come from people who can do two things:

1. Build practical, working AI systems on platforms like Tachyon.

2. Learn fast — and share that knowledge just as quickly.

That’s why alongside building my own predictive maintenance stack, I’m creating hands-on AI learning paths on Kajabi: simple, practical, and focused on deployment rather than theory.

If you want to understand AI not from a textbook but from real machines, real data, real tests, this is the place.

What’s Next

Over the next weeks, I’ll be sharing:

• early results from Tachyon-powered sensor analytics,

• behind-the-scenes development of our maintenance intelligence platform,

• and step-by-step lessons you can apply immediately in your own operations or AI projects.

If you want to follow the journey, learn, and build with me — you’re in.