Automation Just Grew Up: Learning in Operations with Edge AI
- Jasmine Shiel
- 8 minutes ago
- 2 min read
Let’s face it - automation is getting a glow-up. We’ve had programmable automation for decades. And it’s done a solid job—just like cassette tapes did once. But today, we’re not just pushing play on pre-set rules. We’re introducing machines that learn. Machines that adapt. Machines that figure things out on their own, in the real world, after they’ve left the factory floor.
It’s called Edge AI, and yes—it’s a big deal.
“Another AI company?” you ask. Not quite.
You might use ChatGPT for emails. Maybe there’s a chatbot on your website. Or AI nudging your sales leads along. That’s nice. But here’s a thought: What are you doing with AI on your actual products? Your core IP. Your secret sauce. The very thing your business is built on.
Most products today come loaded with sensors—generating real-time data 24/7. That’s the fuel for AI. So why aren’t we putting that data to work?
Here’s what you can do: Automate, but smarter.
Traditional automation works on one simple idea: we tell machines what to do. But only for what we already know—known faults, known thresholds, known use cases.
What about the unknowns? Different climates. Different setups. Different applications. What’s “normal” in one installation might be a red flag in another.
With Edge AI, your product doesn’t just follow instructions—it learns from its unique environment. It detects shifts. It adapts. It gets smarter, right there, on the edge.
Want proof? We’ve helped companies like Atlas Copco, Danfoss, and Siemens build products that think locally and act instantly.
See what that looks like in action:
Why this matters (a lot):
You know every product in the field is doing something slightly different.
You can’t hard-code all the possible situations it’ll encounter.
You don’t want delays (and inaccuracies) of sending summaries to the cloud.
You know data security is vital.
So we flip the model. Train a custom ML model on every device. Right there at the edge. No assumptions. No averages. Just your product, learning as it goes.
This means:
Condition Monitoring – actually know what every unit is doing.
Predictive Maintenance – catch issues before they become problems.
Performance Optimization – adjust for the best outcome, continuously.
Energy & Wear Reduction – less waste, more efficiency.
Automation of complex tasks – from setup to service timing.
And it’s secure, fast, and works on tiny embedded devices. Yes, we’ve run this on a valve terminal.
What’s the catch? There isn’t one.
You can be up and running with your own smart product—in under 6 months. And you don’t have to wait until someone else beats you to it.
Because here’s the truth: Products that learn will outperform those that don’t. Simple as that.
So if you’re ready to bring your products into the AI era—not for the buzz, but for the business impact—we should talk.
