Innovate-Ops

IoT Octopus

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Predictive condition monitoring

Stop guessing. Know which machine fails next.

One platform watches the condition of every asset — motors, pumps, compressors, gearboxes and more — across every line and site. AI reads vibration, temperature, electrical load and runtime, then ranks your equipment by what's most likely to fail first. No rewiring, no shutdown.

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Prefer to start small? Ask about a deployment on a handful of critical assets.

Built on Google Cloud · per-customer data isolation · Ontario-based

What customers see · illustrative
Plant condition · illustrative
Line 3 gearbox
Vibration trending up Watch
Coolant pump
Bearing temp rising At risk
Air compressor
Load steady Healthy

You can't fix what you can't rank.

No way to rank risk

Dozens of machines, one maintenance crew — and no clear signal for which asset is the one about to go.

The fault that hides between rounds

A monthly walk-around can't catch a bearing that turns from fine to failed in days.

Mixed assets, mixed blind spots

Motors, pumps, compressors and gearboxes each fail differently, and few programs watch them all the same way.

Reactive maintenance is the expensive kind

Running an asset to failure costs more in lost production and emergency repairs than catching it early ever does.

Condition monitoring, the simple way.

1

Mount the wireless sensor

Non-invasive sensors attach to each asset in minutes — no rewiring, no shutdown — on any machine type.

2

AI watches the condition

It reads vibration, temperature, electrical load and runtime across every machine type and learns each asset's baseline.

3

See what fails next

Your equipment is risk-ranked by what's most likely to fail first, with work orders and reports you can act on.

What you get from one view.

Your riskiest asset surfaced first

Stop guessing where to spend the crew's day — the machine most likely to fail next is at the top of the list.

Weeks of early warning

Catch a developing fault while it's still a scheduled fix, not an unplanned line-down event.

One view across mixed assets

Motors, pumps, compressors and gearboxes — every machine type ranked side by side on one platform.

Turn machine data into a ranked plan your team can act on — before the failure, not after.

Real, measured results · 2025

It ranked a $31,200 failure as the plant's rising risk — 48 hours early.

In a 2025 deployment at an Ontario building-products manufacturer, IoT Octopus ranked a drive motor as the plant's rising risk — flagging the developing bearing failure two full days before it seized. That is what condition monitoring catches that a rounds-based program misses.

$31,200 CADCost of the failure: $27,000 lost production + $4,200 repairs
48 hoursOf warning visible before the bearing seized
Under $200 CADThe lubrication job that warning pointed to
Risk-ranked early, this is a sub-$200 lubrication job scheduled for the next maintenance window — not a $31,200 line-down event.

Read the full case study →

Background reading: predictive vs preventive maintenance, explained.

Built for industrial reliability.

Built on Google Cloud

Secure, scalable infrastructure your IT team can trust.

Per-customer data isolation

Your data stays yours, isolated per customer and never used to train shared models.

Ontario-based

Built and supported from Kitchener, Ontario, with a Canadian primary data region.

Any asset, one platform

Motors, pumps, compressors, fans and gearboxes — watched the same way, side by side.

Predictive condition monitoring, answered.

What equipment can it monitor?

Most rotating and powered assets — motors, pumps, compressors, fans, gearboxes and more — on one platform. The same wireless sensor and AI read vibration, temperature, electrical load and runtime, so mixed equipment is watched the same way across every line and site.

How does it know which machine fails next?

The AI tracks each asset's normal condition and watches for the patterns that come before failure — rising vibration, heat or load. It then ranks your equipment by what is most likely to fail first, so you act on the riskiest machine instead of guessing.

How long does it take to install?

Sensors are non-invasive and wireless, so they mount in minutes with no rewiring and no shutdown. Monitoring starts the same day and the AI builds each asset's baseline from there.

Does it replace my CMMS?

No. It works alongside an existing CMMS — it tells you which asset needs attention and when, and turns that into a work order. Nothing gets ripped out.

How is our data secured, and where is it stored?

Your equipment data is encrypted in transit and at rest, with per-customer data isolation. The primary data region is Canada, and the platform is built on Google Cloud. You own your data at all times.

Can we start with just a few machines?

Yes. Many teams start with a handful of critical or problem assets, prove the value, then expand across more lines and sites. There is no minimum fleet to begin.

Want the whole picture?

Condition monitoring is one part of the platform. Explore how IoT Octopus turns machine data into action across every asset and site.

The full platform How the AI works Take the product tour

Book a demo.

See predictive condition monitoring running on your equipment — vibration, temperature and load across mixed assets, ranked by what fails next.

  • Built on Google Cloud
  • Per-customer data isolation
  • Ontario-based
  • A real person follows up within one business day

Real 2025 result: 48 hours of warning before a $31,200 bearing failure at an Ontario building-products manufacturer. Read the case study.

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