Predictive maintenance AI for manufacturing plants

Predict the breakdown before it happens

Unplanned downtime is the factory floor’s worst enemy. Our AI dashboard gives you a 48-hour warning before breakdowns happen, with visual signals your engineers can act on straight away. Why wait for a red light when the machine can already be telling you what’s wrong?

37% reduced unplanned downtime at a Midlands automotive stamping plant
4 hours edge gateway deployment, without turning it into a heavy IT project
4x faster defect detection with quality control metrics on live vision data
48 hours advance warning for failures, so maintenance teams can plan with confidence
Industrial engineer reviewing a predictive maintenance dashboard beside a production line with glowing equipment health indicators
Machines, sensors, and PLCs speaking the same language. Cleanly. Can your current setup do that?

Overall Equipment Effectiveness, live

See every line in your plant, from stamping to assembly, with a dashboard that turns raw signals into clear decisions. No clutter. No hunting through spreadsheets. Just the numbers that matter.

See how we reduce downtime

OEE at a glance

Availability, performance, and quality in one place.

OEE84%
Availability91%
Performance88%
Quality96%
Line 1
86%
Line 2
79%
Line 3
93%
Line 4
74%

Production line efficiency without the noise

A single control view for plant managers who need the story behind the figure.

Our dashboards connect directly to PLCs, sensors, and existing historians. That means your team sees cycle times, downtime causes, and throughput trends in context. Want the short version? The data tells you where the line is slowing down, and why.

Siemens
OPC-UA ready
Allen-Bradley
PLC-friendly
Real-time
Shop-floor cadence

Plant-wide tooltips

Useful, concise, and built for busy shifts.

Every metric can carry a plain-English note. Which line is drifting? Which batch needs attention? Which sensor has been noisy for three shifts? The answers are right there.

Shift comparison

See where night shift outperforms day shift.

Compare output by shift, product family, or machine cell. The layout is compact, but the story is not. It’s a useful angle for lean reviews and daily stand-ups.

Health scores for every asset

Motors, conveyors, compressors, and the awkward assets nobody talks about until they fail. Why wait for a surprise stop when the equipment already knows it’s struggling?

Main motor bank
RUL: 38 days

AI recommendation: bearing likely to fail in 38 days. Replace at the next planned maintenance window.

Conveyor drive
RUL: 112 days

Stable for now, but vibration drift has increased for two consecutive shifts. Worth a closer look, isn't it?

Air compressor
RUL: 24 days

Pressure variance and heat build-up are moving together. That pattern usually means trouble later in the week.

Robotic arm cell
RUL: 156 days

Healthy and within tolerance. The dashboard still watches for torque spikes, because quietly failing parts love to hide.

Cooling loop
RUL: 67 days

Temperature trend is rising during peak loads. If the pattern holds, maintenance should be booked before the next batch run.

Packaging unit
RUL: 94 days

Good performance today, with one sensor creating occasional noise. We flag it before the problem becomes a line stop.

Quality that builds itself into the product

Real-time SPC charts, defect drift alerts, and image evidence that your quality team can review fast. Could manual inspection keep up with this pace?

SPC drift chart

A clear view of defect movement across each production run.

Defect rate per 1,000 units Alert threshold reached on Shift 3

Defect gallery

Zoomable evidence for faster root-cause checks.

Midlands automotive plant slashes downtime by 37%

The problem was familiar: repeated line interruptions, maintenance fire-fighting, and no single view of equipment health. We connected the plant’s sensors, lifted the important signals into one dashboard, and gave the team a warning window that actually changed behaviour.

What happened next? Fewer surprise stoppages, faster scheduling, and a maintenance team that could work ahead of the failure, not behind it.

640

production hours regained annually

“The dashboard took the guesswork out of maintenance. We stopped reacting and started planning.”

— Ben Hargreaves, Plant Manager

Connects to your shop floor in days

Siemens, Rockwell, Mitsubishi, Fanuc, Bosch — the stack is broad, and the deployment is tidy. The edge gateway goes in quickly, so your team can get value before the month is out.

Siemens
Rockwell
Mitsubishi
Fanuc
Bosch
Edge gateway deploys in under 4 hours No IT heavy lift Visual-first diagnostics

Ready for zero unplanned downtime?

Get a plant health score now, then decide whether your maintenance plan is working hard enough. Why keep guessing when your machines can show you the risk before it bites?