One platform, four pillars
Four kinds of intelligence. One platform.
Start with the pillar that hurts most today. Add the others on the same data, with no new integration.
Execution Intelligence
Where are we losing output?
- Advanced OEE with automatic downtime and reason capture
- Live job tracking synced with your ERP work orders
- AI scheduling that adjusts to real capacity and material
Maintenance Intelligence
Which machine will stop us next?
- Condition monitoring on vibration, temperature and current
- Predictive alerts with probable cause
- Service history, work orders and spare parts
Quality Intelligence
Why did this product fail spec?- AI vision defect detection on the line
- Each reject traced to the process conditions behind it
- Auto-hold limits per product grade
Energy Intelligence
What does energy cost per good unit?
- kWh per part, per product grade, per shift
- Peak-demand and idle-load alerts before they hit the bill
- Machine-level metering with low-cost edge devices
AI Advisor
Built for real plants. Not hypothetical AI.
iDataOps sits above your controls and beside your ERP. It doesn't replace them; it makes them smarter.
Straight from the machine
Connects directly to PLCs, robots, sensors and SCADA over OPC-UA and standard industrial protocols. No middleware project.Â
Works with your ERP and MES
Answers why, not just what
One view of output, energy, assets and quality
Four connected modules on one data model. See cost per good unit, not four separate dashboards.
Value before contract
Start with one line and one use case. We connect, collect and show results before you commit.Â
Platform building blocks
Start where you need. Scale when you're ready.
Real-Time Insight
One live view across lines, machines and plants. The command center for all four pillars.
Operator Assistance
AI-prioritized tasks and the right operator on the right machine, every shift.
Edge Devices
Collect data from any machine, including older ones, using ADE9000, Raspberry Pi 5 or custom boards.
Purposeful AI
AI trained on real machine data, built to explain.
Dashboards tell you what happened. iDataOps tells you why, and what to do next.
Root cause, not just alarms
When a line stops, a part fails spec or energy spikes, our AI traces it back to the runtime conditions that caused it and shows you the evidence.
Scheduling on live capacity
Schedules adjust to real machine availability, labor and material, not last week's plan.
Downtime prediction
Spot failure patterns days ahead and plan the fix around production.
Material forecasting
Predict material use per job to avoid shortages, overruns and scrap.
Industries we serve
Deep in three industries, not spread thin across all of them.
Running in production at plants in the USA and India.
Discrete Manufacturing
Auto components · Precision engineering · Press shops
Typical operations
CNC machining, stamping and press lines, assembly cells
Where we help
- Cycle time, OEE and downtime per machine and part
- Die and tool life tracking, predictive maintenance
- Job progress and labor reported back to ERP
Specialty Chemicals
Adhesives · Packaging materials · Plastic films
Typical operations
Extrusion, coating, lamination, reactors, converting
Where we help
- Process parameters linked to every quality defect
- Run and batch consistency against grade specs
- Energy per kg on extruders, dryers and chillers
Paper Mills
Kraft · Duplex board · Writing and printing
Typical operations
Paper machines, pulpers, dryer sections, boilers, winders
Where we help
- Machine speed, breaks and downtime by shift
- Steam and power per tonne of good paper
- Quality by grade, linked to machine conditions
Proven on the plant floor.
From control rooms to the C-suite, iDataOps delivers results you can measure.
iDataOps is easy for our team to use, and it has helped us cut production losses and improve product quality.
Pete Mazik
Operations Head
iDataOps' analytics and real-time monitoring have given us a level of control over our production process we never had before.
Grant Branch III
CEO
With iDataOps, we unified 40+ machine feeds across lines in under a month and gained a true factory-wide view of performance.
Josh Washington
Head of Digital
Transformation
How it works and integrations
From machine signal to decision, in four steps.
Connect
Edge devices and protocol connectors read PLCs, sensors, robots and SCADA. Read-only: we never control the line.
Contextualize
Machine data is matched with jobs, products and orders from your ERP and MES.
Explain
AI finds patterns, predicts problems and traces each loss to its cause.
Act
Alerts, schedules and recommendations reach operators, engineers and managers in real time.
Machines & PLCs → Edge device → AI engine → Real-time insight → ERP / MES
Works with the protocols and platforms you already run.
