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Predict breakdowns before they stop production.
DataTheta helps operations teams connect sensor, MES, SCADA, maintenance, quality, and production data into live plant intelligence.








- The Problem
Plants generate data. Decisions still arrive late.
Operations teams rely on disconnected sensors, manual logs, shift reports, maintenance records, and delayed OEE dashboards. DataTheta connects those signals into intelligence leaders can act on.
- Reactive Maintenance
Breakdowns still surprise teams because sensor data is collected but not converted into early warnings.
- Delayed OEE
Line performance is reported after the shift, not managed live while losses are happening.
- Quality Loss
Defects are often discovered downstream, after scrap, rework, or customer impact has already occurred.
- Site Silos
Each plant optimizes locally, while enterprise-wide performance patterns remain difficult to compare.
- Energy Waste
Machine, line, and shift-level waste stays hidden without connected operational and energy data.
- Capabilities
What we build for plant teams.
DataTheta builds operational AI and analytics systems that turn plant data into uptime, quality, efficiency, and cost outcomes.
Predictive Maintenance
- Failure alerts
- Sensor monitoring
- Parts prediction
- Intervention planning
OEE Intelligence
- Live OEE tracking
- Line visibility
- Shift comparison
- Loss analysis
Quality Analytics
- Defect detection
- Root-cause AI
- Batch linkage
- Process monitoring
Plant Command
- Site dashboards
- Line performance
- Exception alerts
- Leadership views
Waste Analytics
- Energy tracking
- Yield loss analysis
- Machine efficiency
- ESG reporting
24h
Failure prediction window
-45%
Unplanned downtime
+12 pts
OEE improvement
-38%
Quality defect rate
-10–40%
Maintenance cost reduction
800h
Preventable downtime risk
- How It Works
From function pain point to production intelligence.
DataTheta starts with the business outcome, connects the right data, builds the intelligence layer, and embeds it into how teams actually work.
Discover
Map the function's goals, workflows, pain points, and data sources.
Design
Define the data model, analytics layer, AI use cases, and governance approach.
Build
Create pipelines, dashboards, models, copilots, and decision workflows.
Deploy
Embed intelligence into existing tools, teams, and operating rhythms.
Improve
Monitor adoption, accuracy, outcomes, and continuously improve the system.
Operations FAQs
Common questions about predictive maintenance, OEE intelligence, plant analytics, quality AI, and operational decision systems.
DataTheta builds predictive maintenance, OEE intelligence, quality analytics, plant command centres, waste analytics, and digital-twin-ready data foundations.
Yes. DataTheta works with MES, SCADA, IoT sensors, historians, maintenance systems, quality systems, and production records.
No. DataTheta builds connected data layers, AI models, real-time alerts, root-cause systems, and operational workflows.
It connects sensor data, equipment history, production context, and maintenance records to detect likely failures earlier.
The first use case can usually be scoped within weeks, depending on asset data, system access, and plant complexity.
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See what DataTheta can do for operations.
Share your plant systems, equipment data, and operational priorities. We’ll show how DataTheta would approach them.