IoT & Industry 4.0
AI on the factory floor. Not just in the control room.
For manufacturing, mining, energy, and logistics leaders. IoT and AI that works where conditions are harsh, networks are spotty, and stakes are measured in tonnes and megawatts.
Who This Is For
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AI-Based OT Systems
IoT sensors, edge AI, and predictive models deployed in aluminium rolling, steel manufacturing, and oil-fired boiler operations.
Predictive Maintenance
Machine learning models that identify equipment failure risks before breakdowns happen, reducing unplanned downtime.
Energy Management
AI-driven thermal and mechanical optimisation to reduce energy consumption and improve operating efficiency.
Digital Twins & Telemetry
Real-time virtual representations of assets and processes for monitoring, optimisation, and operational visibility.
What Else We Enable
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Vehicle Monitoring
AI-powered monitoring systems for mining and construction vehicles operating in harsh environments.
SCADA & MES Integration
End-to-end data flow and integration with existing operational systems for real-time visibility and control.
What Changes For Your Operations
Operations move from reactive firefighting to predictive and optimised systems driven by real-time data.
Unplanned downtime reduces significantly with predictive maintenance.
Energy consumption drops through AI-driven optimisation.
Production efficiency improves with real-time monitoring and control.
Decision-making becomes data-driven at every level of operations.
Results
20% efficiency improvement | 15% energy savings (~$1.8M/year) | 30% less downtime | 10-month ROI
Related Case Studies
FAQ
Can this work in harsh industrial environments?
Yes. These systems are designed for plant floors, mining environments, and remote operational sites where heat, dust, vibration, and unstable connectivity are common.
Do you integrate with existing SCADA or MES systems?
Yes. We connect IoT and AI layers with existing SCADA, MES, ERP, and telemetry systems to avoid parallel infrastructure.
Can you deploy AI at the edge?
Yes. Edge deployments are used where low latency, local processing, or unreliable connectivity make cloud-only setups impractical.
What kind of outcomes do these deployments usually improve?
Typical improvements include reduced downtime, energy savings, better asset visibility, predictive maintenance, and higher production efficiency.
Book an AI-OT readiness review
Tell us about your plant, processes, and challenges. We’ll assess where IoT and AI can deliver measurable impact.