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AI infrastructure for predictive maintenance, quality control, supply chain optimisation and digital twins — deployed on-premises for the operational demands of the factory floor.
European manufacturing faces a defining challenge: how to maintain competitiveness against lower-cost regions while meeting increasing demands for quality, sustainability and supply-chain resilience. The answer lies not in replacing workers with AI but in giving them better tools — systems that predict equipment failure before it halts a production line, that detect microscopic defects invisible to the human eye, that optimise thousands of supply-chain variables in real time. NOVACORE AI delivers private, on-premises AI infrastructure designed specifically for industrial environments. Our systems integrate with existing PLCs, SCADA systems, MES platforms and ERP backbones — ingesting sensor data, machine logs and quality measurements to build predictive models that run at the edge, near the equipment that generates the data. This is not a cloud service that requires internet connectivity and ships data to external servers. It is AI infrastructure that lives in your factory, on your network, under your control. Models are trained on your machines, with your data, and never leave your facility.
Sensor-driven machine learning models that predict equipment failure hours, days or weeks in advance. Analyse vibration, temperature, current draw and acoustic signatures to forecast bearing wear, motor degradation and tool condition — reducing unplanned downtime by up to 30% and extending asset life.
Computer vision and AI inspection systems for surface-defect detection, dimensional measurement and assembly verification. Deploy at line speed with models trained on your product specifications and defect taxonomy — catching defects that escape human inspection.
AI for demand forecasting, inventory optimisation, supplier risk assessment and logistics routing. Model thousands of supply-chain variables — from raw-material lead times to shipping disruption probabilities — with explainable recommendations for procurement and operations teams.
Real-time digital replicas of production lines, individual machines and entire factories. Simulate process changes, test line configurations and optimise throughput before committing physical resources — with AI-driven what-if analysis running on your private infrastructure.
AI-driven process parameter optimisation for yield improvement, energy reduction and waste minimisation. Continuous analysis of production data identifies optimal settings for temperature, pressure, speed and material ratios — adapting in real time to changing conditions.
Edge AI infrastructure that processes sensor data where it is generated — on the factory floor, not in a distant cloud. Real-time inference on streaming data from hundreds or thousands of sensors, with localised models that continue operating even during connectivity interruptions.
On-site survey of equipment, sensor infrastructure, data availability and integration points. Identify high-value use cases with measurable ROI.
Deploy edge AI infrastructure on a single production line or asset class. Train initial models on your data and validate performance against operational KPIs.
Expand across production lines, sites and asset classes. Federated model management and centralised monitoring while maintaining site-level data sovereignty.
Continuous model improvement with new data. Advanced use cases including cross-site benchmarking, supplier quality prediction and autonomous process control.
Manufacturing AI must integrate with existing operational technology — not replace it. NOVACORE platforms connect to PLCs, SCADA, MES and historians through standard industrial protocols (OPC UA, Modbus, MQTT) while maintaining the security isolation between IT and OT networks. Models run at the edge, near the equipment, with deterministic inference latency suitable for real-time control loops. No production data leaves the factory perimeter without explicit authorisation.
Secure AI and high-performance computing for enterprises, governments and research.