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Energy | Utilities | Manufacturing

Working with our clients to increase efficiency, reduce waste, reduce emissions and improve safety with AI

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Civil Nuclear Power

Our technology is used to ensure nuclear power stations operate as safely and as efficiently as possible. We have developed advanced machine learning solutions to optimise reactor performance, reduce outage duration, reduce plant emissions, and predict and prevent adverse process faults.

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We work with operators to monitor the health and performance of critical turbine components and rotating plant to minimise unplanned downtime and optimise offshore maintenance schedules. We specialise in unsupervised ML techniques for wide-scale fleet health monitoring.

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Solar PV operators look to us to get the most out of their plants and to prevent complex adverse events reducing output or increasing maintenance costs. We work across a variety of technologies in all phases of the power generation process and associated balance of plant systems.

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In this highly regulated sector where downtime is unacceptable, we are able to effect rapid change with minimal impact on day-to-day operations.  Our sensor health technology is used to minimise sensor calibration burden and reduce the risk of adverse quality events.

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Built Environment

We work with partners to develop digital twins of industrial buildings from construction through to commissioning and operation. We support development of the BIM process into fully fledged digital twins to optimise building energy consumption and guide decision making during construction.

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Our advanced condition monitoring technology helps manufacturing facilities to boost OA and OEE and optimise maintenance regimes to reduce cost and waste. Our digital twins integrate with existing platforms to provide richer insight into plant performance.

Our work

Case study

Ada Mode Smart Factory

Case study

Surrogate modelling in nuclear generation

Case study

Optimisation of biogas upgrade plant performance

Case study

Generator system health determination for maintenance optimisation