Using Real-time Data for
Predictive Maintenance
Companies in industries from retail to manufacturing are using outdated maintenance models, processes that
are cumbersome and in desperate need of refinement.
Our real-time monitoring platform combined with inbuilt AI means that firms can start predicting issues before they happen.
Changing the efficiency mindset
Monitor the performance and condition of assets proactively. Assess risks for maintenance engineers and operators with visualised asset-level diagnostics across your estate.
Out with the old
From day one of installation The Hark Platform's Asset Monitoring systems use Machine Learning and Artificial Intelligence to automatically recognise patterns and spot anomalies. From proof of concept right through to nationwide scale-up projects, our technology instantly allows our clients cut energy costs, increase yield and predict failures.
Say goodbye to unplanned downtime
The Hark Platform can automatically make your maintenance team aware of potential areas of concern, through our real-time alerting function. Significant pattern changes and anomalies in energy usage data are exposed by Hark’s inbuilt Machine Learning that studies the usage and performance patterns of your assets from the day one of installation.
Scaling with a Top Four UK Retailer
The Hark Platform revolutionised efficiency for a top 4 UK retailer.
£0.5 million saved in 3 months. 600 stores nationwide. 368 million daily readings. 24,000 assets monitored.
Further Reading
CNG Energy chooses Hark for revolutionary energy analytics
Multi-award-winning commercial energy supplier CNG has chosen Hark to innovate their energy monitoring in order to provide instant access to consumption data and insight. Harrogate based CNG Energy who currently supplies over 50,000
How to Implement an Effective Energy Management Strategy
Effective energy management is the stringent control of energy consumption. The average UK office spends £10,423 per year on energy and 29.15% of that is used
Five Contextual Factors Which Increase Retail Shrinkage
In order to understand the factors which impact retail shrinkage, we must first analyse data at a store level, to