Third party feeds
Driven by Industry 4.0 / the Industrial Internet of Things, industrial operations are increasingly autonomous. Sensors all over the factory provide real-time data on the status of production and machinery to optimize operations. Welcome to the fourth Industrial Revolution.
Senseye is the only product to offer easy-to-use automatic condition monitoring and prognostics at scale, without requiring deep pockets or a team of expert data analysts. Senseye enables predictive maintenance, the key to reducing unplanned machine downtime and increasing Overall Equipment Effectiveness (OEE).
Instant deployment and actionable results within two weeks.
No need to hunt for data or interpret complex charts. Senseye tells you what you need, when you need it.
Over 40 years of condition monitoring and prognostics knowledge, combined with the latest advances in machine learning and semantic technology.
From one machine to thousands, we deliver Uptime as a Service as a scalable solution to meet your ongoing business needs.
Be a maintenance hero
Senseye puts predictive maintenance at the core of operational performance, removing chaos and uncertainty, helping you to become a maintenance hero. Think of it as a team of condition-monitoring engineers in the cloud, getting the right information to you ahead of time, multiplying your efforts.
Fact: 45-55% increased productivity of maintenance staff
Predict the unpredictable
Senseye enables quick and easy predictive maintenance, reducing unplanned downtime and maximizing OEE; it’s the ultimate cloud-based uptime application for time-starved production and operations managers. Our proprietary machine learning technology infused with over 40 years of machine failure expertise gives you fast, accurate Remaining Useful Life (RUL) information without upfront costs.
Fact: 30-50% reduction in machine downtime
Senseye helps you to reduce the Total Cost of Ownership of your assets, increasing throughput, saving money and improving profitability.
It’s the ultimate cloud-based uptime application to let you know what’s happening now and in the future, in a really simple way and at any scale.
Fact: 10-40% reduction in maintenance costs
Levering industrial trends like the Industrial Internet of Things and analytics at scale with our unique prognostics engine, Senseye delivers truly transformational condition monitoring and predictive maintenance capability. As the only product to offer scalable automatic prognostics, Senseye is transforming predictive maintenance.
Fact: 85% increase in forecasting accuracy
Senseye connects to your sensor, control and operational data stored in a factory historian, database or IoT middleware solution. There is no requirement to add any hardware or install any software on-site.
Third party feeds
Don't worry about these,
Senseye uses them
Senseye clever stuff
Easy and simple to use,
we bring you the information you need to know.
Get in touch and start saving money
Are you ready to take control? Start getting ahead of downtime by using Senseye to guide your decisions.
Get in contact to share your requirements and discover how much Senseye could improve your operations.
Predictive maintenance sounds great – maintain your assets, before they show outward signs of failure and cause unplanned downtime (loss of revenue), whilst spending less money than you would for a preventative maintenance program – boosting profitability and throughput. The benefits are quite clear. Why then do relatively few companies have an active predictive maintenance program?
Condition monitoring, whilst now highly technical and adapted for specific industries (with Aerospace & Defence arguably leading the way) had very humble beginnings, essentially listening to a machine and trying to understand if it ‘felt right’ or not. Humans seem to have an inherent talent for this (I’m sure many of us have experience with our cars, feeling that something isn’t quite right or doesn’t sound like it should!) but pure intuition isn’t a good way to scientifically implement predictive maintenance and avoid unplanned downtime.