Skaiwatch is a predictive maintenance program which allows you to reduce maintenance cost by 30-40%, unexpected failure by 40-50% and optimize spare parts inventory by 15-20%. Skaiwatch is:
Easy to use
Web-based interface provides access to view alerts and KPIs for 10 or 10,000 assets anytime and anywhere.
Build with experience
Our algorithms are built with combined experience of more than 70 years with service, maintenance and condition monitoring of rotating machines.
Scalable and safer
Skaiwatch grows with your needs, from tens to thousands of machines on demand. Secure data transfer with APIs and secure FTP from historian/IoT platform/ PLC system and other existing data sources.
Skaiwatch learns the normal behavior of your machines and will alert you when it starts showing anomalies and signs of deterioration.
Skaiwatch takes advantage of big data technology combined with machine learning, deep learning and transfer learning, to monitor, and reveal machines condition.
We ingest your data continuously into our secure and scalable data platform.
An API call allows an easy access to data, which is fed to SkaiWatch, where the data is automatically featured engineered, real time analysed for any anomaly. depending on the type of data, we predict the remaining useful life of your assets.
The resulting mined data is display on a dashboard available accross all devices.