Real Life Business Impact of AI/ML on GE CT Scanners Using Glassbeam Clinsights™

Vivek Sundaram
Sep 25, 2019

We are now in an era where machine learning isn't just hype. In fact, it is absolutely real in its business impact as Glassbeam has recently demonstrated for its growing network of connected medical imaging equipment.

With Glassbeam's extensive experience in data engineering and analytics related to GE CT Scanner machine logs, we now have dozens of powerful use cases where automated anomaly detection via machine learning has been used to detect potentially expensive part failures well before the end-user even noticed an issue.  Here are 3 real-world examples:

The intersection of machine data analytics and the internet of things

Sep 08, 2013

The ability to gather and harness data from machines and devices connected to the net is increasingly becoming a source of competitive advantage for those who have been thinking ahead. GE is widely cited, with their INDUSTRIAL INTERNET initiative. Cisco has been talking about INTERNET OF EVERYTHING for a while. At Glassbeam, we have been focusing on the infrastructure required to process and analyze machine data for over 3 years now.

Scaling machine data analytics for the internet of things – introducing glassbeam scalar

Oct 21, 2013

from: Puneet Pandit, CEO, Glassbeam.

It’s a new era…

Welcome to the Internet of Things – where every connected physical device will generate volumes of machine data. And the key to extracting the intelligence and meaning locked inside this data will lie in a highly scalable platform and a set of applications. At Glassbeam, today marks the launch of that that truly next generation platform purpose-built for machine data analytics – Glassbeam SCALAR.

Analyzing logs and more. A big data reference architecture

Srikanth Desikan
Jan 14, 2013

Analyzing logs and more- a Big Data reference architecture for processing product logs and other data.

Big data and log files

Splunk’s great success in providing the tools for a sysadmin to delve into previously inaccessible log files has opened up the market for deeper analysis on data in log files.