Predicting Downtime

problem

Business processes and customer experience often depends on high availability and performance. Unplanned downtime has risen 59% over the last 3 years.

use case

Learn what normal network behavior looks like based on event data, traffic information, application data and SNMP data
In real time, indicate that the network is deviating from predicted behavior
Make predictions about future behavior of the system

How to Customize

Detailed network data such as traffic information, machine profiling (CPU, I/O etc.), SNMP data
Model needs to be retrained on a regular basis
Applicable to predicting if the system is deviating from nominal behavior or predicting if an outage event is imminent

Seong-jin Kim

Hyundai Elevator

CDO

We were able to successfully train an AI model to recognize complex industrial parts using Neopulse 3.0 on AWS. The AI solution was built very quickly and was able to recognize objects in unpredictable, real-world environments with high accuracy.

Serena Miran

Megazone Cloud

Manager

Everybody seems confident in AI, and they actually enjoy solving various AI problems.

Balachandran Rajendran

Dell, Unstructured Data Solutions

CTO

The vendor’s services are integral to providing AI solutions for a wider audience. They had an effective project management style, accented by a quick working style.