problem

A Fortune 50 company wanted to be able to predict key performance metrics based on prior time series data saved to a log file. Being able to know that certain events were likely to occur in the future was of significant business value.  Thankfully they had millions of lines of log data we could use to train a model to do exactly that. 

use case

With NeoPulse® Studio, an AI model was trained on log data taken from servers in such a way that it would predict the next 10 or 45 minutes of data from the previous 6.5 or 15 minutes of data respectively. By identifying when important events were likely to occur the organization would be able to anticipate and meet customer needs with almost clairvoyant ability.

predicted time stamp for appliance manufacture using NeoPulse AI platform
predicting time stamp for large appliance manufacturer using NeoPulse platform

Results

NeoPulse® was able to predict the CPU utilization to within 10% of the actual results for the next 45 minutes and sometimes as low as to within 0.5% of the actual results for the same period.

redeploy

Do you have an internal process that outputs operational data to some sort of log file or database? Would it be valuable to get ahead of problems before they happen, or identify previously unseen anomalies in real time? You can redeploy this AI model architecture and train it on your data with just a few clicks in NeoPulse Studio. Connect with us to discover how.

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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.

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Serena Miran
Megazone Cloud
Manager

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

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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.

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