Automotive equipment manufacturer manages customer data from the edge

A Fortune 500 automotive equipment manufacturer built an AI predictive maintenance solution to predict potential failures in its equipment. Since unplanned downtime in automotive manufacturing can result in millions of dollars of loss, this solution is gaining rapid interest with its customers. However, the company finds that many of its customers are not willing to move data to the cloud, and because the AI solution is in the cloud, this prevents adoption from many of its customers.

Prescient is helping the company to move its AI predictive maintenance solution to the edge. The AI solution runs in a container at the edge, and Prescient supports the complete solution from data ingestion, cleansing, transformation, to post-processing and data integration.

In addition to supporting the complete edge solution, Prescient has helped the company to significantly improve its edge data pipeline. Previously, data was collected in XML files and was manually cleansed and transformed by the company’s engineering team. This is not only time consuming, it is also error-prone and not scalable. And because the data structure can be modified by the customer, the unexpected changes in the data structure can break the company’s data preparation process, and also possibly the AI that follows.

Using Prescient’s OpenCDM data management solution, Prescient can both automate the data pipeline and detect data structure changes. This significantly speeds up the data preparation process and allows the company to scale to many customers without having data preparation as the bottleneck. By validating data structure, Prescient helps the company to avoid mistakes which nearly eliminates lengthy engineering time for debugging and fixing data structure errors.

Ask our experts.

Learn how you can build flexible and customizable edge DataOps by consulting our experts today.

What You Need to Know

  • Overcomes data privacy challenge by keeping customer data at the edge

  • Eliminates lengthy engineering time for fixing data structure errors

  • Automated data cleansing for XML files and detects data structure changes