Automotive equipment manufacturer automates data and AI at 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 their 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 orchestration and management of this solution.

In addition to edge AI, Prescient has helped the company to automate its edge data pipeline. Automotive manufacturing data is very complex and can include thousands of parameters.  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, not real-time, and not scalable. And because the manufacturing data can be modified by the end customer, the unexpected changes in the data structure can break the data preparation process and the AI that follows.

Using Prescient’s OpenCDM data management solution, Prescient automates the data pipeline and detects data structure changes. This significantly speeds up the data engineering process and allows the company to scale to many customers without having data pipeline as the bottleneck. By validating data structures, Prescient helps the company to avoid mistakes, which eliminates costly engineering time for debugging and fixing data structure errors.