A More Cost-Effective and Predictive Automotive Supplier


The Need

The automotive supplier in question found themselves hindered by outdated data infrastructure and mounting costs. They sought to leverage machine learning, but lacked the expertise to execute. StandardData was brought in to address these challenges, optimize their infrastructure, and develop a powerful fault-predictive model.

  • Upgrade data infrastructure
  • Enable machine learning capabilities
  • Swift data processing within tight deadlines

The Challenge

The client struggled with escalating financial and operational costs due to their constantly expanding dataset and existing solutions in data storage and processing. They needed an innovative, data-driven approach to becoming machine-learning ready and managing their extensive data storage requirements

The Solution

StandardData swiftly deployed its expertise to provide a comprehensive solution aligning with the automotive supplier’s needs.

  • Optimized data storage to reduce costs by over 50%
  • Dramatically reduced processing times from weeks to hours
  • Developed a machine learning predictive model for faults

The Result

StandardData’s optimized infrastructure enabled machine learning for predictive fault detection, reduced data processing time, and enabled effective scaling of operations in the future. These enhancements led to the client’s increased efficiency and competitiveness in the market.