Case Study: Volkswagen Group increases productivity and speeds prototyping with ClearML

Volkswagen Group boosts cluster utilization and cuts MLOps maintenance with ClearML

Volkswagen Group's Machine Learning Research Lab faced a challenge in increasing productivity and decreasing prototyping time. They lacked a single end-to-end platform to automate the ML lifecycle, leading to difficulties in comparing experiments, workload prioritization, and significant administrative overhead from extending open-source solutions. They sought a unified MLOps solution to replace their entire stack and enable researchers to work without major technical support.

By implementing ClearML, the lab gained an all-in-one solution featuring orchestration, experiment management, and dataset sharing. The results included deprecating their previous heterogeneous MLOps stack, minimizing administration work, and achieving high cluster utilization to maximize their compute infrastructure. ClearML provided the team with a unified platform for sharing information and artifacts, simplified compliance with RBAC, and enabled full automation of workflows for continuous delivery and evaluation.

Volkswagen Group