We delivered a cloud-native data science and ML platform on GCP and Kubernetes, fully aligned with enterprise security and IT standards.
Meet our client
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Client’s Challenge
A multinational manufacturer required a secure, cloud-native platform to support distributed DS and ML teams across EMEA. The infrastructure needed to enable compliant data access, collaboration, and scalable GPU training without heavy reliance on in-house MLOps or DevOps. It also had to enforce strict security while keeping shared compute costs under control and enabling rapid adoption of production-grade ML workflows.
Our Solution
We delivered a cloud-native data science and ML platform on GCP and Kubernetes, fully aligned with enterprise security and IT standards. The solution provides isolated, containerized user workspaces with persistent storage, secure VPN- and IAM-based access, integrated enterprise tooling, and on-demand GPU training with built-in experiment tracking and monitoring.
Client’s Benefits
The new platform standardized and secured enterprise AI development by accelerating productivity, improving collaboration, enforcing security, optimizing compute costs, and enabling scalable growth to GPU-intensive workloads.
