Enterprise AI Platform Engineering
Kubernetes-native AI architecture, secure team environments, self-service, resource management and tenant isolation.
ENTERPRISE AI · MLOPS · PRIVATE INFRASTRUCTURE
From GPU infrastructure and private AI platforms to model operations, governance and edge AI, we engineer the foundations for production-ready AI workloads.
FROM PROTOTYPE TO PRODUCTION
Many AI projects succeed in a proof of concept but struggle in production. Scalability, secure data pipelines, repeatable deployment, resource management and observability need to be engineered together from the beginning.
OUR AI & MLOPS SERVICES
Kubernetes-native AI architecture, secure team environments, self-service, resource management and tenant isolation.
Sovereign GPU platforms across on-premises, hybrid and partner infrastructure, with capacity planning, isolation and workload scheduling.
ML pipelines, model versioning, validation, deployment, monitoring and controlled updates with appropriate open-source tooling.
Infrastructure for deploying and operating LLM inference, retrieval-augmented generation and AI agent workloads.
Local inference, distributed Kubernetes, industrial data processing and reliable edge operations.
Kubernetes infrastructure and operations for robotics fleets, autonomous systems and industrial AI applications.
Identity, data protection, segmentation, traceability, security policies and controlled change management.
Architecture workshops, platform blueprints, technical evaluation and practical paths from pilots to production.
OPEN FOUNDATIONS
OpenKubes brings Kubernetes platform engineering to AI and MLOps workloads. Our focus is on open components, reviewable architecture decisions and control over infrastructure and data.
Discover OpenKubes ↗LET'S TALK AI ENGINEERING
Talk to our engineers about your private AI, GPU, MLOps or edge AI requirements.