AiK Cloud
Unified control plane
Single Kubernetes-native surface across 15+ cloud and on-prem environments.
Platform / AiK Cloud
AIK CLOUD
Sovereign multi-cloud control plane for AI & HPC workloads
AiK Cloud is the unified platform where workloads run: one control plane across 15+ cloud and on-prem environments so teams operate AI infrastructure as a single system—fully managed MLOps and open-source tooling on sovereign infrastructure, without the usual integration tax.
Compute / Unified View
POOL COMPUTE ACROSS CLOUDS
AiK Cloud pools compute from multiple cloud providers into one control plane, so teams do not need to open separate provider accounts or manage fragmented access paths. Get the compute you need with a click and place workloads where cost, performance, and sovereignty align.
Platform Demo
SEE AIK CLOUD IN ACTION
01 / Platform
WHAT IT INCLUDES
Everything needed to run AI and HPC as one sovereign fabric—from clusters to serving and marketplace services.
AiK Cloud
Sovereign compute
Deploy where regulation demands—UK, EU, on-prem, and hybrid—with consistent policy.
AiK Cloud
Private networking fabric
Low-latency, high-bandwidth mesh between clusters and data estates.
AiK Cloud
GitOps, MLOps, DevOps
Integrated delivery and ML lifecycle tooling on sovereign infrastructure.
AiK Cloud
LLM serving
Built-in patterns with Ray Serve and vLLM for production inference.
AiK Cloud
Managed marketplace
100+ managed services—from databases to vector stores and backends.
KEY CAPABILITIES
Operational depth for regulated teams: visibility, portability, and production inference at scale.
AiK Cloud Capability Map
One view across clouds, regions, and on-prem GPU pools.
Operate distributed infrastructure through one control plane instead of fragmented provider dashboards.
MANAGED SERVICES
Examples from the marketplace—deploy as managed stacks on your sovereign clusters.
- Databases: PostgreSQL, CockroachDB
- Vector DBs: Weaviate, Qdrant
- MLOps: Kubeflow, MLflow
- Backend: Supabase
ONE CLUSTER, MANY CLOUDS
Operate AI workloads across providers as if they sit on a single cluster—cutting cost by up to 80% in many footprints and eliminating hyperscaler lock-in while staying sovereign-by-design.