Kubernetes control
Operate clusters and workloads from one deliberate control surface, without flattening the boundaries between environments.
Infrastructure intelligence for the AI era.
Operate Kubernetes and GPU infrastructure with a shared model for health, capacity, incidents, and controlled action.
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Kubernetes and GPU operations
Agent-based
Outbound cluster connectivity
Accountable
Reasoned and audited change
One operational system
See the whole infrastructure. Act with precision.
AIDC brings the signals and workflows behind AI infrastructure into a coherent operating model—from Kubernetes resources to individual GPU devices.
GPU operations
Understand device health, allocation, topology, and workload pressure across the accelerators that matter most.
Deep observability
Connect infrastructure signals to the resources, alerts, and operational context behind every change in system health.
Incident workflow
Move from detection to accountable action with tickets, operational context, and a complete audit trail.
Capacity intelligence
Reveal fragmentation, idle capacity, and placement constraints before they become expensive scheduling problems.
Agent architecture
Central intelligence. Local authority.
A central control plane coordinates policy and context while a lightweight Agent stays close to each Kubernetes cluster. Connections remain outbound, scoped, and observable.
Mutual TLS between control plane and every Agent
AIDC control plane
Policy, inventory, workflow, audit
Training
Cluster Agent
Inference
Cluster Agent
Research
Cluster Agent
Security by operation
Control is only useful when it is accountable.
Identity, authorization, verification, and audit are part of the workflow—not a separate layer operators have to reconstruct later.
Mutual TLS
Authenticated, encrypted Agent connections.
MFA and step-up
Additional assurance for high-risk operations.
Permission RBAC
Explicit access aligned to operational responsibility.
Complete audit
Actor, reason, target, decision, and result preserved.
H100
GPU operations profile
H200
GPU operations profile
B200
GPU operations profile
B300
GPU operations profile
Across GPU generations
A clearer operational story for every accelerator.
Follow health, placement, utilization, and capacity context across mixed H100, H200, B200, and B300 environments without losing the Kubernetes workload behind each signal.
- Device and node health in context
- Capacity and fragmentation analysis
- Direct paths from alert to investigation
Bring infrastructure decisions into focus.
Enter the operations console to inspect the current environment.