AI HPC Platform
A Kubernetes-native platform to run and manage AI HPC workloads — for both training and inference — across on-prem clusters and sovereign clouds, with AI-native observability and security at the core.
Topology-aware, gang and priority scheduling tuned for large-model training and low-latency inference.
Runs air-gapped, on-prem or on sovereign clouds — with the same control plane and no lock-in.
Model, GPU, network and job telemetry unified — with agents that surface anomalies and root causes.
Hardware-rooted identity, supply-chain attestation and per-workload isolation by default.
Quotas, fair-share and chargeback across research and product teams on shared fleets.
First-class support for RDMA, InfiniBand and RoCE with automatic fabric health remediation.
Built on Kubernetes with a hardened control plane, a GPU-aware scheduler and a telemetry pipeline designed for AI. The Agentic Layer plugs directly into the control plane for provisioning, remediation and optimization workflows.
Agentic Layer
Plug-and-play agents extend every workflow — from provisioning to observability — with a shared plugin architecture across the stack.