From hardware to workload
GPU topology, storage throughput and scheduling determine what you can actually run. We connect those choices to your models, dataset and capacity.
07 / What we build
The foundations matter as much as the model.
We design and build the GPU, storage and platform layers for training, inference and document processing. Including the path to daily operations.
Connected where possible. Offline where required.
Kubernetes, Kubeflow, image registries and model storage can run in tightly controlled or fully disconnected networks.
WHAT YOU GET
Compute and storage
GPUs, NVMe-oF, networking and scheduling matched to the workload.
MLOps
Repeatable pipelines, model versions and controlled releases.
Observability
Visibility into execution, usage, quality and bottlenecks.
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