One system, owned end to end.
PureTensor Ltd designs, owns, and operates every layer of its platform — the silicon, the fabric, the storage, the orchestration, and the operations practice on top. No layer is rented from a hyperscaler; no abstraction hides an operator we cannot name. This page is the platform as built.
Current-generation NVIDIA Blackwell GPUs on AMD Zen 5 server platforms, with terabytes of system memory. Sized for private inference, fine-tuning, and GPU desktop workloads — and owned outright, so capacity commitments are commitments.
A 200G RDMA network fabric connects compute and storage tiers, keeping model loading, checkpointing, and data movement off the bottleneck list.
Hundreds of terabytes of erasure-coded distributed storage for durability, with PCIe Gen5 NVMe working tiers for active workloads. S3-compatible object access; geographic replication to our Iceland disaster-recovery site.
Declarative workload deployment across the estate. Client environments are isolated at this layer: separate namespaces, separate storage boundaries, separate audit trails.
The platform is monitored and operated by the engineers named on this site. Every inference request is logged; every operational action is attributable. Autonomous detection and remediation run under human authority, not instead of it.
The measured engineering behind this platform — benchmarks, failure analyses, system records — is published by our US research affiliate at puretensor.ai. What runs here is what is measured there.