GLabs Enterprise

GLabs Enterprise — Vault & POD

Storage and Pre-Integrated Compute, One Chapter

Why Vault and POD Share a Page

Vault (storage) and POD (pre-integrated GPU clusters) solve different problems, but they ship the same way: neither asks you to design a data center first. Vault drops into existing infrastructure as a high-throughput storage tier; POD arrives pre-cabled and ready to power on. Where a customer needs both, GLabs delivers them as one integrated order — not two separate procurement conversations.

GLabs Vault

SpecDetail
ProtocolNVMe-oF, GPU Direct Storage
ThroughputUp to 120GB/s aggregate
CapacityUp to 10PB (Vault Core); Vault Infinite for cold-tier archive
UseHPC parallel storage tier, checkpoint/restart, model & dataset storage

GLabs POD

SpecDetail
Scale4 to 40 GPUs
DeliveryPre-integrated, pre-cabled — ships complete
Target buyerOrganizations without an existing data center
NetworkingFactory-validated fabric, rack-and-roll

Why POD, Not GPU Servers

GPU Servers assume a facility already exists to receive them — power, cooling, racks, network fabric. POD is for the organization that doesn't have that yet: the cluster arrives pre-cabled and validated, so it goes from delivery to first job without a separate data-center build.

Also Available: NVIDIA DGX SuperPOD — Deployed & Supported by GLabs

PlatformFull-stack turnkey AI infrastructure — compute, storage, networking, and software unified
ComputeBlackwell- and Rubin-generation NVIDIA DGX systems
ScaleFrom a single SuperPOD to tens of thousands of GPUs
ManagementNVIDIA Mission Control and Base Command
Certified storage partnersDDN, Dell, IBM, NetApp, Pure Storage, VAST, WEKA
PositioningShared NVIDIA-partner tier for GLabs Vault + POD customers scaling beyond a single rack

Where It Shows Up

  • HPC Storage Layer — Vault sits under Lustre/BeeGFS as the hot-and-cold tier (140GB checkpoint: 2.2s at 120GB/s vs. ~70s on commodity NAS).
  • Foundation Model Pre-Training & AI Data Centers — POD and DGX SuperPOD give enterprise and sovereign customers a pre-integrated path to multi-rack scale without a from-scratch build.

Used across: AI Solutions (GLabs AI Stack), HPC Solutions (GLabs HPC)

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