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Proven at Scale

Our software and operations stack has been validated across some of the world's most demanding GPU cluster environments.

Cluster Management See the Cluster Operations layer →
1,000+

Leading Autonomous Driving Company

One of Asia's top three autonomous driving companies deployed its first thousand-card GPU compute cluster on our cluster management platform, network integration, and ongoing operations services.

Scale · 1,000+ GPU cards Services · Cluster management, network integration, ops Go-live · April 2025
4,000

Western Data Valley — National Compute Hub

A national compute hub serving frontier large model developers, sited in the only province designated as a "dual-center" node of the national integrated computing network. Our platform provided cluster management software and ongoing operations for 4,000 NVIDIA GPU cards in a multi-tenant environment.

Scale · 4,000 NVIDIA GPU cards Services · Cluster management, ops Go-live · April 2023
12,288

Preferred Networks, Japan

Japanese AI research company and developer of the open-source framework Chainer and the PaintsChainer application. Built the country\u2019s largest GPU cluster — 12,288 GPUs across P100×8 and V100×8 configurations — alongside its own AI chip programme.

Scale · 12,288 GPUs Services · Cluster management, performance optimization Go-live · April 2021
Network Architecture See the Network Architecture layer →

World's First Scheduled-AI-Fabric Deployment

Deployed with a leading global short-video platform alongside DriveNets and Broadcom — the first production deployment worldwide of a Scheduled-AI-Fabric built on our DDC-based network architecture.

GPUs1,280
Fabric20 NCP · 20 NCF · cell-based
Ports400 Gbps
Outcome30% JCT improvement
Inference Optimization See the Model Optimization layer →

E-Commerce AI Image Processing

An e-commerce platform's AI image editing tool accelerated with our inference optimization layer — minimal code changes, direct PyTorch compatibility.

Outcome · Best-in-class acceleration versus comparable engines, with simplified deployment.

Telco AI Video Content Generation

A carrier's AI custom video ringback tone project — a latency-sensitive, high-volume generative workload — accelerated on our inference platform, with multi-resolution support and LoRA hot-swap across SVD, Diffusers, ComfyUI, and WebUI.

Outcome · 40%+ average performance uplift, ~100% inference speedup for video generation, 10% VRAM reduction.
Key Platform Metrics
10,000+ GPU cards under active management
<1 ms Cluster fault recovery time
55% Peak GPU utilization in training
Total GPU cards managed (cumulative)10,000+
Thousand-card clusters deployed4+
Ten-thousand-card clusters1
Cluster fault recovery time<1 ms
Training GPU utilization (peak)Up to 55%
Ops staffing reduction via automation~50%
Inference throughput uplift (LLM)Up to 2.5×
Inference latency reduction (LLM)Up to 2.7×
End-to-end inference speedup (diffusion)Up to 3×

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