Cloudion
Cloudion
Explore our tier-1 enterprise rack servers built for rigorous edge computing and AI workload acceleration.
Cloudion AI Systems Ltd is a high-performance AI GPU server manufacturer dedicated to delivering next-generation computing infrastructure for global AI workloads. Built under the brand CloudionAI (https://cloudionai.com), the company specializes in scalable GPU server architectures designed for deep learning, model training, inference acceleration, and cloud data center deployment.
Founded in 2016, Cloudion AI Systems Ltd has developed a strong reputation in the global AI hardware industry, supported by years of engineering expertise and continuous innovation in high-density computing systems.
The company operates a modern manufacturing facility covering approximately 18,600㎡, equipped with advanced assembly lines, automated testing systems, and precision engineering workshops to ensure consistent product quality and performance stability.
With annual export revenue ranging from USD 12 million, CloudionAI serves international markets across North America, Europe, and Southeast Asia. The company has accumulated 7 years of export experience and over 12 years of industry expertise in high-performance computing and server infrastructure.
Quality assurance is strictly enforced through ISO-based quality management systems, thermal stress testing, burn-in testing, and full system load validation. Product inspection methods include automated optical inspection (AOI), hardware-in-the-loop testing, and multi-stage functional verification. The quality control team consists of 48 professional inspectors ensuring strict compliance with global standards.
CloudionAI maintains a diversified trade background with strong participation in both OEM and ODM markets. Its supply chain is supported by more than 1,100 upstream partners, including semiconductor suppliers, PCB manufacturers, cooling system providers, and enterprise-grade component vendors.
The company’s primary markets include enterprise AI infrastructure providers, cloud service operators, research institutions, and data center integrators. CloudionAI also offers extensive R&D capabilities, supporting custom GPU server configurations, liquid cooling solutions, and hybrid cloud deployment architectures.
Customization options include chassis design, GPU configuration, power architecture optimization, thermal system engineering, and firmware-level tuning. In the past year, CloudionAI launched 86 new products, reflecting its strong innovation pipeline. The R&D department consists of approximately 320 engineers specializing in AI hardware design, distributed computing systems, and high-efficiency thermal management technologies, ensuring continuous advancement in next-generation GPU server solutions.
Discover enterprise-class storage arrays, RAID controllers, and high-density GPU deployment nodes.
A visual look into our precision assembly lines, automated testing labs, and high-capacity manufacturing cleanrooms.
Expert answers regarding global procurement, server customization, and CDN infrastructure deployment.
CloudionAI operates an 18,600㎡ advanced manufacturing facility backed by 12+ years of industry expertise. We combine rigorous ISO quality management systems, 320+ expert R&D engineers, and a robust network of 1,100+ upstream partners to deliver enterprise-grade, highly reliable server hardware worldwide.
Yes, we specialize in both OEM and ODM partnerships. We offer extensive customization options including specialized chassis design, multi-GPU configurations, customized power architectures, advanced liquid/air cooling thermal engineering, and firmware-level tuning tailored to your specific workloads.
Every server undergoes stringent quality validation including ISO-compliant inspection protocols, automated optical inspection (AOI), thermal stress testing, burn-in testing, and full system load verification conducted by our dedicated team of 48 professional quality control inspectors.
Our high-performance servers are deployed globally across enterprise AI infrastructure providers, cloud data center operators, content delivery networks (CDNs), deep learning research institutions, and large-scale model training and inference clusters.
