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ScaleFlash

Funded

High-performance AI-optimized cloud storage and computing infrastructure

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About ScaleFlash

ScaleFlash delivers advanced cloud infrastructure solutions tailored for AI training, inference, and high-performance computing workloads. Their product suite includes high-speed parallel file systems, RDMA-native object storage, distributed block storage, and NVMe RAID systems, all engineered to meet the demanding data throughput and low latency requirements of AI and intelligent computing environments. ScaleFlash’s technology supports seamless integration with Kubernetes and major storage protocols such as POSIX, NFS, SMB, CSI, HDFS, and S3, enabling flexible deployment in complex enterprise ecosystems.

Targeted primarily at large enterprises in sectors like finance, semiconductor design, autonomous driving, GIS, and life sciences, ScaleFlash’s solutions unify storage, networking, and compute resources into a cohesive data platform. This approach enhances AI model training efficiency, accelerates inference, and reduces storage costs through intelligent data tiering. Their collaboration with NVIDIA and support for GPU direct storage technologies further optimize performance for AI workloads, making ScaleFlash a strategic partner for enterprises seeking scalable, high-throughput cloud infrastructure tailored to AI and HPC demands.

Key Capabilities

  • High-performance parallel file system for AI workloads
  • RDMA-native object storage optimized for intelligent computing
  • Distributed NVMe block storage for AI vector databases
  • NVMe RAID system aggregating bandwidth with redundancy
  • Seamless Kubernetes and multi-protocol integration

Integrations

KubernetesNVIDIA Magnum IO GPUDirectNVIDIA BlueField DPU

This profile was compiled by CIOPages from public sources with AI assistance, and may be incomplete or out of date. It is informational only and not an endorsement. Represent this vendor? or .

Quick Facts

www.scaleflash.com
CategoryCloud Infrastructure
PricingSubscription
HeadquartersBeijing, China
DeploymentCloud
Target SizeEnterprise