A 24-GPU cluster of NVIDIA H100 / H200 / A100, deployed in Cairo or Riyadh, on the MomentumX sovereign cloud platform. Your prompts, your weights, your audit log — none of it leaves the country. SAMA, NCA CCC-2 and PDPL aligned by design.
Hyper AI by MomentumX delivers GPU-powered, high-performance cloud environments for AI and HPC workloads — fully sovereign, open, and built for enterprise scale. Run your AI securely, regionally, and transparently — with predictable pricing and full control.
Hyper AI is MomentumX’s AI and HPC cloud platform, designed for organizations that demand both GPU performance and data sovereignty.
It allows enterprises, AI startups, and research teams to train, deploy, and scale models seamlessly — on an open, regionally hosted cloud with no dependency on hyperscalers.

Cloud GPU platform optimized for AI & HPC

Powered by NVIDIA H100, H200, A100, and Tesla T4 GPUs

Open architecture – no vendor lock-in

Dedicated tenant environments with private networking

Regional cloud zones ensuring data residency & privacy

Flexible monthly or on-demand billing
Technical Highlights:
-10 Gbps private backbone
-NVLink and RDMA interconnects for GPU clustering
-NVMe-backed local storage for fast I/O
-Scalable tenant environments up to multi-GPU nodes
Hyper AI supports all major frameworks: TensorFlow, PyTorch, JAX, Hugging Face, ONNX, RAPIDS, and OpenAI-compatible APIs.
Ideal for:
Your data stays where it belongs. MomentumX operates sovereign cloud zones in:
Engineered for extreme performance:
Simple, transparent, and flexible.
Choose between:
Hyper AI connects seamlessly with:
Built on open-source — no vendor lock-in at any layer.
Every customer receives:

AI platforms, analytics, and data science workloads

LLM hosting, training, and inference at regional scale

Shared GPU clusters for innovation

Compliant AI and data-sovereign operations
Hyper AI by MomentumX combines the best of GPU cloud, HPC power, and sovereign infrastructure — enabling you to build, train, and deploy AI with freedom and speed.
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