Power the Next Generation of AI with Industry-Standard AI Factories

Sovereign AI Clouds: Retain full control of data, workloads, and compliance, critical for service providers in regulated industries or national markets.

Multi-Tenant Service Delivery: Securely isolate environments for each tenant, ensuring data privacy, high performance, and resource efficiency at scale.

GPU & Accelerator Scarcity: Maximize utilization and flexibly allocate premium hardware for both training and inference.

Hybrid, Edge, and Multi-Cloud Expansion: Deploy across diverse locations and seamlessly manage AI workloads everywhere.

Rapidly deploy sovereign, multi-tenant GPU-powered AI clouds on your preferred hardware, in your country, under your full control

Offer differentiated AI-as-a-Service to your customers, with the flexibility to scale, partition, and monetize infrastructure for both inference and training

Integrate seamlessly with major GPU and accelerator vendors, leveraging open standards, and with your choice of cloud, on-prem, bare metal, or edge environments

Full Sovereignty: Complete control of infrastructure, data, and compliance, with no vendor lock-in or cloud provider dependency.

Composable Architecture: Build and adapt your AI Factory using declarative templates for compute, storage, GPU, and networking layers.

Multi-Tenancy at Scale: Secure isolation of customers and workloads at every layer, including bare metal, VM, Kubernetes, networking, DPU and GPU.

Unified Lifecycle Automation: End-to-end automation of bare metal, virtualized, and cloud-native environments with a single control plane.

Advanced Observability & FinOps: Centralized real-time monitoring, cost tracking, and resource optimization built-in.

NVIDIA: Full-stack integration with the NVIDIA Enterprise AI Stack, MIG, BlueField DPUs, Infiniband, advanced collective communication offload (SHARPv3), and more.

AMD: Comprehensive support for ROCm, MxGPU, SmartNICs/DPUs, and Ethernet-based AI fabrics.

Intel: Support for Gaudi accelerators, optimized RDMA, advanced packet spraying, and open Ethernet-based scaling.

3rd Party & Open Source: Deep catalog of validated integrations—SLURM, KubeFlow, AIBrix, llm-d, Gcore, ClearML, and more.

Application Platform Layer: Accelerate the launch of real AI services—generative AI, computer vision, agentic RAG, and more, with a curated catalog and managed PaaS options.

Platform Layer: Automate bare metal, VM, and Kubernetes clusters across data center, cloud, and edge.

Compute & GPU Layer: Maximize utilization with fractional provisioning, advanced GPU sharing, and support for all major vendors’ latest features.

Storage & Network: High-throughput NVMe-oF, multi-tiered storage, and AI-optimized networking, including RDMA, Infiniband, RoCEv2, SmartNIC/DPUs, and more.

Security & Compliance: Zero trust, hard multi-tenancy, confidential computing, and sovereignty for regulated sectors and cross-border workloads .

Ultra-low latency, multi-region, multi-cloud inference

Smart routing to the nearest compliant data center

Scalable to any number of customers, clouds, or edges

Granular monitoring, usage-based billing, and operational transparency

Explore detailed architectures, deployment models, and operational best practices

Learn how to offer differentiated, monetizable AI services on sovereign, secure clouds

Discover how to integrate with NVIDIA, AMD, Intel, and open-source ML ecosystems