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Enterprise AI Factory

Enterprises across industries such as financial services, manufacturing, healthcare, and retail are rapidly adopting GPU infrastructure to support AI initiatives including generative AI, digital twins, simulation, and predictive analytics. Unlike Neoclouds, enterprises deploy GPUs primarily for internal use by business units, subsidiaries, and development teams.

Problem​

Enterprise AI infrastructure introduces several challenges:

  1. Secure resource isolation: Large enterprises operate across multiple departments, subsidiaries, and countries. Infrastructure must enforce strong separation between teams handling sensitive data.
  2. Regulatory compliance: Global enterprises must comply with regional data sovereignty regulations that restrict where data and AI workloads can run.
  3. Efficient GPU utilization: Without shared dynamic infrastructure platforms, GPUs are often statically assigned to teams and remain idle when not in use.
  4. Operational complexity: Managing GPU clusters requires specialized expertise in infrastructure provisioning, orchestration, networking, and AI software environments.

Solution​

Armada Bridge is a GPU management platform that enables enterprises to deliver GPU infrastructure as Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and AI-as-a-Service (AIaaS) to internal users. Bridge provides secure multi-tenancy, lifecycle management, and operational automation across GPU clusters, allowing organizations to safely share expensive GPU infrastructure among multiple tenants while maximizing utilization and simplifying operations.

Bridge enables enterprises to operate GPU infrastructure as a shared internal AI platform. Bridge enforces secure multi-tenancy across infrastructure resources while allowing internal teams to access GPU resources through multiple service models including:

  • Bare metal GPU instances
  • Virtual machines
  • Containers
  • Managed Kubernetes clusters
  • AI development environments
    • LLM-as-a-Service
    • Jupyter Notebooks
    • Schedulers such as KAI and SLURM
    • MLOps
    • 3rd party Agentic, fine-tuning, RAG, and more

Bridge enables enterprises to dynamically allocate GPU resources from 1/7 of a GPU to 100s of clustered GPUs across teams, maximizing infrastructure utilization. Centralized observability and operational automation reduce operational overhead while ensuring consistent governance and security policies across enterprise environments.

For enterprises that do not have a brick-and-mortar datacenter available, Armada can also provide Modular Data Centers branded Armada Galleon.

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