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aranya

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AI inference and training companies needing rapid deployment of production-grade GPU clusters. Automates GPU orchestration from kernel drivers to federation across clusters. Custom architecture design including networking, storage, GPU scheduling, and orchestration layers like Kubernetes, VMs, or Slurm.

THE PRODUCT, BEYOND THE PITCH

Editorially reviewed · Sources checked Sep 10, 2026

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A good fit for

  • AI companies requiring fast production cluster deployment and datacenters/neoclouds needing AI compute platform capabilities without building their own platform team.

Know the limitations

  • Currently targets datacenters and neoclouds at 20MW and below, implying scale limitations beyond that size.

What you can do

  • AI inference and training companies needing rapid deployment of production-grade GPU clusters.
  • Datacenters and neoclouds with hardware but lacking AI compute platforms, enabling them to offer AI compute services without a dedicated platform team.

Features

  • Automates GPU orchestration from kernel drivers to federation across clusters.
  • Custom architecture design including networking, storage, GPU scheduling, and orchestration layers like Kubernetes, VMs, or Slurm.
  • Observability features from individual GPU temperature monitoring to federation-wide traffic analysis.
  • Role-based permissions at the OS level to control access securely.
  • Support for NVIDIA and AMD driver stacks and a Cilium/eBPF network layer.

Integrations

  • Extends to VM-based and Slurm environments beyond Kubernetes.

Platforms & data export

Not confirmed yet.

THE COST FOR YOUR TEAM

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Published plan prices for your team size and usage. Results update as you type. Taxes, currency conversion and unlisted add-ons are excluded, and anything the source did not state is called out rather than guessed.

Known monthly subtotal

$0.00/month

1 of 1 tools could not be priced with these inputs, so this is not the full cost.

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Tool / planMonthlyPer yearWhat this assumes
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A practical workflow

  1. Aranya designs the cluster architecture based on specific workload requirements, including custom networking, storage, GPU scheduling, and orchestration layers.
  2. Aranya automates all operational tasks from kernel drivers to cluster federation, enabling rapid cluster deployment and management.

Based on the sources below. Editorial review does not imply hands-on product testing.

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