Aranya Raises $11M for Software It Says Can Ready GPU Clusters in 48 Hours
The startup is targeting the operational work that follows GPU procurement: configuring workloads, storage and networking into infrastructure that can run AI services. Its deployment and scale figures are company-reported.
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3 key pointsAranya’s $11M financing backs an attempt to make GPU infrastructure deployment more repeatable across heterogeneous fleets. Its open-source clusterdOS, built on Kubernetes and compatible with VMs and Slurm, is designed to configure, monitor, and repair bare-metal clusters, with planned multicluster controls and plain-language operations. The company reports managing over $500M in GPU hardware and cites a Hydra Host...
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The round combines a $9M seed led by First Round Capital with a $2M pre-seed led by Asylum Ventures.
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clusterdOS aims to address overheating GPUs and network faults at the source, rather than only moving workloads elsewhere.
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Aranya plans a permissioned multicluster interface for creating inference endpoints and adding or removing nodes through plain-language requests.
Aranya has raised $11 million to build software for a stubborn stage of AI deployment: turning delivered GPU servers into clusters that can run production workloads. The company says its open-source clusterdOS engine can convert racked bare-metal hardware into customized AI clusters in under 48 hours.
The financing includes a $9 million seed led by First Round Capital and a $2 million pre-seed led by Asylum Ventures. Box Group, Vermilion Cliffs and Asylum joined the seed, while Founder Collective, Parable VC and Uncommon Ventures participated in the pre-seed.
Turning hardware into an operating system
ClusterdOS is built on Kubernetes, software used to coordinate applications running in containers. Aranya says its engine uses configuration files to deploy and maintain AI infrastructure, coordinating workloads, networking and storage across different hardware environments.
The company says the product also works with virtual machines and Slurm, a system for scheduling computing jobs. Its pitch is to handle failures closer to their source: Aranya says clusterdOS can identify and resolve problems such as overheating GPUs and network faults, rather than only moving work away from a failing server.
A control layer beyond one cluster
Aranya says clusterdOS provides federated control across multiple clusters. It plans to use the funding to expand engineering, sales and marketing, and to launch a full multicluster interface.
What the planned interface is meant to change
- Engineers could create inference endpoints using plain-language requests instead of directly editing configuration files.
- They could add or remove nodes through the same interface.
- Aranya says requests would remain limited by each user’s existing permissions, preserving an auditable action set.
The company’s public performance evidence remains limited. Aranya says a deployment with Hydra Host cut cluster setup from six weeks to less than 48 hours and reduced outages by 90%; those are company and partner claims, not independent benchmarks. The funding now tests whether that approach can become a repeatable control layer for varied GPU fleets.
Sources
- prnewswire.comAranya Secures $11M to Convert Bare Metal into Custom, Production-Ready Clusters in 48 Hours with Full Visibility into Inference and Training Management
- siliconangle.comAranya raises $11M to turn bare-metal servers into AI clusters in less than 48 hours - SiliconANGLE
