Aranya Inc. launched today with $11 million in funding, unveiling software that converts bare-metal servers into production-ready GPU clusters for AI inference in less than two days. The startup, founded last year, says it has already been tasked with managing more than $500 million worth of GPU hardware for leading AI inference providers and data centers.
The company's flagship technology, clusterdOS, is an open-source engine built on Kubernetes. It provides a framework for deploying and maintaining infrastructure through declarative configuration files, automating the orchestration of containerized workloads, networking, and storage resources across various hardware environments.
The Kubernetes gap
Kubernetes has a well-known blind spot when hardware fails. It can reschedule a pod off a failing node, but it does not diagnose the root cause. Aranya says clusterdOS fills that void.
"ClusterdOS discovers, diagnoses and resolves the hardware itself," said Christian Bhatia Ondaatje, co-founder and CEO of Aranya.
The system handles GPU thermal events, error-correcting code errors, and networking faults. It is not Kubernetes-exclusive either. ClusterdOS also encompasses virtual machine-based and SLURM job schedules and workload managers, covering environments that rely on the Simple Linux Utility for Resource Management.
"ClusterdOS is built for organization-scale computing, not for managing individual applications or isolated workloads," Ondaatje said.
A 48-hour promise
Aranya promises to transform any quantity of racked hardware into a cohesive, self-healing cluster within 48 hours, including custom storage and networking. The company says it has matched that timeline repeatedly.
"We've matched that timeline repeatedly, and no other operator does it consistently for custom architecture," Ondaatje said.
The system uses agents that "live inside the cluster continuously and adapt to what that cluster needs," rather than executing pre-scripted jobs. That adaptive approach is central to the platform's design, according to the company.
ClusterdOS also provides federated control across multiple clusters, allowing teams to manage all clusters as a unified fleet. Built-in utilization monitoring helps rightsize workloads and optimize costs, and the system enables customers to recycle idle compute, reducing operating expenses.
Security by design
The operating system operates under strict permission controls. Aranya emphasizes that the multicluster OS cannot see or access anything the organization hasn't explicitly granted it.
"The multicluster OS cannot see or access anything the organization hasn't explicitly granted it," Ondaatje said.
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"It's governed by strict multitenancy and role-based permissions at the OS level. Access is granted, not assumed."
Aranya is also introducing a natural-language interface that lets engineers manage infrastructure with plain commands, such as spinning up inference endpoints or adding nodes, without touching configuration files. The system respects existing user permissions to ensure actions are secure and auditable.
"A request in Slack resolves to the same permitted action set the engineer already has," Ondaatje said.
Funding and expansion
The $11 million total includes a $9 million seed round led by First Round Capital Holdings L.P., with participation from BoxGroup Ventures LLC, Vermilion Cliffs Ventures LLC, and Asylum Ventures. A separate $2 million pre-seed round was led by Asylum Ventures.
With the capital, Aranya plans to expand its engineering and sales and marketing teams and launch a full multicluster interface.
The company claims significant operational improvements, including dramatic reductions in downtime at both cluster and datacenter scale through proactive symptom detection. Those claims are presented without independent verification.
"Real GPU infrastructure is heterogeneous and the OS layer has to absorb that," Ondaatje said.
The AI infrastructure market faces a bottleneck in deploying GPU clusters for AI inference. Aranya's approach targets that problem directly, positioning clusterdOS as an OS layer that absorbs hardware diversity and automates remediation.
The article was updated at 10:00 EDT on September 01, 2026. It appeared in SiliconANGLE's AI section, with an image credit to SiliconANGLE/Microsoft Designer.
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