Aranya Secures $11M to Turn Bare Metal Into AI Clusters

Aranya is helping organizations operate demanding AI infrastructure with smaller engineering teams. One leading AI inference provider now manages its entire GPU fleet with just a handful of engineers using Aranya’s technology. Less than a year after its launch, Aranya is managing more than $500 million in GPUs. The company also announced $11 million in new funding, including a $9 million seed round led by First Round Capital with participation from Box Group, Vermilion Cliffs, and Asylum Ventures, along with a $2 million pre-seed round led by Asylum Ventures. The funding supports Aranya’s mission to close the gap between traditional data center capabilities and the infrastructure demands of modern AI workloads.

Inference is now the critical mass workload of the AI era, accounting for two-thirds of all compute by the end of 2026—a 2x increase in only three years. Compute infrastructure was never built for this shift, and both large-scale AI enterprises and datacenter supply are struggling to keep pace. Aranya closes that gap, converting bare metal into custom, production-ready clusters in under 48 hours for fast-growing inference providers, AI startups, and data centers. Their bleeding-edge technology forms the connective tissue between AI companies and the highly distributed GPU hardware that fuels them.

ClusterdOS, Aranya’s open-source engine built on top of Kubernetes, turns any quantity of raw bare metal servers into a self-healing, enterprise-grade, cohesive whole—completely customized. Its proprietary technology, the AI-native multicluster operating system, feels the pulse of every cluster, reasoning through the issues and acting decisively before any team member needs to be alerted. The result is direct, plain-language control over how inference or training is designed, scaled, and operated, cutting the overhead and complexity of HPC clusters.

“In less than a year, Aranya is already managing hundreds of millions of dollars in GPUs for some of the most demanding inference workloads in AI,” said Todd Jackson, Partner at First Round Capital. “The team built exactly what the infrastructure layer needs: something that makes the complexity disappear.”

The Growing Gap Between Raw Compute and Production-Ready Infrastructure
Today, deploying AI at scale means stomaching exorbitant hyperscale GPU pricing, wrangling highly custom architecture, or effectively building a cloud from scratch on bare metal. Even with a dedicated platform engineering team, most organizations struggle deeply to ship to production on a competitive timeline.

Aranya closes every one of these gaps. Any team, regardless of technical background, can now seamlessly design, scale, and operate enormous compute clusters. Their technology is already trusted to operate more than $500M of compute hardware for some of the world’s preeminent AI companies. In a case study with Hydra Host, Aranya cut cluster setup timelines from six weeks to less than 48 hours, and once deployed, their distributed operating system reduced outages by 90%.

“A growing number of customers need more than bare metal. They need a faster, more reliable path to production Kubernetes, without hiring a platform team or chasing datacenter tickets,” said Aaron Ginn, Co-founder & CEO of Hydra Host. “Our partnership with Aranya delivers exactly that. By bringing in Aranya for the Kubernetes layer, built on clusterdOS, we can now give customers a complete solution for deploying and scaling real workloads with far less complexity.”

Aranya Deploys Intelligence into the Infrastructure Itself
The fresh funding will fuel Aranya’s next chapter: serving a growing customer base and launching its groundbreaking, AI-native multicluster interface. Aranya improves:

Workflow compression: Breaks down operational barriers and reduces data center-scale and multi-data center-scale workflows from weeks to minutes.
Compute accessibility: Allows every engineering team to manage millions of dollars in compute resources, regardless of their technical background.
Natural language control: Enables teams to operate the cluster in plain language, spinning up inference endpoints, provisioning VMs, and adding or removing nodes without touching config files or CLIs.
Proactive management: Monitors the cluster and resolves issues autonomously, with AI diagnosing and remediating problems before they cascade.

“We aim to give clusters an accessibility jump similar to the spread of personal computers in the nineties,” said Christian Bhatia Ondaatje, co-founder and CEO of Aranya. “This capital plants Aranya squarely at the center of that movement—the intelligent contact surface that connects massive GPU compute to the AI teams that need it yesterday.”

Building the Team to Match the Moment
To support clusterdOS deployment and the product launch, Aranya is expanding its team across engineering and go-to-market:

Engineering: Platform engineers with depth in ArgoCD, Go, and Kubernetes; full-stack, frontend, and DevOps engineers for the dos interface; and SRE contractors for managed Kubernetes on-call.
Go-to-Market: Marketing and developer relations hires to cultivate the open-source community around clusterdOS and drive brand awareness.

Learn more about how Aranya is transforming bare metal infrastructure into production-ready AI clusters for GPU workloads at scale at the website here.