Bare metal to Production in 48 hours.
Tailored to your workloads.

Aranya builds and operates production AI infrastructure. We take teams from bare metal to live in production within 48 hours — with the full stack configured for their specific workload. Powered by clusterdOS, our open-source distributed operating system.

Teams where compute is a core product constraint. AI inference and training companies scaling GPU workloads, ML platforms running at the edge of what managed cloud Kubernetes can handle, and companies that want production-grade infrastructure without building out a platform team. If your engineers are spending more time on infra than on product, that's the conversation.

Every cluster is architected around your requirements: custom networking, storage, GPU scheduling, and inference or training setup — not a generic Kubernetes template you adapt to fit your workload. A high-throughput inference deployment looks different from a distributed training setup. We build for the actual architecture. That starts before deployment: Aranya specifies the hardware and infrastructure requirements your data center needs to meet, then deploys and runs the full stack on top.

Under 48 hours from bare metal to production-ready. The typical build-your-own approach takes four to six weeks. We've cut that to under two days, with production monitoring live from day one.

ClusterdOS is the distributed operating system layer for Kubernetes. K8s is the kernel; clusterdOS is everything on top. GitOps-native configuration, self-healing observability, inference and training tooling, storage, networking, and GPU management, all production-configured out of the box. Push to Git; the cluster manages itself.

EKS, GKE, and AKS give you a Kubernetes cluster, then the rest is on you. They're not built for the configuration demands of inference or training workloads: custom GPU scheduling, high-throughput storage, specific networking setups. You're also paying hyperscaler margins the whole time. ClusterdOS sits on top of Kubernetes, K8s is the kernel, clusterdOS is the operating system, with the full production stack configured for your specific workload. No generic template, no platform team required to run it.

No. That's kind of the point. If you can git push, you can manage clusterdOS.

Yes. We believe the future of infrastructure is community-built. You can find us on GitLab and we welcome contributions.

Dos is a proactive AI experience for your cluster. Instead of waiting for you to run a command, it surfaces what needs attention and can act once you approve, all in plain language. You describe what you want; it figures out how. It's how you work with clusterdOS, not just through it. Launching soon.