AI development on Kubernetes-managed GPU infrastructure

Give your platform teams the AI layer their engineers need

Spectro Cloud Palette manages your Kubernetes infrastructure, covering cluster lifecycle, GPU operators, governance, and compliance. Saturn Cloud turns that infrastructure into a self-service token factory where engineers fine-tune, deploy, and serve models from day one.

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Why Spectro Cloud + Saturn Cloud

Full-stack Kubernetes management.
A token factory platform you don’t have to build.

Spectro Cloud gives platform teams declarative control over Kubernetes clusters from edge to data center to cloud. Saturn Cloud gives those same teams a proven token factory platform they can deploy on top, instead of spending months assembling one internally.

No internal platform build

Most organizations solve the Kubernetes infrastructure problem and then face a second one: delivering a usable AI development experience to their teams. Saturn Cloud eliminates that gap. Deploy a complete AI platform on your Palette-managed clusters instead of building and maintaining one yourself.

Fine-tuning, serving, and inference out of the box

Engineers fine-tune open models (full-weight or LoRA), deploy to OpenAI-compatible inference endpoints, and meter usage per token. The platform also provides managed environments, distributed training orchestration, scheduled jobs, and experiment tracking, all from a single interface.

Full-stack, declarative control

Palette manages everything from bare metal and OS to Kubernetes, GPU operators, and networking with a GitOps-driven, declarative approach. Saturn Cloud inherits that foundation and delivers developer tooling without adding operational complexity.

Enterprise and government ready

Palette VerteX delivers FIPS 140-3 compliance and FedRAMP authorization for government and regulated industries. Saturn Cloud runs on your infrastructure, under your governance. Together, they meet the requirements of defense, healthcare, and financial services environments.

How it works

Saturn Cloud on Spectro Cloud Palette

Saturn Cloud

Fine-tuning · Inference endpoints · Per-token billing · Jobs · Deployments · Experiment tracking

Spectro Cloud Palette

Cluster lifecycle · GPU operators · GitOps profiles · Governance

GPU infrastructure

Bare metal · Public cloud · Private DC · Edge · Air-gapped

1. Palette manages infrastructure

Full-stack Kubernetes lifecycle from bare metal to cluster. GPU operators, NVIDIA driver stacks, networking, and storage are declared in profiles and applied consistently across every environment.

2. Saturn Cloud provides the platform

Deploys directly on Palette-managed Kubernetes clusters. Engineers self-service their own fine-tuning jobs, inference endpoints, and training runs. No YAML, no cluster administration, no DevOps bottleneck.

3. Engineers start shipping

Log in, pick a GPU, upload a dataset. Fine-tune a model, deploy it to an inference endpoint, and start serving tokens. Pre-configured with CUDA, drivers, and standard AI frameworks.

The difference

Spectro Cloud + Saturn Cloud vs. building it in-house

Palette solves infrastructure lifecycle. Saturn Cloud solves fine-tuning, inference, and the developer experience. Together they replace months of internal platform engineering.

Building internally

Spectro Cloud + Saturn Cloud

Months of engineering to assemble fine-tuning pipelines, inference serving, and billing infrastructure

Production-ready AI platform deployed on your Palette clusters in days

Custom auth integration, access controls, and resource management per team

SSO, RBAC, shared projects, and cost tracking included

Ongoing maintenance burden on your platform engineering team

Managed by Saturn Cloud, including updates, patches, and support

GPU drivers, operators, and K8s versions managed separately from developer tooling

Palette handles the stack, Saturn Cloud handles the experience

GPU idle time from manual provisioning and no automatic reclamation

Automatic idle detection and shutdown with GPUs reclaimed when unused

Different tooling for cloud, on-prem, edge, and air-gapped environments

Same experience everywhere Palette runs, from data center to edge

Built for platform teams running AI workloads

Who this is for

Organizations that manage Kubernetes at scale and need
to deliver AI capabilities to their teams and tenants.

Neocloud GPU providers

Offer tenants managed fine-tuning, inference endpoints, and per-token billing on your GPU infrastructure. Palette manages the Kubernetes layer, Saturn Cloud delivers the platform on top. Differentiate on capabilities, not just compute hours.

Enterprise AI teams on private infrastructure

Run training, fine-tuning, and inference on GPUs you own, in your data center, under your security policies, with a development environment your engineers actually want to use.

Sovereign and regulated environments

European data residency, air-gapped deployments, government and defense workloads. Infrastructure stays under your control. Saturn Cloud runs entirely within your perimeter.

HPC centers and research institutions

Give researchers self-service GPU access with proper resource management, experiment tracking, and reproducible environments, without exposing them to Kubernetes complexity.