Saturn Cloud Integrates NVIDIA DSX OS into AI Token Factory

Saturn Cloud has integrated NVIDIA DSX OS into its platform, giving neocloud operators a way to turn NVIDIA infrastructure into a token-metered service they can sell.

Saturn Cloud, the AI token factory platform and an NVIDIA portfolio company, announced that it has built support for NVIDIA DSX OS into its platform. Saturn Cloud packages NVIDIA DSX OS, which provides inference serving, scheduling, and fleet operations, together with its own tenant, metering, and billing layer, so neocloud operators can run a production inference service on NVIDIA infrastructure without assembling the stack themselves. The integrated platform is available now for AI cloud operators to evaluate.

The Production Layer on DSX OS

NVIDIA DSX OS is open, modular software with a powerful set of NVIDIA’s components for operating AI infrastructure at scale. It gives an operator the building blocks for inference, scheduling, and fleet operations, from NVIDIA Dynamo and NVIDIA Grove to KAI Scheduler, NVSentinel, and Fleet Intelligence. Neoclouds are seeking a commercial layer on top: the per-token metering, per-tenant billing, and chargeback that turn served tokens into something an operator can price and sell. That layer is inherently the operator’s to build, and it is the part Saturn Cloud provides.

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On the serving side, Saturn Cloud runs NVIDIA Dynamo as the distributed inference and serving layer, with disaggregated prefill and decode. Dynamo is engine-agnostic, driving vLLM, SGLang, or TensorRT-LLM as the underlying serving engine. NVIDIA Grove orchestrates the multi-node workloads. Scheduling runs on NVIDIA KAI Scheduler, which places workloads with GPU awareness, allocates fractional GPUs, and enforces quotas across tenants. NVIDIA Fleet Intelligence and NVSentinel handle fleet-wide health monitoring and failure detection. Operators can serve NVIDIA Nemotron models alongside other open and partner models.

On top of all of it, Saturn Cloud adds per-token metering, quotas, and billing per tenant. The operator gets a serving stack built on NVIDIA’s tools and a way to sell what it produces, in one platform.

“NVIDIA DSX OS gives AI cloud operators a strong foundation for serving models,” said Sebastian Metti, founder of Saturn Cloud. “We add the piece that lets them turn it into a service they can sell to their own customers, instead of just renting out GPU hours.”

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What an Operator Runs

Saturn Cloud runs an operator’s open and partner models in production on a single, production-grade control plane that’s versioned and managed. Customers fine-tune on the operator’s own infrastructure and serve the results alongside the base models, with no separate training stack to stand up. Operators serve each model the way the workload demands with dedicated single-tenant for isolation, or shared multi-tenant for density, and Saturn Cloud handles the tenant boundary, quotas, and per-tenant metering either way. Data and inference stay inside the operator’s boundary under the security and governance controls that regulated customers require.

Usage is tracked per tenant against quotas, so faster hardware and better utilization turn into margin rather than a lower hourly rate. The result is infrastructure an operator can sell, not just operate.

Where Saturn Cloud Runs

Saturn Cloud deploys across public cloud, private cloud, and on-premises environments, and runs on NVIDIA AI infrastructure wherever the operator has it, including neoclouds adopting the NVIDIA DSX platform stack.

For telcos, sovereign AI clouds, and enterprise operators, the shape is the same. NVIDIA’s tools serve the tokens. Saturn Cloud does the production engineering that turns them into a service an operator can run and sell.

“AI factories are moving into production, and operators are looking to expand their offerings with value-added services,” said Warren Barkley, vice president of product management at NVIDIA. “Saturn Cloud’s integration with NVIDIA DSX OS, including per-token metering and tenant billing, gives customers AI production-ready services customers want, without the complexity of assembling and integrating the stack themselves.”

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