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Burst capacity, fairly priced
H100, A100 and L40S instances at 30% under the leading cloud on-demand, billed by the second for the length of the run.
Manufacturers use compute in bursts: a simulation before a design freeze, a retraining run for a vision model, a planning job at the end of the month. Paying for that capacity all year is wasteful, and paying the leading cloud on-demand for it is expensive. Compute bills GPUs and CPUs by the second at 30% under the leading cloud for the same hardware.
Used by single-site manufacturers, multi-plant groups and Fortune 500 industrials.
What this looks like in practice
H100, A100 and L40S instances at 30% under the leading cloud on-demand, billed by the second for the length of the run.
Cloud Services queues take readings from the floor; CosmoBase keeps them for analysis.
Control logic, models and configuration in CodeGraph, with a history of who changed what and when.
Run the big planning job on large CPU instances when it is needed, then stop paying for them.
Manufacturing has long understood that capacity sitting idle is cost without output. The same discipline applies to computing. Per-second billing at a lower price means engineering and quality teams can use as much as a problem needs, then hand it back.
Engineering teams queue for shared clusters, and design decisions get made on the analyses that happened to fit. With GPU and CPU instances available by the second at 30% under the leading cloud on-demand, the question changes from whether there is capacity to whether the answer is worth the cost — and that cost is published before the run starts.
Vision models trained on GPU instances and served on L40S, so quality checks cover the line rather than a sample.
Predictive models over machine telemetry, retrained as often as the data warrants.
Supplier portals hosted on Panel with access granted and recorded per organisation.
Work instructions and engineering records versioned in CodeGraph alongside the systems they describe.
Compared with the leading cloud's own published on-demand prices, US East. Every comparison.
Yes. Control systems usually stay where they are. Compute takes the data, analysis, simulation and planning work that benefits from capacity on demand.
Each plant or business unit can be its own project, with its own access, data and itemised costs, separated as a configured property.
Access records, separation and residency are configured properties of your account. For a specific standard or attestation, ask us directly and we will tell you plainly whether we hold it today.
The per-second price of the instance multiplied by the length of the run. Every instance price is published with the leading cloud’s price for the same hardware beside it.
Run agents, the tools they call and the models behind them on one platform, billed by the token and the second, for less than the same work costs on the leading cloud.
Host the landing pages, attribution pipelines and onboarding flows that bring customers in, and spend less on the infrastructure than you would on the leading cloud.
Run campaign sites, personalisation, content pipelines and marketing data on one platform that costs less than the leading cloud for the same machines and models.
Run the forms, enrichment jobs, scoring models and routing that turn interest into leads, for less than the same infrastructure costs on the leading cloud.
Run CRMs, sales data, call analysis and AI assistants on one platform, priced under the leading cloud for the same machines, databases and models.
Host creator platforms, media processing, storefronts and AI tools on infrastructure that bills by the second and costs less than the leading cloud for the same machines.
Begin with one workload. Keep what you have running. Decide whether to continue once you have seen it carry something real.
No migration required to begin. Nothing to tear down if you stop.