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Sensitive data stays separate
What may reach patient data is set by how projects and access are arranged, and held to across the platform.
Healthcare organisations carry two pressures at once: the duty to guard sensitive data and the duty to spend carefully. Compute treats separation, residency and access records as configured properties of your account, and runs the same machines, databases and models for less than the leading cloud charges for them.
Used by digital health startups, clinics, research groups and large health systems.
What this looks like in practice
What may reach patient data is set by how projects and access are arranged, and held to across the platform.
Who reached what, and when, answerable as a lookup rather than an investigation.
GPU capacity at 30% under the leading cloud on-demand, billed by the second, so analyses run when they are ready.
The same infrastructure for less, with no commitments, means more of the budget reaches patients.
Healthcare often protects data by making everything slower and more costly than it needs to be. Separation that is structural lets scrutiny focus where the data actually is, and a lower price for the same infrastructure means caution does not have to cost so much.
Who could see this record, and who did. In many organisations that takes days and a careful person reading logs. On Compute access is granted explicitly and every grant and use is kept on record, so the answer is a lookup. Nothing depends on anyone having kept a separate log beside their actual work.
Draft clinical summaries and letters with AI inference, under the leading cloud’s price for the same model, with a clinician approving each.
Train and evaluate models on H100 and A100 instances by the second, then release them.
Booking, reminders and results portals on Panel, changed on an ordinary release cadence.
Where patient data lives is configured and held to across databases, storage and machines.
Compared with the leading cloud's own published on-demand prices, US East. Every comparison.
Ask us directly about the specific attestation or agreement your organisation requires, and we will tell you plainly whether we hold it today. We will not imply one we do not have.
Through projects, databases and access grants arranged so that only what should reach patient data can. That arrangement is configured once and held to across the platform.
Yes, and many organisations do. Research and analysis workloads benefit first from per-second GPUs at 30% under the leading cloud, and clinical systems can follow when you are ready.
Yes. The free allowances let a small team build and test, with usage billed at published prices beyond them. The same platform serves large health systems.
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.