Aircloud exists because AI teams shouldn't have to choose between fast, affordable GPU access and meaningful security guarantees. We built the infrastructure to deliver both — with a tiered trust model that lets you match isolation depth to each workload's actual risk.
Mission
"Make private GPU infrastructure accessible to every AI team — not just the ones with hyperscaler contracts and infrastructure teams to manage them."
The GPU infrastructure market asks you to pick: cheap and fast, but insecure — or secure, but slow and inaccessible. Teams serving production AI workloads have been stuck in this trade-off for years. Aircloud is the third option.
The answer wasn't to build another GPU rental cloud with a better UI. It was to build a supply network with layered trust guarantees — so teams could get the isolation level they actually need without paying hyperscaler prices for workloads that don't require it.
Three isolation tiers — Trusted, Secure, Community — each with documented technical boundaries and contractual protections. You choose isolation depth per workload. Your development environment doesn't need the same guarantees as your production inference server.
We tell you where your GPU is, who operates it, and what protections apply. Every tier discloses its operator class, isolation model, and SLA structure. No mystery infrastructure, no undisclosed subprocessors.
Provision a serverless GPU in seconds via API. Or run an enterprise procurement process with volume pricing, SLA terms, and dedicated support. The same platform serves both paths — you don't have to choose a vendor track before you know your requirements.
Serverless billing that actually means something. No reserved pod tricks, no minimum session charges, no artificial capacity floors. Your costs scale exactly with your usage — whether that's a 30-second embedding job or a 30-day training run.
The Aircloud team comes from hyperscalers, GPU infrastructure companies, and security-focused cloud providers. We've run the systems we're replacing. We know exactly where they fall short.
Background in distributed systems and cloud infrastructure. Previously built GPU orchestration at scale.
Infrastructure engineering background. Worked on hyperscaler GPU allocation systems and Kubernetes scheduling.
Data center operations and network engineering. Deep experience with colocation contracts and physical security audits.
Security engineering and compliance at cloud infrastructure companies. Led SOC 2 and ISO 27001 programs.
Our investors have built and funded infrastructure companies. They understand the long cycles, the trust required, and the value of getting it right. Investor details will be announced shortly.
Early team. High ownership. The problems are real and hard — GPU scheduling, isolation architecture, supply network operations, enterprise security. If this is what you want to work on, we should talk.
jobs@aircloud.com