Dedicated GPU clusters with predictable performance, full data control, and the flexibility to deploy on-premise, in colocation, or in a hybrid model. Arc Compute handles the infrastructure so your teams can focus on AI.
Every cluster is configured around your actual compute requirements. Training, inference, or mixed workloads each get a tailored GPU, networking, and storage configuration.
Your data stays on infrastructure you own and control. No shared environments, no third-party data handling, and no ambiguity about where your models and training data live.
On-premise in your own facility, in colocation we source and manage, or a hybrid of both. You choose the deployment model that fits your security, compliance, and operational requirements.
Know what your compute costs per month, per quarter, and per year. No variable pricing tied to demand spikes, no surprise egress fees, and no billing complexity.
Purchase your infrastructure outright or consume it as a managed service. We support both models and can help you structure the approach that aligns with your budget and procurement process.
For teams that want hands-off infrastructure, Arc Compute offers end-to-end management covering monitoring, optimization, maintenance, and support.
Shared GPU instances mean variable performance depending on who else is using the same hardware. Your workloads compete for the resources you are paying for.
Your cluster is yours. Full hardware capacity, every time, with no contention from other tenants and no surprise throttling.
Cloud GPU spend is difficult to forecast and tends to grow faster than the workloads driving it. Egress and storage fees compound the problem.
Owned or managed infrastructure gives you a fixed cost structure that improves over time as utilization increases. Predictable today, more predictable next year.
Sending proprietary data and model weights to a third-party cloud introduces risk that many enterprises are not comfortable with.
Dedicated infrastructure keeps everything under your control and supports compliance with internal governance, HIPAA, SOC 2, and other frameworks.
Standing up GPU infrastructure internally requires expertise in hardware selection, system integration, cooling, networking, and ongoing operations.
Arc Compute brings that expertise so you do not need to hire for it. We design, build, deploy, and run the infrastructure so your team can stay focused on AI.

We evaluate your workloads, security requirements, deployment preferences, and growth plans. From there, we design a cluster architecture tailored to your organization.
.avif)
We design your solution, source hardware, integrate all components, and validate every system against your specifications and performance requirements before deployment.
.avif)
Systems are built and deployed into your facility or a colocation environment we source on your behalf. Installation, configuration, and commissioning are all included.

Ongoing monitoring, optimization, and support. Fully managed by Arc Compute or operated by your team with our support. As your needs grow, your infrastructure grows with you.
We have designed and deployed dedicated GPU clusters for organizations across financial services, healthcare, and technology. We understand procurement processes, compliance requirements, and the stakeholder landscape.
Data control, isolation, and compliance alignment are built into every deployment from the start. We work with your security and compliance teams to ensure the infrastructure meets your standards.
CAPEX, OPEX, or a hybrid of both. We help you structure infrastructure ownership in a way that fits your budget cycles and procurement processes.
From initial design through deployment, operations, and scaling. We stay engaged as your AI capabilities and infrastructure needs evolve.
Tell us about your workloads, security requirements, and deployment preferences. Our team will design a dedicated GPU cluster tailored to your organization.