Affordable
Shared compute
Your own environment on shared hardware. Built for individual workloads and experiments.
Compute for research and AI,ready on day one
Shared, dedicated, and on-premise infrastructure for labs and teams. Preconfigured environments, transparent pricing, engineers on call.
From solo researchers to university labs, teams rely on us for the jobs that can’t wait.
376+
Universities
7,500+
Researchers
5 yrs
In research computing
70%+
Renew every year
RStudio, Jupyter, and a full control panel — preinstalled and ready. We migrate your existing environments too.
Deployment options
Shared, dedicated, or on-prem. Your call.
Match resources to the job — workload size, runtime, and how sensitive your data is.
Powerful
Dedicated servers
The whole machine for your team. No queues, no noisy neighbors.
Private
On-premise infrastructure
Hardware in your rack. Data never leaves your network.
Built for how you work
Flying solo or running a lab?
Individuals
Your laptop shouldn’t be the bottleneck. Offload heavy analysis to a server that’s always on.
See solo plansTeams & labs
One shared environment for everyone — code, data, and results in the same place, with room for long-running jobs.
See team plansSkip the setup. Log in and start running — we handle the rest.
Preconfigured environments
RStudio, Jupyter, and your toolchain installed before you log in.
Serious memory
Up to 768GB of RAM for large datasets and long-running jobs.
Engineers on call
Real humans for dependency hell, migrations, and failed jobs.
Right-sized for the job
Shared, dedicated, or on-prem — matched to your workload and budget.
Environments, costs, ops — straight answers, no runaround.
Pricing
Simple pricing, no surprises
Prices are in USD and include preconfigured environments and support.
Starter
Shared — Starter
$1199/ yearUSD
20 CPU cores · 256GB memory · 512GB storage
Your first research server. Great for routine genomics and everyday analysis.
Advanced
Shared — Pro
$2199/ year, fromUSD
40 CPU cores · 512GB memory · 1TB storage
More cores and memory for heavy samples and memory-hungry pipelines.
Lab & teams
Dedicated — Starter
$8600/ year, fromUSD
12 CPU cores · 128GB memory · 5TB storage
A whole machine for your lab — isolated, fast, and always available.
Why dedicated
- Real engineers, real-time support
- 2× faster than shared
- Zero queueing
Need GPUs? We offer cloud GPU servers too. Explore GPU plans
Model training, simulations, imaging, rendering — run it all on the same infrastructure.
What researchers are saying.
Single-cell analysis
“The high-memory machines kept our pipeline running — and when dependencies broke, support fixed it fast.”
PhD researcher
Genomics research lab
Fewer jobs stopped by memory limits
Lab collaboration
“Everyone works in the same browser environment. Analysis and file management finally feel standardized.”
Lab member
Bioinformatics research group
One environment for the entire lab
Environment migration
“We stopped re-configuring software and got our time back for the actual analysis.”
Research student
Medical imaging lab
Less time lost to setup
Ready when you are
Flying solo? Start with a plan or a free trial. Equipping a lab? Tell us what you need to run.
For individuals
Check shared plans and pricing, or grab a free 5-hour trial and take it for a spin.
The questions we hear most.
Which plan is right for solo work?
Start with a shared plan for routine analysis. Step up to GPU or dedicated resources when your work demands it — or try a free trial first.
Do I need to know Linux?
No. RStudio, Jupyter, and the control panel all run in your browser. Stuck? Our engineers are one message away.
Can we migrate our existing setup?
Yes. We help verify software versions, dependencies, and file paths before anything moves.
Can it handle AI training and inference?
Yes — CPU, high-memory, and GPU resources are all available for training, fine-tuning, and inference.
Can we try before we buy?
Absolutely. Tell us about your research and data size, and we’ll set up a free 5-hour trial.
Shared or dedicated for our lab?
It comes down to concurrent users, workload, and whether you need isolated resources. Share the project details and we’ll recommend a setup.