Compute, hardware and data-centre delivery for CPU- and GPU-led workloads.
Learn how we workA use case is a starting point for a better infrastructure brief. The working conditions decide the route.
Tell us about your workloadTwo teams can both describe their work as rendering, AI or simulation and need very different infrastructure.
Rendering time is a production constraint.
Artists and production teams may need capacity for a deadline, a workstation for daily work, or infrastructure for a larger pipeline.
Start with the renderer, versions, plug-ins, assets, output settings and delivery date. File preparation, storage and review cycles can change the practical setup.
Large scenes need a setup that matches the way the studio works.
Separate the design-time experience from the production-time requirement. A visualiser may need a responsive workstation while shaping a project, then additional rendering capacity for final views or revisions.
Describe the software, typical scene size, output format, review cycle, team location and the points where work slows down.
The useful brief is more specific than “we need AI infrastructure.”
Describe whether the work is experimentation, model training, inference, visual workloads or another GPU-backed task.
Include the frameworks, data movement, expected runtime, user access and whether the demand is temporary or steady.
Engineering workloads often expose the bottleneck somewhere unexpected.
Some workflows depend on CPU cores. Others need GPU acceleration, memory, fast storage or specialised software.
Explain the current workflow from input to result, including applications, licences, job duration, concurrent jobs and the output location.
Private environments need an operating plan as well as equipment.
A private environment may involve compute nodes, storage, networking, access rules, job scheduling, monitoring and an internal team.
Write down the service users expect, the administrative model and operating responsibility before selecting the architecture.
Shared workloads need clear access and support expectations.
Education and research teams may balance teaching, lab work, simulations, experiments and shared access.
Explain the applications, user groups, budget process, data requirements and peak periods so the capacity or procurement discussion has a practical starting point.
Start with the application, the people using it, the data path and the result you need.
Discuss your requirement
