Zabi Infotech

AI/ML Workstations & Hardware Sourcing

GPU-equipped desktops and workstation sourcing for machine learning development, training and local inference workloads.

Machine learning workloads put real demands on a machine — GPU VRAM for model size, fast storage for dataset I/O, and enough system RAM and cooling to run training jobs for hours without throttling. We source and build workstations for developers, students and small teams working on ML locally rather than entirely in the cloud.

What we recommend depends on your actual workload: fine-tuning smaller models or running inference locally has very different GPU/VRAM requirements than training from scratch, and we'll ask about your typical model size and framework (PyTorch, TensorFlow, etc.) before proposing a spec. For many individuals and small teams, a well-specced desktop for local development and inference — paired with cloud compute for the heaviest training runs — is a more cost-effective setup than trying to buy enough local GPU for everything.

We can also source and build for computer-vision or CCTV-analytics use cases, since that overlaps with the surveillance hardware we already work with. Tell us your workload and budget and we'll put together a realistic configuration, not just the most expensive GPU available.

Frequently asked questions

Not necessarily — it depends on your model sizes and whether you're training from scratch or fine-tuning/running inference. We size the GPU to your actual workload.
Yes — a GPU workstation can usually serve both purposes; tell us about both uses and we'll factor them into the spec.
For many individuals and small teams, a capable local machine for development and inference, combined with cloud compute for the heaviest training runs, is more cost-effective than either extreme alone — we can talk through what makes sense for your workload.

Want this set up?

Tell us your requirement and budget — we'll recommend a configuration and quote it.

Get a quote

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