What is included

Hardware requirements depend heavily on the task: running a ready model and training one are completely different budgets.

Discuss the scope

Sizing the configuration

Accelerators, video memory, processor and RAM for the specific workload.

Local deployment

Installing and configuring the model inside your perimeter with no calls to external services.

Data storage

Fast access to training sets, versioning and backups.

Isolation

A network segment with no internet access, separated permissions and access logging.

Monitoring

Accelerator load, temperature and the job queue.

Renting capacity

An option with no capital spend when the task is one-off or the volume is unpredictable.

How the work runs

Deploying a ready model takes a few days. Infrastructure for training takes weeks, allowing for delivery times.

01

Requirements

Which model, what size, how many concurrent requests and whether training is needed.

02

Sizing

A configuration with reasoning and a comparison of renting against buying.

03

Deployment

Installation, configuration and integration with your systems.

04

Handover

Documentation, monitoring and training for the administrators.

Running a ready model and training one differ in requirements by tens of times. For typical text workloads a single server with a mid-range accelerator is enough. Training from scratch needs a cluster and a budget of a different order, and in the overwhelming majority of cases it is unnecessary.

Frequently asked questions

Not if the data is not sensitive: renting capacity is cheaper and faster. Your own hardware is needed where data cannot leave the perimeter for regulatory reasons or because of trade secrets.

It is determined by the size of the model: the key parameter is video memory, and the model has to fit into it. For typical text workloads a mid-range option is usually enough rather than the most expensive one.

For summarising text, searching documents, classification and drafting correspondence, generally yes. For complex reasoning, open models fall short of the large cloud ones. It should be tested on your own tasks before buying.

We will build your AI infrastructure

Tell us about the workload and your data requirements. We will size the configuration and compare it with renting.