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Услуга · Artificial intelligence

Infrastructure for AI

Needed where sending data to external services is unacceptable: financial institutions, healthcare, the public sector, companies protective of their own developments. We build a closed environment where the computation happens entirely inside your network.

Send a request What is included
Inside the perimeter
the data does not leave
GPUs
chosen to fit the model
Storage
sized to the datasets
Renting
when buying is excessive

What the work includes

The hardware requirements differ radically: running a ready model and training your own are budgets of a different order.

Discuss the scope

Configuration

How many cards and how much memory they have, which processor and how much RAM you actually need.

Deployment

We install and configure the model inside your own environment, with no calls to any external network.

Storage

The datasets have to read quickly, be versioned and have a backup copy.

Isolation

A separate segment with no internet access, permission separation, a log of requests.

Monitoring

GPU utilisation, temperatures, the length of the job queue.

Renting capacity

Suitable if the work is one-off or the demand fluctuates and it is too early to invest in hardware.

How it goes

A ready model is deployed in a few days, while a build for training depends on delivery and stretches over weeks.

01

Requirements

Which model and what size, the expected request volume, whether fine-tuning will be needed.

02

Sizing

A configuration with the reasoning and an honest comparison of renting against buying.

03

Installation

We deploy it, configure it and connect it to your systems.

04

Handover

Documentation, load monitoring, training for your administrators.

Hardware for neural networks ages faster than ordinary servers. GPUs change generation every eighteen months to two years, and what you buy today will compute three times slower than new models in three years. When the future of the task is unclear, renting capacity is often more sensible than buying.

Questions and answers

If the data is not sensitive then no, renting is cheaper and starts faster. Your own hardware is required where the information cannot leave the perimeter by law or because of commercial confidentiality.

It all comes down to the size of the model: it has to fit entirely into the card's memory, so that is the figure to look at first. For ordinary text tasks a mid-range option is enough and there is no need to buy the most expensive.

For summarising documents, searching a knowledge base, classifying enquiries and helping with correspondence, generally yes. Where multi-step reasoning is needed, freely available models are noticeably weaker than the large cloud ones. It is worth confirming suitability on your own material before ordering any hardware.

More in this area

Open the area
Service AI adoption Scenarios with a measurable return rather than experiments Service AI adoption strategy Дорожная карта и оценка готовности компании Service Training staff to work with AI Practice on real working tasks

We will build the hardware for the task

Tell us about the task and what must not leave the perimeter. We will put together a build and compare it against the cost of renting.