Servers for Artificial Intelligence
Infrastructure for training models and running them in production.
AI workloads split into two phases with opposite requirements. Training is heavy, occasional and hungry for memory and interconnect bandwidth. Inference is lighter per request but runs constantly and is judged on latency and cost per response. Buying one configuration for both means overpaying in one of the phases, so we plan them separately — and keep the data in a Kazakhstan data centre, which for many clients is what makes the project possible at all.
What you get
Training and inference planned apart
Two phases, two cost profiles. We size each on its own so you are not paying training rates for a workload that only serves requests.
Memory sized to the model
Models that do not fit one card have to be split, and splitting costs throughput. We pick capacity so the model stays resident where that is possible.
Ready ML environment
CUDA, cuDNN, PyTorch or TensorFlow, plus serving stacks such as vLLM on request. The team gets a machine they can work on, not a driver project.
Data residency in Kazakhstan
For banks, healthcare and the public sector, moving data abroad is often simply not allowed. In-country hosting removes that question and keeps latency low regionally.
Frequently asked questions
Do we need our own model, or can we use an existing one?
Both paths work. Many projects start by serving an open model and only fine-tune once the gap between generic and domain-specific output is measured rather than assumed.
How much GPU do we need for inference?
It follows from request volume, latency target and model size. We calculate cost per response for the candidate cards and pick on that number, not on raw specs.
What happens to our data afterwards?
Storage is wiped when the server is released and we confirm it in writing. If you need the data returned first, we agree the transfer window before shutdown.
Talk to an engineer, not a sales script
Tell us the workload — model size, number of camera streams, deadline — and we will come back with a configuration and a price. If renting is the wrong answer for your case, we will say so.