AI Router

Open models on dedicated capacity

AI with capacity reserved for your company

Run the model you need on dedicated capacity. We agree on the configuration, access and support. Your team uses AI while we take care of hosting and operations.
Dedicated to your company
Your chosen model
Agreed GPU capacity
Your apps and employees

One configuration. One operations team.

When AI becomes part of your daily work

Capacity for your workload

We select GPUs for the model size, user count and request length. You know which resources are allocated to your project.

One model for your systems

Connect your CRM, knowledge base, internal apps and automation through a shared API. Access rules are agreed for your team.

Hosting on your terms

Infrastructure region: Kazakhstan. Together, we define data processing, service and model update terms.

New open models. Your own capacity.

Choose current Qwen, DeepSeek, GLM and Kimi models for your company. We will size the GPUs, test your tasks and quote the deployment.
Models with published weights

Selection reviewed

12 more models for your tasks

Dedicated deployments are set up to order. Pricing depends on the model, GPUs and workload. We agree on the configuration, licensing and schedule before launch. Need another model? Send us its name and we will check deployment options.

Already have your own model?

Send us the model name or description and your deployment requirements. We will assess compatibility, capacity and licensing terms.

Fine-tuned for your task

Discuss hosting your model weights and connecting the model to your business systems.

From an open catalog

Choose a version with the right quality, size and license. Then test the result on your examples.

Connect through a familiar API

After deployment, we provide your model ID. Use it with your existing OpenAI-compatible client.
from openai import OpenAI

client = OpenAI(
    base_url="https://api.airouter.kz/api/v1",
    api_key="air_live_your_key_here"
)

response = client.chat.completions.create(
    model="your-deployed-model",
    messages=[{"role": "user", "content": "Summarize this document"}]
)

print(response.choices[0].message.content)

Give AI a dedicated place in your company

Tell us about your task, model and workload. We will propose a configuration with clear service terms.

Discuss a deployment