Technology · LLM
01

Models tested
Yandex, Sber, Qwen, MTS

02

Call modes
tool calling and standard prompting

03

Vendor lock-in
the model is a parameter, not a foundation

The model is your choice

02MODELS

Proven on live models

Not benchmarks — working dialogues. The platform has been tested with Russian cloud models and open ones — including a run inside a closed contour.

/01

YandexGPT

Yandex’s cloud model — a fast start inside the Russian contour.

/02

GigaChat

Sber’s model — tested on live dialogues of the platform.

/03

Qwen

An open model — in the cloud or entirely inside your contour.

/04

Cotype · MTS

The MTS corporate model — proven in production scenarios.

/05

Your own LLM

A corporate model behind your API — the platform connects to it.

/06

Switching by setting

Moving to another model is a configuration parameter, not a project.

03ARCHITECTURE

One layer, any model

Dialogues, RAG and skills talk to the model layer, not to a particular vendor. Which is why a cloud LLM and a corporate one are equals to the platform.

Cloud LLM
YandexGPT · GigaChat · Qwen
Corporate LLM
Your contour · your API
Function calling
The model calls tools
Prompt mode
For models without tool calling
LLM layer
04 · TWO MODES

A mode to match the model

If it can call functions, good. If it cannot, it still works. The platform tunes the mode itself: tool calling for current models, prompt mode for the rest.

Function calling
Standard prompt
Cloud model
Corporate LLM
Switching without migration
One configuration parameter
05IN NUMBERS

Speed does not depend on the vendor

Streaming levels out the experience. Whichever model stands behind the layer, the answer starts typing into the dialogue in under a second.

01

First token
the answer starts typing into the dialogue at once

02

Models tested
Yandex, Sber, Qwen, MTS

03

Call modes
tool calling and standard prompting

04

Vendor lock-in
the model is a parameter, not a foundation

First token · ms · by model
PeakTypical
06WHERE THE MODEL LIVES

The cloud or your contour

Where the model lives is your decision. The platform works the same with a cloud API and with a model deployed inside the company — all the way to a fully isolated contour.

REQUEST

Tell us your task

PORTFOLIO BY TYPEBY YEAR

Projects by type grow year over year

MVPRedesignAISupportTotal

MVP, redesign, AI and support — cumulative

STRENGTHSPROFILE

The studio profile across key axes

Speed, quality, transparency, engineering

PROJECT PHASESOVER TIME

Research, design and build overlap

Parallel streams — not a waterfall