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DBCV — Open AI Workflow Platform

An open multi-agent low-code platform: a visual scenario builder, runtime and AI assistant — one of the things we've built.

Open source (Gitverse) Presentation

DBCV is one of the things we’ve built: an open AI workflow and multi-agent low-code platform where workflows are built and run visually. Not a model wrapper — the visual builder, runtime and AI assistant sit on an architecture grounded in a patented, entropy-resistant data-separation method. The workflow is assembled from blocks and links, and the LLM and AI agents are wired in as individual steps — only where they are actually needed.

The core engineering idea: the model is wired in only where it is needed. Logic, branching, data work and integrations can be built with no LLM at all, so token cost is controlled at the scenario-architecture level, not discovered after the fact on the invoice. Below — capabilities, integrations, video and the interface.

capabilities

Visual scenario builder

Design and debug UX scenarios in a visual editor: branching from message triggers, Python code, external requests and variable values.

No-LLM steps — token economy

Logic, branching, data work and integrations can be built without calling a language model at all. The model is wired in only where it is truly needed — direct cost control.

Multi-agent

Service-agents for chatbots, games, sites, automation and cross-system integrations. Services combine into a multi-channel environment, even without APIs.

AI assistant: Ask · Plan · Agent

Three modes — Q&A, planning and autonomous task execution — with transparency: you see when it thinks, calls tools, and the pipeline stage.

Flexibility and branching

A scenario is assembled from blocks and links with master-links and transition rules; behavior changes without rewriting the whole process.

Logs, history and sandbox

Detailed run history, before/after states per step, built-in logs inside agents, and a sandbox mode with diagnostics and no external tools.

integrations

Telegram

Integration with the popular messenger for bot development

News API

The largest news portal, available via API

OpenAI

GPT-4.1 for generating text, code and analytics

Speech2Text

Online service converting Russian speech audio to text

Google Calendar

Create, remind and share events

Yandex Calendar

Calendar for planning and reminders

Google Sheets

Cloud spreadsheets with formulas and scripts

DaData

Autofill and validation of addresses and phone numbers

YandexGPT

Yandex's Russian LLM for text, code and analytics generation

Anthropic Claude

The Claude family for reasoning, analysis and code

WhatsApp

Messenger for business bots and conversation automation

Slack

Enterprise messenger for work communications and notifications

Notion

Knowledge base and collaborative documents and tables

VK

Russian social network and messenger for bots and integrations

Discord

Communities and bots on voice and text channels

GitHub

Repositories, issues and pull requests for DevOps scenarios

GigaChat

Sberbank's Russian LLM for text generation and knowledge work in Russian

Yandex SpeechKit

Russian speech recognition and synthesis from Yandex for voice scenarios

Bitrix24

Russian CRM and corporate portal for sales and process automation

amoCRM

Sales CRM with deal pipelines and communication automation

MAX

Russian messenger from VK Tech for business correspondence and bots

Webhook

A universal HTTP connector to integrate with any external service via API

+ any external API

video

DBCV — platform overview
DBCV — platform overview
Building a scenario
Building a scenario
AI assistant in action
AI assistant in action

interface

patent

RU Patent No. 2 688 238 C1

Data separation method “Distributor — Block — Link — Presentation” for web services

The platform architecture is based on a patented, entropy-resistant data separation method. Patent holder — Philippe Delsaul.

Yandex Patents rusneb.ru

deployment

Free cloud

Non-commercial cloud platform.eni7.ru: the visual builder with no separate hosting or DevOps.

Open source

Python source on Gitverse (carbonfay/DBCV): deploy, study, extend.

Portability

Export scenarios to JSON — move between cloud and local servers.

Materials, screenshots and video: dbcv.ru

related

related cases

Next step

Let's design an AI-native automation layer for your operations.

DBCV