Cortex
An agentic operating system for business: it collects signals from 1C, CRM, ERP, MES, documents, and chats, assembles the right team of digital specialists, and drives the task to a verifiable result.
- Крупный бизнес
- МСБ
- on-prem
- частное облако
- гибридный контур
We start with a scenario review and a pilot — no invented promises, no extra risk.
Data and actions already live in 1C, CRM, ERP, MES, documents, and chats, but the team spends time gathering context and reconciling versions, while cases get stuck between departments. Cortex is an agentic operating system that turns a signal into a governed game graph: it assembles the right team of digital specialists, guides it through plan, action, verification, and recording — and leaves a verifiable trace of every step.
This is for those who value the process of connection between functions over a single chat: CEOs, COOs, commercial services, production, and IT teams, where a lead, incident, contract, or production issue passes from person to person and part of the context is lost.
What you get
- A core as a control layer. An intake router, planner, context curator, knowledge layer (RAG), critic, compliance control, and action executor turn a signal into a governed execution graph.
- A catalog of role archetypes. A library of digital employees across sales, marketing, production, procurement, quality, documents, and risk — but only the needed team is activated per case.
- Temporary agent teams for the task. For a specific case, a team of specialists is assembled and guided through the cycle
signal → plan → action → verification → recording. - Multi-level memory and audit ledger. Session, operational, knowledge, outcome, and policy memory are kept separate — actions are not only smart but also provable.
- A model router for Russian and international scenarios. For the Russian-language corporate facade — GigaChat, for reasoning and background analytics — DeepSeek, for self-host and specialized tasks — Qwen and other models.
- Tool-gated autonomy. Any external action passes through roles, permissions, limits, a sandbox, and, where needed, human confirmation.
- Ready-made packages for departments. The first release is assembled as a Revenue Pack, Operations Pack, or Growth Pack, then transitioned into programmatic mode with standing assignments.
Who it's for
- CEO, COO, business owner. You need not "another chat" but a system that accelerates work between functions and makes actions reproducible.
- Commercial director, head of sales. Leads, proposals, follow-ups, contracts, and handoffs between marketing, sales, and legal slow down the deal cycle.
- Production director, head of maintenance and repair. Signals on quality, safety, and reliability already exist, but actions between people and systems happen slowly.
- CIO, CTO, architect. You need a governed multi-agent solution with memory, model routing, logs, and a sandbox — without the chaos of plugins and manual prompts.
- CISO, compliance. AI automation runs into risks of leakage, prompt injection, and lack of audit — you need autonomy levels and a verifiable trace of decisions.
What's special
- Not "a set of hundreds of bots."
- Not a single universal assistant. A real process needs roles, permissions, context handoff, escalations, and tracing; a single universal assistant quickly becomes opaque and unsafe.
- Model routing, not vendor lock-in. GigaChat as the Russian-language facade, DeepSeek as the reasoning layer, self-host models as specialized executors — not "one model for everything."
- A trusted perimeter for sensitive data. Sensitive scenarios run in a secure perimeter, and external API models are connected only through a policy gate.
- Human-in-the-loop at critical points. The system prepares and accelerates decisions, while responsibility remains with the human.
How it works
- We define the business case and risk. We establish what work Cortex should close: sales, approvals, production, procurement, or a mixed case between departments.
- We connect context sources. The system gains access to the needed systems, documents, email, and reference data and builds context from facts.
- We assemble the core and the needed role package. The router and planner form the execution graph and spin up only the specialists needed for the case.
- We launch safe execution. The task is guided through a draft, a controlled action, or a proactive mode with verification of policies, permissions, and result quality.
- We record the result and improve the playbook. After the case, actions, decisions, metrics, and useful patterns are saved for future runs.
Where to start
The primary step is a pilot in shadow mode on one process. We select one business package, spin up the core, and launch a controlled pilot: the system runs the case in parallel with the team, and you see the quality and boundaries before moving it into the real process.
The secondary step is architecture discussion: we review priority integrations, the licensing model, and the criteria for transitioning from shadow mode to a controlled mode with approval.
[Discuss architecture and pilot] · [Request a demo]
FAQ
Is Cortex just a set of dozens of agents?
No. The archetype catalog is a library of roles. In operation, the system spins up only the needed temporary team and guides it through a governed execution graph.
Why not take one strong assistant for all tasks?
A real process needs roles, permissions, context handoff, memory, audit, and autonomy levels. A single universal assistant quickly becomes opaque and unsafe.
Do you have to choose one model?
No. Cortex is built on the principle of model routing: GigaChat can be the Russian-language corporate facade, DeepSeek the reasoning layer, and self-host models specialized executors.
Can sensitive data be kept in the Russian perimeter?
Yes, this is one of the core principles of the concept: sensitive scenarios run in a trusted perimeter, and external API models are used only where permitted by data policy.
Where to start with implementation?
Not with all roles at once. It's practical to spin up the core, select one business package, and launch shadow mode or a controlled pilot on a real process.
---
What is clarified before launch
The target first pilot (revenue, operations, or growth), priority integrations, delivery format, licensing model, and criteria for transitioning from shadow mode to a controlled mode are fixed at the architecture discussion stage.
Let us review your scenario and shape a pilot
We will show how the product fits your process and suggest a pilot format for your scale. No obligations.
info@right-digits.ru