Course: Enterprise AI Governance Architecture | Grigoriy Dobryakov

Grigoriy Dobryakov

Course · Enterprise AI Governance Architecture

Course

Enterprise AI Governance Architecture

AI governance is the set of rules and mechanisms that decide what an AI system in a company may and may not do, and how to make sure it actually holds to that. This course is about the engineering side: not a forty-page policy but a control plane — the layer between the business and the models that all traffic passes through and that governance cannot be bypassed technically.

Each chapter takes a business or regulatory goal and drives it down to an architectural pattern and an engineering implementation: what to deploy, where it breaks, and how it maps to the EU AI Act, ISO/IEC 42001 and OWASP. The running case is Kovcheg, a bank AI assistant (RAG plus an agent that takes actions), deliberately high-risk so it touches every plane at once.

The course runs down a stack of control planes: one request passes through the layers top to bottom — from data masking and access control through guardrails to audit and evaluation. Start with the manifesto.

Read the manifesto →

Putting AI into production under regulatory risk?

Designing the control plane for your system: privacy, access, guardrails, audit, EU AI Act / ISO 42001 compliance — as working architecture, not a policy PDF.

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The transition engine

Next Move Engine — the system that takes a team to an autonomous delivery loop.

Next Move Engine →