The EU AI Act (Regulation EU 2024/1689) is now progressively binding, yet corporate compliance is still demonstrated primarily through self-assessment reports and paper files. Regulatory authorities have no independent technical means to verify these claims, and cannot access corporate environments directly due to trade secrecy and data protection constraints.
This is the gap I have been working on: translating binding legal obligations into technical requirements that can be verified without requiring companies to disclose trade secrets or regulators to access internal systems directly.
The approach covers the provisions of the Act that speak directly to a technical system rather than to institutional or administrative processes: Article 5 (prohibited practices), Articles 9 through 15 (high-risk system requirements), Article 50 (transparency), and Articles 53 and 55 (GPAI obligations).
Each provision is translated through a shared four-layer technical architecture:
- An interception layer positioned between the system and the user, inspecting outputs before they are delivered
- A rule engine that converts legal requirements into automated, auditable enforcement actions
- A behavioral monitor tracking patterns over time rather than single events
- An immutable audit log with automatic alerting to the competent authority upon violation, without disclosing underlying data content
The methodology is grounded in internationally peer-reviewed academic literature and recognized standards (ISO, NIST, IEEE, ACM), with every technical claim traceable to a specific reference. It is jurisdiction-agnostic by design and does not constitute a legal instrument — it is a technical research framework intended for review and validation by qualified engineers, security specialists, and legal experts before any practical deployment.
I am glad to discuss the framework, its scope, or specific provisions with anyone working on the same problem.
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