On compliance, accountability, and AI — written plainly.
EU AI Act timeline changes, the Dutch Cyberbeveiligingswet moves through parliament, and the Commission’s own infrastructure gets attacked. How Sovaign’s Governance Pulse tracks it automatically.
The model will make mistakes. The relevant question for a compliance team is not how to prevent them — it is whether your system can detect them, bound them, and demonstrate that it did. A system design problem, not a model problem.
Every system that introduces AI into a compliance workflow is itself a new source of risk. This is a feature-by-feature account of the quality, AI, and IT performance risks Sovaign is built to address — and the mechanisms that address them.
ISO 42001:2023 is the international standard for AI management systems. If your organisation is deploying AI, you are already creating obligations under it — whether or not you have mapped them. Most organisations have not.
We were people who used AI every day for serious work and kept running into the same wall. The AI was genuinely impressive. But the moment the conversation ended, everything it had helped us build disappeared.
No standard yet defines what autonomous AI agents owe each other across trust boundaries. IACS-1.0 is a draft that tries to fill that gap — and it points directly at the compliance problem Sovaign is built to solve.
A short PDF overview of what Sovaign does, how a compliance manager would use it day to day, and what the main screens look like. Seven pages. No marketing fluff.
Most compliance tools ask you to fill in a structure someone else designed. Hub-and-spoke turns that around: start with what you are required to do, and let AI discover how you actually do it.
In January 2026 we ran the same EU AI Act compliance document through three AI models and measured what each extracted. The numbers are interesting. But the more useful finding is what the differences say about how to think about model choice — and why having a local fallback matters more than it might seem.
Most compliance work produces documentation that describes how an organisation should behave. Little of it actually proves how it does behave. That distinction is becoming critical — and AI is what is making it so.