AI Regulation, Synthetic Data & Certification
Practical reference guides for AI engineers, compliance leads, and governance teams. Each guide connects regulatory requirements to the technical mechanisms that satisfy them.
Built by CertifiedData — the certificate authority for AI artifacts. Every guide links directly to the product surfaces that address the obligation described.
AI Regulation
What AI regulation actually requires from your team — EU AI Act, NIST RMF, and the technical obligations that matter.
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EU AI Act Explained
Risk tiers, key articles (10, 12, 13, 19), enforcement timeline, and what high-risk classification means in practice.
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AI Risk Classification
How the EU AI Act's four-tier risk model works — unacceptable, high, limited, and minimal — and where your system lands.
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Synthetic Data
What synthetic data is, how it's generated, and why it's the privacy-safe path to training data for regulated AI systems.
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Dataset Certification
How cryptographic certification works — Ed25519 signatures, dataset fingerprints, verification, and the artifact registry.
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AI Governance
Controls, accountability, and operational oversight for AI systems — and how governance becomes evidence.
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Data Provenance
How to prove where AI data came from — origin, transformations, and artifact-level evidence.
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AI Auditability
What reviewers need to inspect and verify an AI system — records, provenance, and machine-verifiable proof.
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