Synthetic data certification, AI governance, cryptographic provenance, and compliance from the team building the certificate authority for AI artifacts.
A step-by-step walkthrough of the REQUESTED → ISSUED lifecycle — SHA-256 hashing, RFC 8785 canonicalization, Ed25519 signing, and what the certificate actually proves.
Read more →You don't need CertifiedData's tooling to verify a certificate. This guide shows how to do it with sha256sum, curl, and any Ed25519 library.
Read more →Why synthetic datasets need more than a README. How CertifiedData's certificate authority model gives AI artifacts the same verifiability as TLS certificates.
Read more →Articles 10, 12, and 53 place documentation and logging requirements on AI systems. Certified synthetic data creates a tamper-evident audit trail that satisfies them.
Read more →Governance frameworks mean nothing without evidence. How certificate-anchored provenance turns governance policies into verifiable records.
Read more →Software has SBOMs. AI systems need AIBOMs. How certified dataset provenance feeds directly into an auditable AI bill of materials.
Read more →Logging that an AI made a decision is not enough. Tamper-evident decision lineage proves what data drove the model and what the model decided.
Read more →What it means to certify a training dataset: hash binding, generation provenance, schema attestation, and the certificate artifact that proves all three.
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