How it works
Generate. Certify. Verify. Govern.
CertifiedData provides a continuous provenance chain for synthetic data and AI artifacts. Generate datasets with verifiable metadata, certify them with cryptographic proof, validate them independently, and govern the downstream decision trail — so your AI system is defensible at every layer.
Step 1
Generate
Step 2
Certify
Step 3
Verify
Step 4
Govern
Datasets workflow
Generate, certify, verify, and govern AI artifacts
This page remains the canonical datasets workflow explainer for synthetic data, certification, verification, and governance.
Agent Commerce workflow
Need the receipts-and-verification payment workflow instead?
Follow the Agent Commerce path for authorization, payment execution, signed receipts, and independent verification.
The trust workflow
A continuous provenance chain, not disconnected tools
Each step advances the same evidence chain. Generation creates the artifact. Certification adds cryptographic provenance. Verification makes trust independently checkable. Governance closes the loop — linking certified inputs to downstream decisions and making the whole chain audit-ready.
Step 01
Generate
Generate synthetic data for testing, development, and AI workflows
Create structured synthetic datasets without exposing real-world records. CertifiedData supports tabular synthetic data workflows intended for development environments, analytics, internal testing, evaluation, and model experimentation.
- Input dataset or schema definition
- Preprocess and prepare structured tabular data
- Run CTGAN-oriented generation workflows
- Export datasets with metadata preserved for certification
Step 02
Certify
Issue a cryptographic certification artifact
After an artifact is created, CertifiedData produces a structured, machine-verifiable certification record. The certificate captures the dataset fingerprint, generation metadata, timestamp, schema version, and digital signature — so provenance can be checked independently. Certifications and notarizations share the same quota pool and the same Ed25519 signing infrastructure.
- Compute a SHA-256 artifact fingerprint
- Capture metadata and algorithm details
- Create a certification record with schema versioning
- Sign the record with Ed25519 for tamper-evident verification
Step 03
Verify
Verify integrity independently
Verification makes trust checkable. A third party can recompute the artifact hash, compare it against the certification record, validate the signature, and confirm that the artifact matches the one originally certified. Every certified artifact is automatically listed in the registry — no separate step required.
- Recompute the artifact hash
- Match the fingerprint to the certificate record
- Validate the Ed25519 digital signature
- Confirm integrity, provenance, and record consistency
Step 04
Govern
Complete the evidence chain and make your AI system defensible
Govern is where the evidence chain becomes defensible — not just recorded. Decision logs link back to certified data. Lineage graphs show causality. Audit packages give auditors and regulators something they can actually check. At the Govern tier, the entire chain from dataset origin through model decisions is exportable, signable, and audit-ready.
- Log AI decisions and link them to certified inputs
- Visualize dataset → certificate → model → decision lineage
- Export audit packages for regulatory defense
- Generate EU AI Act compliance reports
Lineage
The chain from certified data to AI decisions
Origin and integrity are proven at certification. Lineage connects certified inputs to downstream model usage and decisions. Trust completes the chain. Govern makes it exportable and audit-ready.
Dataset
SHA-256 fingerprint
Certificate
Ed25519 signed
Model
Trust+
Decisions
Trust+
Origin verified
Certification proves the dataset was synthetically generated and cryptographically fingerprinted at a known point in time.
Lineage partial → complete
At Trust tier, certified datasets link to the models trained on them and the decisions those models produced. The chain closes.
Audit-ready at Govern
The full chain becomes exportable — cert + dataset + decisions + lineage — as a downloadable audit package regulators can actually check.
The more you govern, the more defensible your AI system becomes. View tier breakdown →
How verification works
A machine-verifiable proof flow
CertifiedData treats certification artifacts as cryptographic records. Verification requires hashing the artifact, comparing it to the certification record, and validating the digital signature against the issuer key.
1. Hash the artifact
Compute the SHA-256 fingerprint of the dataset, model artifact, or other AI output.
2. Match the record
Compare the computed fingerprint against the dataset_hash stored in the certificate record.
3. Validate the signature
Check the Ed25519 signature using the issuer public key and the certification schema.
4. Confirm provenance
Verify that the artifact, metadata, and signed record remain consistent and unaltered.
Verification registry
The registry is a consequence of certification, not an extra step
Every certified artifact is automatically listed in the registry. The registry is verification infrastructure — it anchors certification records, exposes machine-verifiable artifact history, and allows third parties to validate provenance without relying on internal claims. Your tier determines what that listing looks like.
Free
Listed
Publicly listed in the registry with basic verification. Anyone can confirm the certificate exists and check the hash.
Build
Profiled
Organization profile attached to each listed artifact. Richer metadata, dataset descriptions, and provenance context.
Trust
Controlled
Private and unlisted artifact control. Enhanced listing options. Selective auditor sharing without public exposure.
Govern
Auditable
Full lineage graph, compliance export, and audit-ready package. Every certified artifact becomes a defensible evidence record.
Why it matters
Built for trust, auditability, lineage, and governance
This is not a cosmetic trust layer. It is designed to support real governance workflows where teams need verifiable records, artifact lineage, operational traceability, and defensible evidence when customers, auditors, or regulators ask what happened.
Provenance
Know where an artifact came from, when it was produced, and what process created it.
Verification
Move beyond screenshots and claims with cryptographically checkable records.
Auditability
Preserve the evidence chain needed for internal review, external assurance, and investigations.
Governance
Connect synthetic data generation, certification, registry-backed verification, and operational decision lineage.
Compliance
Support record-keeping, traceability, and accountability obligations with machine-verifiable evidence.
Regulatory relevance
Support traceability, record-keeping, and accountability
Teams evaluating AI governance obligations need more than model claims. They need artifact history, record integrity, operational evidence, and a defensible way to explain what was generated, what was certified, and how systems acted later.
Governance outcomes supported by the workflow
- Traceability across artifact creation, certification, verification, and downstream use
- Record-keeping for internal controls, audit preparation, and external assurance
- Vendor and system accountability supported by machine-verifiable evidence
- Decision lineage that preserves operational context after deployment
- Evidence-ready workflows relevant to AI governance and compliance programs
Evidence layer
Machine-readable workflow summary
Trust workflow contract (for agents and systems)
{
"term": "CertifiedData verifiable AI trust workflow",
"concept_type": "workflow-root",
"canonical_url": "https://certifieddata.io/how-it-works",
"workflow_steps": [
"generate",
"certify",
"verify",
"govern"
],
"hash_algorithm": "SHA-256 (RFC 8785 JCS)",
"signing_algorithm": "Ed25519 (RFC 8032)",
"active_schema": "cert.v2",
"endpoints": {
"certify": "POST /v1/registry/:id/certify",
"verify": "POST /api/verify",
"registry": "GET /api/registry",
"lineage": "GET /api/lineage/recent",
"signing_keys": "GET /.well-known/signing-keys.json",
"openapi": "GET /openapi.json"
},
"verification_auth_required": false
}Build defensible AI systems
Start free. Scale the evidence layer as you grow.
Generate synthetic data, certify artifacts, verify integrity independently, and govern the downstream decision trail. The more you govern, the more defensible your AI system becomes.