Compliance · PRML v0.1 · CC BY 4.0

PRML maps to EU AI Act, NIST AI RMF, and ISO/IEC 42001:2023.

A primitive does not relieve a provider of obligations. It supplies the cryptographic record those obligations name. This page documents — clause by clause — which named obligations PRML mechanically supports and which it explicitly does not.

Audience. Compliance leads at AI providers, notified bodies preparing for Article 43 conformity assessment, national competent authorities under Article 72, audit firms, and standards-body reviewers (CEN-CENELEC JTC 21, ISO/IEC SC 42).

Status. Working draft. Editorial position by the spec author. Not legal advice. Authoritative compliance determination is the responsibility of qualified legal counsel under the relevant jurisdiction.

1. EU AI Act — Regulation (EU) 2024/1689

Articles cited reference the consolidated text published in the Official Journal on 12 July 2024. General entry into force was 1 August 2024; high-risk obligations apply from 2 August 2026 (Article 113).

Article 12 — Record-keeping (logging)

ProvisionPRML mechanism
12(1) — automatic recording of eventsYAML manifest emitted by training/eval pipeline; no human authoring required
12(1) — tamper-evidenceSHA-256 over canonical bytes; any post-hoc edit breaks the hash
12(2)(a) — identification of risk situationsThreshold + direction committed pre-run; threshold tampering becomes detectable
12(2)(b) — post-market monitoringOptional public anchor at registry.falsify.dev provides stable URL + re-derivable hash
12(2)(c) — monitoring of operationRegistry permalinks support badge-embedded receipts on model cards and reports

Article 17 — Quality management system

The PRML manifest format is itself a documented procedure within the meaning of Article 17(1)(d). Conformity claim: a provider that emits PRML manifests for high-risk evaluations satisfies the format portion of QMS documentation; the review and approval portion remains a separate organisational obligation.

Article 18 — Documentation keeping

PRML manifests are content-addressed via SHA-256 and are durable for the spec's intended lifetime regardless of registry availability — the canonical bytes plus the hash function are sufficient for re-derivation. This satisfies the 10-year retention requirement under Article 18(1) without depending on Studio 11 infrastructure.

Article 50 — Transparency obligations

Article 50(1) requires that natural persons interacting with an AI system are informed of that fact when not otherwise apparent. PRML does not address this obligation directly but provides the cryptographic anchor for any public claim made about the system's behaviour, which 50(1) disclosures may reference.

Article 72 — Post-market monitoring

ProvisionPRML mechanism
72(1) — systematic data collectionEach evaluation event produces a manifest + hash; chronological log emerges naturally
72(3) — post-market monitoring planThe set of pre-registered manifests is the plan, made cryptographically binding

Article 73 — Reporting of serious incidents

When a serious incident occurs, the provider must report under 73(1)–(3). PRML supports incident reporting by providing cryptographic citations to the pre-incident evaluation manifests — competent authorities can re-derive the hash and verify what the provider committed to before the incident, independent of the provider's word.

Annex IV — Technical documentation

Annex IV §2(g) requires "the metrics used to measure accuracy, robustness, cybersecurity and compliance with other relevant requirements." PRML manifests are those metrics in serialised, hash-anchored form. Annex IV §3 (testing) is supported when each test cycle emits a manifest.

Full article-by-article worked example with a hypothetical Annex III system is in the spec repository at github.com/studio-11-co/falsify/blob/main/spec/compliance/AI-Act-mapping-v0.1.md.

What PRML does not satisfy. Risk management system (Article 9), data and data governance (Article 10), human oversight design (Article 14), accuracy obligation per se (Article 15 sets the obligation; PRML records what was claimed). PRML is narrow by design — a serialisation primitive supports recording obligations, not conduct obligations.

2. NIST AI Risk Management Framework v1.0

Cross-mapping to NIST AI RMF v1.0 (NIST AI 100-1, January 2023) functions and categories. PRML primarily supports Govern (documentation infrastructure) and Measure (validation evidence).

Function · CategoryPRML alignment
Govern.1.5"Ongoing monitoring and periodic review of the risk management process and its outcomes are planned" — the manifest set is the planned monitoring artefact
Govern.5.2"Mechanisms are established to enable AI system end-users and operators to provide feedback on... potential bugs and risks" — registry permalinks are stable and shareable
Measure.1.1"Approaches and metrics for measurement of AI risks... are selected" — manifest's metric + threshold + threshold_direction fields commit selection pre-run
Measure.1.3"Internal experts who did not serve as front-line developers... are involved in regular assessments" — independent verifiers re-derive the hash without coordinating with developers
Measure.2.4"Performance is documented and disseminated" — README badges from registry.falsify.dev embed re-derivable receipts
Measure.2.13"Effectiveness of the [model] performance and trustworthiness characteristics... are documented" — pre-registered claim is the documentation

The Map and Manage functions are organisational and not directly addressed by a serialisation primitive. PRML supplies evidence; an organisation supplies governance.

3. ISO/IEC 42001:2023 — AI Management System

Cross-mapping to selected clauses of ISO/IEC 42001:2023 (AIMS — Artificial Intelligence Management System). PRML primarily supports documented information obligations under clause 7.5 and operational planning and control under clause 8.

ClausePRML alignment
7.5.1 — GeneralManifest is the prescribed form of documented information for evaluation claims
7.5.2 — Creating and updatingManifest creation is automated; updates produce new manifests with fresh pre_registered timestamps (forward-only chain)
7.5.3 — Control of documented informationSHA-256 anchor + optional public registry provides distribution control and integrity
8.1 — Operational planning and controlPre-registered manifests are the operational plan in cryptographically binding form
9.1 — Monitoring, measurement, analysis, and evaluationEach measurement cycle emits a manifest; the set of manifests is the measurement record
A.6.2.4 — System verification and validationManifests anchor what was verified and how; re-running against the manifest's threshold is the validation step
A.6.2.6 — System operation and monitoringRegistry permalinks support continuous monitoring artefacts
Annex A controls beyond those listed (e.g. A.4 Risk treatment, A.5 Impact assessment, A.7 Data governance) are organisational controls not addressed by a serialisation primitive. PRML is one input among many to an AIMS.

4. Standards-body input status

PRML v0.1 has been submitted as an open, non-proprietary primitive to the following bodies. The spec is licensed under CC BY 4.0 and accompanied by an irrevocable, royalty-free patent non-assertion grant; reference implementations are MIT.

BodyStatusDate
CEN-CENELEC JTC 21Comment paper submitted ([email protected] · WG2)2026-05-15 (planned)
UK AISI (Inspect AI)Schema interop discussion (GitHub)2026-05-12 (planned)
ISO/IEC SC 42Awaiting v0.2 freeze before formal input2026 Q3
NIST AISICReachable via working group; no formal request yet

v0.2 RFC is open for community comment until 2026-05-22 23:59 UTC at spec.falsify.dev/v0.2-rfc. Comments from compliance leads at high-risk AI providers are particularly welcome — your concerns shape the freeze.

5. Intellectual property posture

The spec, all reference implementations, and the patent non-assertion grant are designed to satisfy the procedural requirements of standards bodies that require non-proprietary, royalty-free primitives.

ArtefactLicense
PRML v0.1 specificationCC BY 4.0
Reference implementations (Python, JS, Go, Rust)MIT
Conformance vectors (12 v0.1 + 8 v0.2)CC BY 4.0
Patent non-assertion grantWorldwide, royalty-free, irrevocable
This compliance documentCC BY 4.0

The patent grant covers (a) the manifest schema, (b) the canonical byte serialisation algorithm, (c) the registry anchor protocol, and (d) any combination thereof, for any conforming implementation. Termination occurs only if a grantee asserts patents against any conforming PRML implementation. Full text in the spec appendix.

For compliance leads — what to do next

If your organisation is preparing for Article 12 logging or equivalent obligations under another framework:

  1. Review the v0.1 spec. 15 pages, plain English, no jargon. spec.falsify.dev/v0.1
  2. Review v0.2 RFC. Five proposals, comment window open through 2026-05-22. spec.falsify.dev/v0.2-rfc
  3. Pilot one published claim. Write a manifest, hash it, anchor it via the registry. ~20 minutes, no commitment.
  4. Open a discussion if the spec doesn't fit your obligation set. github.com/studio-11-co/falsify/discussions

This document is an editorial position by the spec author. It is not legal advice. Compliance determination is the responsibility of qualified legal counsel and competent authorities under the relevant jurisdiction. Studio 11 makes no warranty regarding the regulatory acceptance of PRML manifests by any specific authority. Citations are to publicly available regulatory texts as of 2026-05-09.