AI Policy & Compliance
AI policy is how your organization turns expectations into enforceable operating rules. It covers the policies, review steps, and technical controls that keep AI systems auditable, explainable, and aligned to regulatory requirements.
VeriProof is the production evidence layer for that work. It makes each decision traceable, each record tamper-evident, and each compliance obligation easier to defend with real operating data.
This section covers the policy frameworks and compliance guides most commonly used with large language model systems. If you’re looking for a starting point, begin with EU AI Act overview or NIST AI RMF overview.
What Is an AI Policy Program?
A complete AI policy program covers the full lifecycle of an AI system:
| Phase | Activities | VeriProof role |
|---|---|---|
| Design | Risk classification, intended use documentation, bias assessment, data governance | Documentation feed — provides production baselines for comparison |
| Development | Model selection, training data documentation, test evaluation | Out of scope for VeriProof |
| Deployment | Configuration management, access controls, deployment documentation | Deployment context signing; infrastructure security |
| Production | Continuous monitoring, drift detection, incident response | Core VeriProof use case |
| Review | Periodic audit, compliance evidence generation, model update assessment | Compliance evidence export; time-machine analysis |
| Retirement | Decommissioning records, data deletion | GDPR cryptographic erasure; records retention |
VeriProof is primarily a production and review tool. It does not replace design-time policy work. It provides the operating evidence that makes those decisions verifiable after deployment.
Regulatory Landscape
The major frameworks and regulations applicable to AI systems in 2026:
| Framework | Jurisdiction | Type | Scope |
|---|---|---|---|
| EU AI Act | European Union | Mandatory regulation | All AI systems placed on the EU market; high-risk systems have specific requirements |
| NIST AI RMF | United States | Voluntary framework | All organisations; adoption increasing in regulated industries and federal contracting |
| HIPAA | United States | Mandatory regulation | AI systems processing Protected Health Information |
| GDPR | EU + UK + 100+ countries | Mandatory regulation | Data protection for AI systems processing personal data of EU/UK individuals |
| SOC 2 | US-originated, global acceptance | Voluntary audit standard | Service organisations handling customer data |
VeriProof Policy Capabilities
Immutable Audit Trail
Every AI decision captured through VeriProof is stored with a blockchain-anchored Merkle proof. This means no record can be silently altered — any tampering would break the cryptographic chain and be immediately detectable. This is the foundation that makes all other governance evidence trustworthy.
Policy Scoring
You define what constitutes a well-governed decision for your use case — confidence thresholds, refusal rates, tone indicators, fairness signals — and VeriProof scores every session against those criteria automatically. This produces a continuous, quantitative policy signal rather than a periodic sampling exercise.
Compliance Evidence Export
On demand, VeriProof generates structured evidence packages for specific regulatory frameworks. These packages include session records, proof data, policy scores, and attestation material in a form suitable for auditor review.
GDPR Cryptographic Erasure
The session record lifecycle is designed to satisfy GDPR right-to-erasure requirements without disrupting audit continuity. Erasing a data subject deletes the key material needed to verify their linked sessions — the records remain structurally intact for the audit trail, but the content is permanently inaccessible and unverifiable.
Getting Started with AI Policy
If you’re building a new policy program with VeriProof:
- Choose your framework — Start with the regulation most urgent to your organisation (EU AI Act, NIST AI RMF, or SOC 2 are good starting points)
- Integrate the SDK — Capture sessions from your AI pipelines (Getting Started)
- Configure policy scoring — Define the thresholds that matter for your use case (Policy Scoring guide)
- Set up alert rules — Get notified when production behaviour deviates from policy (Alert Rules guide)
- Generate your first evidence package — Validate that the output meets your auditors’ expectations before you need it (Evidence Export guide)
Framework Deep Dives
Search the mirrored JSON vocabulary files by vertical and OTel namespace
Industry Coverage LibraryPer-article implementation guidance for Articles 9, 10, 11, 13, and 17
EU AI ActVeriProof’s role in each of the four RMF functions: GOVERN, MAP, MEASURE, MANAGE
NIST AI RMFBAA requirements, PHI minimisation, and audit trail requirements for healthcare AI
HIPAAControl expectations for AI systems under SOC 2 Trust Service Criteria
SOC 2Technical deep dive into the HKDF key derivation and erasure workflow
GDPR Cryptographic ErasureStep-by-step guide to generating compliance evidence packages
Evidence ExportNext Steps
- Security Overview — platform security architecture
- Compliance Evidence guide — practical guide to evidence generation
- Policy Scoring guide — configuring production monitoring