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Map indicates jurisdictions where regulatory outreach or informational submissions have been made as of Dec 2025.

Verifiable AI Provenance Framework (VAP)

VAP is a layered assurance architecture designed for independent verification of AI decision-making. It is not a single product, but a framework defining how cryptographic evidence and third-party verification interoperate across diverse systems.

The architecture records decision-to-execution events as immutable audit trails, facilitating regulatory review and post-incident analysis without reliance on institutional trust. VAP builds upon the VeritasChain Protocol (VCP), treating cryptographic evidence as a core primitive in AI assurance.

Research Publications

VeritasChain has published two complementary papers on Zenodo establishing the feasibility and necessity of auditable AI infrastructure:

-- Empirical Study: "Cryptographically Verifiable Audit Trails in Live Algorithmic Trading: An Empirical Study Using VCP v1.0"https://zenodo.org/records/17920524

-- Regulatory Analysis: "Why Open Cryptographic Standards Matter for AI Auditability: Formal Analysis and Regulatory Alignment"https://zenodo.org/records/17947483

The official AI Decision Auditability Benchmark (v1.0)-including the scorecard and regulatory mapping-is available at: https://github.com/veritaschain/vcp-spec/tree/main/benchmark

Global Regulatory & Industry Engagement

VeritasChain submitted VCP and VAP materials to 58 regulators across 43 jurisdictions, including authorities in Europe, Asia-Pacific, the Americas, and MEA. These submissions support regulatory understanding of cryptographic auditability within frameworks like the EU AI Act.

Industry adoption of the methodology is also gaining traction. Two Tier-1 global professional services networks have begun referencing the VeritasChain Benchmark Score in the development of their independent AI audit and assurance methodologies.

About VeritasChain

VeritasChain develops open, cryptography-based standards for verifiable audit trails in AI-driven systems. Its work spans protocol design (VCP), assurance architecture (VAP), open benchmarks, and empirical research, enabling regulator-ready, independently auditable AI systems.

More information: https://veritaschain.orghttps://github.com/veritaschain

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Contact

Media ContactVeritasChain[email protected]

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