Veritaschain Unveils VAP Architecture, New Auditability Research, And Confirms Submissions To 58 Regulators Globally - A...
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”
Regulatory Analysis:“Why Open Cryptographic Standards Matter for AI Auditability: Formal Analysis and Regulatory Alignment”
The official AI Decision Auditability Benchmark (v1.0)-including the scorecard and regulatory mapping-is available at:
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.
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