AIVO DIVM™ v1.0 — Data Integrity & Verification MethodologyOctober 2025 — Initial Public Release DIVM™ is the data trust backbone of the AIVO Standard — a globally recognized governance framework for AI Visibility Optimization.It establishes the first auditor-grade reproducibility and verification protocol for AI visibility metrics derived from LLMs.This methodology ensures that every visibility claim can be independently reproduced, audited, and trusted by boards, regulators, and investors. Core Components Reproducibility Protocol — ±5% tolerance standard with CI, CV, and ICC statistical thresholds. Evidence Chain Model — structured metadata capture (prompt fingerprint, model version, timestamp, locale). Replay Harness Specification — supports independent validation of third-party visibility claims. DIVM Compliance SDK/API — designed to automate evidence ingestion, verification, and audit logging. Audit Assurance Layer — aligned with ISO/IEC 17025, ISAE 3000, and NIST AI RMF 1.0. Governance & Regulatory Alignment Establishes standardized data trust principles for visibility reporting. Supports compliance reporting under the upcoming European Commission AI Act (2026). Provides auditors and regulators with clear evidence structures for data integrity attestation. Strategic Application Enables boards and audit committees to trust visibility dashboards and metrics. Allows vendors to certify their visibility measurements via standardized DIVM verification. Lays the foundation for machine-readable evidence trails for ESG, risk, and revenue assurance reporting. References & Standards ISO/IEC 17025, ISAE 3000 (Revised), NIST AI RMF 1.0, OECD AI Classification, W3C Verifiable Credentials, EU AI Act (2026). Version: 1.0Release Date: October 2025License: CC BY 4.0Keywords: AIVO Standard, DIVM, AI Visibility, Reproducibility, Verification, Governance, ISO 17025, NIST AI RMF, Data Integrity, LLM Measurement, Risk Assurance, ESG.