ZYNAGI Methodology
Every score ZYNAGI produces is rooted in a documented, reproducible methodology. This page explains how each assessment type works, how scores are calculated, and why scoring matters for enterprise governance.
ZYNAGI's Trust Assessment analyzes observable, documented signals across six domains: AI governance structure, vendor risk documentation, compliance posture, monitoring infrastructure, operational documentation, and digital integrity. Each domain is scored independently and weighted according to industry-specific risk profiles. Scores are normalized to a 0–100 scale and mapped to Trust Levels ranging from Elite to High Risk.
Governance assessments evaluate an organization's internal AI decision-making infrastructure: policy documentation, oversight committees, risk review cadences, incident response protocols, and board-level AI literacy. ZYNAGI scores governance readiness across five maturity stages and provides a roadmap from current state to enterprise-grade accountability.
Every AI vendor deployed by an organization introduces upstream exposure. ZYNAGI's Vendor Risk Methodology evaluates vendor AI documentation, security posture, data handling agreements, SOC 2 / HIPAA compliance status, and model transparency. Each vendor receives a risk classification (Low / Moderate / Elevated / Critical) that feeds into the organization's composite Trust Score.
AI Readiness measures an organization's capacity to deploy, govern, and scale AI responsibly. ZYNAGI evaluates seven pillars: Strategy, Data, Talent, Infrastructure, Governance, Culture, and Operations. Each pillar is scored on a 100-point scale. Composite Readiness Levels range from Beginner to Leader, with detailed remediation guidance at every stage.
Industry benchmarking aggregates anonymized assessment data from organizations within the same vertical and location tier. Benchmark reports show where an organization ranks relative to peers—top quartile, median, and bottom quartile—across Trust, Governance, and Vendor Risk dimensions. All benchmark data is anonymized before aggregation.
ZYNAGI's monitoring engine performs scheduled rescans at configurable intervals (monthly, quarterly, or continuous). Each rescan generates an updated Trust Score, detects score drift, and flags new exposure signals. Monitoring alerts are delivered to designated executives via email with a delta report showing improvement or regression since the prior scan.
How Scores Are Calculated
ZYNAGI detects observable governance signals—documentation presence, policy structures, vendor certifications, monitoring infrastructure—through automated scanning and structured assessment.
Each signal is assigned to a domain and weighted according to the organization's industry vertical, location count, and regulatory environment. Weights are reviewed quarterly.
Domain scores are aggregated into a composite score using a weighted average. The composite score is mapped to a Trust Level and a percentile rank against the industry benchmark population.
Why Scoring Matters
Scores create accountability where subjective assessments create ambiguity.
Benchmarked scores reveal where an organization stands relative to peers—not just an internal baseline.
Scoring enables trend analysis: is governance improving, stable, or regressing?
A documented score is a defensible record for regulators, auditors, and board members.
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