Stratalize AI Governance Methodology

AGM v1.0 — Effective May 2026

This methodology governs all assessments produced by Stratalize Audit. Every report identifies the methodology version used at time of issuance.

Overview

The Stratalize AI Governance Methodology (AGM) is an independent framework for assessing organizational AI governance posture. AGM v1.0 produces a structured 11-section assessment covering shadow AI detection, agent inventory, input and output verification, access controls, dormant capabilities, and a prioritized risk register.

AGM assessments are structurally independent — Stratalize has no affiliation with any AI model provider and no financial relationship with vendors assessed. Every finding is independently derived from connected system data, not from vendor-provided documentation.

Assessment Scope

AGM v1.0 assessments cover:

1. Connected Systems Analysis

Statistical sampling of AI-assisted documents across connected platforms. Sampling methodology: stratified random, 90-day lookback, proportional allocation per system. Confidence: 95%, margin ±5% for populations exceeding 10,000 documents.

2. Shadow AI Detection

Detection of ungoverned AI tool usage via identity provider authentication logs, MDM signals, and attestation ledger refusal events. Sources vary by connected system availability.

3. AI Agent Inventory (STRLZE-BoM-v1)

Enumeration of all AI tools, models, agents, and data flows active in the assessment period. Formatted as an AI Bill of Materials using Stratalize BoM schema v1.

4. Input Verification

Classification accuracy assessment, sensitivity tier compliance verification, and training data exposure quantification for AI inputs.

5. Output Verification

Claim extraction and grounding verification for AI-generated outputs. Cross-vendor consistency detection across multiple AI systems. ZK-proven authorization coverage percentage.

6. Permissions and Access

User access review including ghost user detection, over-provisioning identification, and sensitivity tier distribution.

7. Dormant AI Capabilities

Identification of available AI features with low or no adoption across connected platforms.

8. AI Stack Optimization

Recommendations for maximizing current stack utilization, agent optimization, and capability gap identification.

9. Framework Awareness

Light-touch mapping to relevant governance domains: model risk governance, data classification policy, AI inventory, access control, incident management. Not a compliance certification.

10. Risk Register and Remediation Roadmap

Prioritized action items with severity classification and resolution tracking.

Cryptographic Attestation

Ed25519 Signed

Report data and findings are signed with Stratalize's Ed25519 private key. The corresponding public key is published at trust.stratalize.com/keys/signing-key.pub.

Base Mainnet Anchored

Merkle roots of attestation events are anchored hourly on Base mainnet via the AttestationAnchor contract.

View contract on BaseScan

Independently Verifiable

Any report can be verified at trust.stratalize.com/verify/[id] without contacting Stratalize.

Limitations

AGM v1.0 assessments are point-in-time. They reflect the governance posture at the time of assessment and do not guarantee ongoing compliance. Stratalize assessments are not regulatory certifications. Organizations are responsible for determining applicable regulatory requirements in their jurisdiction.

Version History

VersionDateNotes
AGM v1.0May 2026Initial release