A complete AI governance record requires identity context from Entra ID, routing context from MuleSoft, policy decisions from your governance layer, and execution telemetry from Azure or AWS.
Cetus AI's Evidence Fabric connects these disparate logs into a single, cryptographically verified chain of evidence that proves exactly who made a decision, which model was used, what data was processed, and what policy was enforced.
Inputs include Azure Monitor, AWS CloudTrail, SAP BTP logs, Salesforce Event Monitoring, internal ML logs, and Songlines Control policy decisions.
Maintains a dynamic inventory of all systems that make or materially assist decisions affecting individuals.
Detailed evidence of data categories, model versions, policy outcomes, and human oversight for specific transactions.
Record of all approvals, denials, conditions applied, overrides, and review events linked to specific enterprise policies.
Tamper-evident verification linking each governance event to the previous entry to ensure report attestation integrity.
From 10 December 2026, relevant APP entities will have additional privacy-policy transparency obligations concerning automated decisions that may significantly affect individuals' rights or interests.
Requirements for operational risk management, resilience, and information security across regulated entities and their third-party service providers.
The international standard specifying requirements for establishing, implementing, maintaining, and continually improving an Artificial Intelligence Management System (AIMS).
Climate-related financial disclosures requiring entities to report on sustainability risks, including the significant compute and emissions footprint of enterprise AI workloads.
Note: Cetus AI produces technical evidence that supports compliance frameworks. Software alone does not guarantee compliance without appropriate legal, risk, and business processes.
