The Definitive Framework Matrices.
Our diagnostic engine evaluates your technical architecture and documentation against the stringent requirements of the world's leading AI regulatory frameworks.
EU AI Act
2027Providers, deployers, importers, and distributors of AI systems accessing or impacting the European Union market.
Mapped against 84 specific technical control checkpoints across Title III (High-Risk Systems), verifying technical documentation completeness and logging pipeline integrity.
- ->Mandatory risk classification (Unacceptable, High, Limited, Minimal)
- ->Implementation of a continuous quality management system (QMS)
- ->Rigorous human oversight and transparent data governance practices
- ->Compulsory incident reporting and post-market monitoring logging
SOC 2 Type II
CurrentTechnology and SaaS service providers handling sensitive customer data and machine learning workloads.
Correlates AI pipeline telemetry with the standard Trust Services Criteria, ensuring model weights, access controls, and boundary defenses pass audit scrutiny.
- ->Security: Protection against unauthorized logical and physical access
- ->Availability: Systems are accessible for operation and use as committed
- ->Processing Integrity: System processing is complete, valid, accurate, and timely
- ->Confidentiality: Information designated as confidential is fully protected
NIST AI RMF 1.1
CurrentU.S. and multinational organizations designing, developing, or deploying AI risk infrastructure.
Evaluates AI observability workflows, bias mitigation parameters, and risk mapping completeness to validate full operational readiness across all 4 foundational functions.
- ->Govern: Cultivate a culture of risk management and oversight
- ->Map: Contextualize AI risks and establish system limits
- ->Measure: Quantify, assess, and track AI risks and impacts continuously
- ->Manage: Prioritize and mitigate risks based on severity
ISO 42001:2024
2024Global entities operating an Artificial Intelligence Management System (AIMS).
Verifies clause requirement documentation, AIMS resource telemetry, and risk threshold enforcement to accelerate formal certification readiness.
- ->Top management leadership and commitment to AI policy formulation
- ->Resource allocation for continuous AIMS operation and maintenance
- ->Operational planning, risk impact assessments, and systemic treatment
- ->Systematic internal auditing and nonconformity resolution pipelines