Make compliance an operational property of every AI-driven workflow. Consent is captured before processing, policies are checked during execution, decisions are traced as they happen, and audit packages assemble automatically.
Track full decision provenance from source data, through every transformation, model inference, rule application, and human review, to final output — creating an unbroken chain of custody.
Signed immutable logs tying outputs to source material
Model version and data version tracking per decision
GDPR Article 22 automated decision-making compliance
Right to human intervention and contestation support
Encode regulatory requirements as executable checks that run inline with business workflows — not as after-the-fact audits. Every decision, not just a sample.
Fair lending (ECOA), discrimination (NAIC), minimization (GDPR)
Continuous bias detection with circuit breakers
Policy versioning with decision-to-version tracking
Automated alerting when compliance thresholds breach
Automatically assemble audit packages with decision records, data lineage, model performance reports, compliance certificates, and exception logs.
NAIC annual AI report generation
EU AI Act conformity documentation
OCC/Fed model risk management packages
Board-level governance dashboards and reporting
Monitor for model drift, bias drift, and performance degradation that could cause compliance violations — with automated Data Protection Impact Assessments.
Data drift and concept drift detection pipelines
Automated DPIA (GDPR Art. 35) and FRIA (EU AI Act Art. 27)
Living documentation that updates as systems evolve
Three Lines of Defense model for AI governance
Full conformity for AI-driven life insurance pricing: risk management system (Art. 9), comprehensive logging (Art. 12), transparency docs (Art. 13), human oversight protocols (Art. 14), and unified GDPR + AI Act impact assessments.
A P&C insurer across 30 states demonstrates NAIC compliance with documented AI governance, explainability for underwriting/claims/pricing, bias testing protocols, and a consumer complaint process for AI-related adverse decisions.
A consumer lender satisfies SR 11-7 expectations: model inventory with risk tiering, validation protocols with challenger testing, drift monitoring, and board reporting. Examination packages auto-generated in hours, not weeks.
Policy traceability
From 5–10% manual sampling to continuous
Less audit prep time
Automated package assembly
Decision monitoring
Every decision checked, not just samples
Not weeks to respond
Regulatory examination readiness
EU AI Act
High-risk system requirements, AI literacy, prohibited practices
GDPR
Automated decision-making rights, DPIA, data principles
ISO/IEC 42001:2023
AI Management System certification standard
NIST AI RMF + SP 800-53
AI risk management and security controls
Let us assess your current compliance posture and design an operational framework that satisfies regulators and auditors.