Privacy-Preserving AI Auditing

Move beyond self-attestation with a certified audit that provides mathematical proof of privacy guarantees. Our reports, backed by privacy loss accountants and attack simulations, create a defensible technical foundation for GDPR, CCPA, and EU AI Act compliance, significantly reducing regulatory risk.

Demonstrate concrete, audited privacy controls to unlock B2B data collaborations and sensitive customer applications. A certified audit acts as a trust signal, enabling partnerships in healthcare, finance, and cross-border data sharing where proof of privacy is a prerequisite.

Identify and remediate latent privacy vulnerabilities—like membership inference or attribute inference attacks—before deployment. Our audit provides a clear roadmap to harden your models, preventing costly post-launch fixes, reputational damage, and potential data breach liabilities.

Quantify the exact privacy budget (epsilon) your models consume and receive expert guidance on tuning differential privacy noise or encryption parameters. We help you maximize model accuracy and utility while maintaining mathematically proven privacy levels, avoiding unnecessary performance degradation.

Establish a measurable baseline for continuous privacy monitoring. Our audit integrates with your MLOps pipeline, providing the tooling and benchmarks to track privacy loss over successive model retraining cycles, ensuring ongoing compliance as your AI evolves.

In regulated procurement processes for defense, government, and enterprise clients, a certified privacy audit is a decisive differentiator. It provides tangible evidence of your technical maturity in privacy-preserving AI, directly addressing stringent RFP requirements.

Audit AI systems handling Protected Health Information (PHI) and clinical trial data. We verify compliance with HIPAA and ensure diagnostic models using patient records cannot be reverse-engineered, a key requirement for FDA submissions involving AI/ML.

Technical verification of AI used for fraud detection, credit scoring, and algorithmic trading. Our audits measure privacy loss in models trained on transaction histories and personal financial data, ensuring defensibility against regulators like the CFPB and SEC.

Assess AI systems processing classified or sensitive unclassified information. We provide air-gapped audit capabilities and verify that models used for intelligence analysis, autonomous systems, or personnel vetting do not create data leakage vulnerabilities.

Audit predictive models for underwriting and claims processing that use highly personal data (health, driving behavior, property details). We ensure algorithmic fairness and privacy guarantees are mathematically sound to prevent disparate impact claims.

Verify privacy claims for recommendation engines and dynamic pricing AI that process consumer purchase histories, browsing behavior, and location data. Critical for compliance with evolving state-level consumer privacy laws.

Audit AI tools for contract analysis, e-discovery, and litigation prediction that process attorney-client privileged communications and sensitive case data. We ensure these systems uphold legal confidentiality obligations.