Inferensys

Service

Privacy-Preserving AI Auditing

Independent, technical verification of your AI system's privacy guarantees. We provide defensible audit reports with quantified privacy loss and simulated attack resilience for GDPR, CCPA, and EU AI Act compliance.
Security engineer reviewing FedRAMP compliance dashboard on ultrawide monitor, home office with city views, casual work session.

Quantify and verify the privacy guarantees of your AI systems to meet regulatory scrutiny.

Your privacy claims are only as strong as your evidence. We provide the technical proof you need for GDPR, CCPA, and the EU AI Act.

Our audits deliver defensible, quantitative privacy metrics using industry-standard tools and adversarial testing:

  • Privacy Loss Accounting: Measure cumulative data exposure with frameworks like TensorFlow Privacy and Opacus.
  • Attack Simulation: Stress-test models against membership inference, attribute inference, and model inversion attacks.
  • Gap Analysis: Identify vulnerabilities in data handling, training pipelines, and inference endpoints.

We translate complex privacy guarantees into executive-ready compliance reports and remediation roadmaps. Ensure your AI initiatives are both innovative and legally defensible. Explore our broader approach to Privacy-Preserving AI Computation or learn about building compliant infrastructure with Sovereign AI Infrastructure Development.

PROVEN RESULTS

Business Outcomes of a Certified Privacy Audit

A certified privacy audit from Inference Systems delivers more than a compliance checklist. It provides defensible, technical proof of your AI's privacy posture, enabling trust with regulators, partners, and customers while de-risking your AI initiatives.

03

De-Risked AI Product Launches

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.

>80%
of critical flaws identified pre-launch
04

Optimized Privacy-Utility Trade-off

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.

<5%
Typical accuracy impact post-optimization
06

Competitive Differentiation in Tenders

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.

100%
of sovereign AI RFPs require privacy proofs
Choose the right level of scrutiny for your AI systems

Structured Audit Engagement Tiers

Our tiered audit approach provides clear, actionable verification of your AI's privacy guarantees, from foundational checks to comprehensive adversarial testing.

Audit ComponentCompliance CheckTechnical Deep DiveAdversarial Certification

Privacy Loss Accountant Review

Differential Privacy (ε,δ) Guarantee Verification

Homomorphic Encryption Implementation Audit

Secure Multi-Party Computation Protocol Review

Attack Simulation (Membership/Attribute Inference)

Full Adversarial Red Teaming (MITRE ATLAS)

EU AI Act / GDPR Compliance Gap Report

Summary

Detailed

Detailed + Remediation Plan

Executive Summary & Technical Findings Report

Remediation Support & Consulting Hours

2 hours

10 hours

40 hours

Certification of Privacy Guarantees

Letter of Assessment

Technical Certification

Public-Facing Attestation

Typical Engagement Timeline

2-3 weeks

4-6 weeks

8-12 weeks

Starting Investment

$15K

$45K

Custom

HIGH-REGULATION SECTORS

Industries Requiring AI Privacy Audits

Our privacy-preserving AI auditing services are critical for organizations in regulated sectors where data sensitivity is paramount and compliance claims must be technically defensible. We provide verifiable assessments using tools like privacy loss accountants and attack simulations.

01

Healthcare & Life Sciences

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.

HIPAA/GDPR
Compliance Focus
PHI/Genomic
Data Types
02

Financial Services & FinTech

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.

GLBA/CCPA
Compliance Focus
PII/Transaction
Data Types
03

Defense & Government Contracting

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.

CMMC/NIST 800-171
Compliance Focus
Classified/ISR
Data Types
04

Insurance & Actuarial Science

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.

Algorithmic Fairness
Audit Focus
Behavioral/Health
Data Types
05

E-Commerce & Retail Personalization

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.

CPRA/VCDPA
Compliance Focus
Behavioral/Geo
Data Types
06

Legal & Compliance Technology

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.

Attorney-Client Privilege
Audit Focus
Legal Communications
Data Types
Technical Due Diligence for AI Privacy

Privacy-Preserving AI Audit FAQs

Get specific answers about our technical audit process, timeline, and outcomes for verifying the privacy guarantees of your AI systems.

Our methodology is based on the NIST AI RMF and ISO/IEC 42001 frameworks, adapted for privacy-enhancing technologies (PETs). We use a combination of automated tools and manual analysis, including privacy loss accountants (e.g., Google's TensorFlow Privacy), membership inference attack simulations, and differential privacy verification libraries. We assess the entire pipeline, from data ingestion to model deployment, against your stated privacy claims.

Prasad Kumkar

About the author

Prasad Kumkar

CEO & MD, Inference Systems

Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.

His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.