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Privacy Consulting for AI Systems

Compliance review and architecture guidance for AI systems facing a specific regulatory trigger — preparing for audit, expanding into new jurisdictions, launching in regulated markets, or responding to board or insurance compliance requirements.

Who this is for

  • Companies preparing for a privacy audit (internal, customer, partner, or non-emergency regulator-driven) of AI systems handling personal data
  • Organizations expanding AI products into new jurisdictions with different regulatory regimes (EU after US-only, HIPAA-regulated states, post-Brexit UK separation, etc.)
  • Teams launching AI features in regulated markets (healthcare, financial services, children's products) where privacy posture must hold up to vertical-specific scrutiny before go-live
  • Companies whose privacy posture must be reviewed for board, investor, or insurance reasons
  • Buyers who have a privacy lawyer but need someone who understands both the regulation and the technical architecture
  • Particular fit: healthcare organizations adding AI to patient-facing workflows, e.g. scheduling, triage, clinical documentation, areas where HIPAA review of the AI system is required before the feature can ship

What you'll get

  • Privacy posture assessment of the AI system in scope, mapped against applicable regulations
  • Identification of specific compliance gaps, ranked by enforcement risk and the specific trigger context
  • Architecture recommendations — where to mask, where to consent, where to retain, where to delete
  • Remediation roadmap with effort estimates
  • Documentation suitable for the specific trigger (audit response, jurisdictional registration, board briefing, insurance review)

Timeline

Two weeks from kickoff to delivery

How it works

  1. 1

    Kickoff call

    Scope the system under review and the specific trigger context — what's driving the review now, who needs the output, what's the deadline

  2. 2

    Architecture and data flow review

    Examine the technical structure of your AI systems

  3. 3

    Stakeholder interviews

    Engineering, legal, privacy, security

  4. 4

    Gap analysis

    Against the named regulations and trigger context

  5. 5

    Written deliverable

    Plus 60-minute walkthrough; remediation guidance as needed

Why work with me on this

I led the data privacy and PII masking work for Apple's customer engagement platform — the kind of system where getting it wrong creates regulatory exposure across dozens of jurisdictions simultaneously. The work covered GDPR, U13, transcript scrubbing, retention design, and the specific architectural patterns that hold up under audit. Most privacy consultants come from a legal background and stop at policy. I work at the layer where the policy meets the data flow.

Frequently asked questions

Which privacy regulations do you cover?

I specialize in GDPR, CCPA, and HIPAA compliance for AI and data systems. I also address emerging AI-specific regulations and can help you prepare for upcoming frameworks like the EU AI Act.

How technical is the privacy audit?

Very technical. Unlike purely legal audits, I examine actual data flows, API integrations, database schemas, and processing logic. This technical depth catches implementation gaps that policy-level reviews miss.

Can you help with privacy engineering, not just compliance?

Absolutely. I design privacy-preserving architectures including differential privacy, federated learning, and secure multi-party computation. Compliance is the baseline; privacy engineering is how you build competitive advantage.

Ready to move forward with confidence?

Let's discuss how I can help you navigate AI implementation and data privacy challenges.

Currently booking May — 1 client slot open