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AI Remediation Sprint

A four-to-six-week engagement that closes the most critical two or three gaps from a prior AI readiness or privacy assessment, with concrete acceptance criteria and integration with the client's existing team.

Who this is for

  • Companies that have an assessment in hand — from Clariflying or another firm — and need the recommendations actually executed before launch, audit, or budget cycle close
  • Teams whose internal engineering capacity exists but doesn't have senior AI/ML or privacy program management experience to drive multi-stakeholder remediation work
  • Buyers with authorization to fix specific problems but not authorization to hire a fractional leader for nine months
  • Organizations whose AI deployment timeline is tight enough that 'build the capability internally over six months' is not viable
  • Particular fit: healthcare and fintech companies where a completed assessment identified specific compliance gaps (HIPAA, CCPA, or SOC 2) and need senior program management support to close those gaps before the next audit cycle or product launch

What you'll get

  • Detailed remediation plan for the two or three highest-priority gaps from the source assessment
  • Hands-on program management of the work — scoping for the client's engineers, vendor coordination where needed, acceptance criteria definition, validation of outputs
  • Weekly progress updates to the executive sponsor
  • Final state report comparing pre-sprint and post-sprint posture, suitable for board, audit, or regulator-facing documentation

Timeline

Four to six weeks from kickoff to delivery

How it works

  1. 1

    Kickoff call

    Confirm scope based on the source assessment and identify the two or three priority gaps

  2. 2

    Detailed work plan

    For each gap — what gets done, by whom, with what acceptance criteria

  3. 3

    Embedded execution

    Typically including 2-3 weekly working sessions with the technical team plus async coordination through existing client tools

  4. 4

    Validation phase

    Confirm each gap is closed against acceptance criteria

  5. 5

    Final state report

    And 60-minute walkthrough with the executive sponsor

Why work with me on this

I led 14 engineers delivering AI/ML data infrastructure at Apple — the work was program-managing teams that closed exactly the kinds of gaps an assessment identifies. Most consultants stop at recommendations because the implementation work is harder, slower, and politically messier. The remediation sprint is the part that actually gets you to launch. Customer-facing AI work (chat, voice, transcripts) and privacy program work (GDPR, U13, PII masking) are areas of particular depth.

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