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    Migrating from Public ChatGPT to Private LLM

    Quick Answer

    Companies switch from public ChatGPT to private LLM deployment when data control, compliance, and predictable cost become non-negotiable. A successful migration usually starts with sensitive workflows first, then expands once monitoring and policy controls are proven.

    Recommendation: Prioritize data-boundary design and workload segmentation before model tuning or infrastructure optimization.

    The Detailed Breakdown

    A private LLM migration should follow a staged plan to reduce risk and service disruption.

    Control and cost are primary migration drivers

    Why teams switch

    Common drivers are PHI or PII controls, contract requirements, and rising per-token spend at scale.

    Segmented routing lowers migration risk

    Data handling design

    Map which data can stay public and which must stay private. Build explicit routing rules before cutover.

    Phased rollout reduces downtime risk

    Infrastructure planning

    Choose managed private cloud or on-premise based on support capacity, latency needs, and compliance constraints.

    Lower unit cost at sustained high volume

    Cost comparison over time

    Public APIs can be cheaper for low volume. Private deployment usually gains advantage as request volume and sensitivity increase.

    Who This Is For / Who This Is Not For

    Who This Is For

    • Teams processing sensitive data in production
    • Organizations with strict audit and residency policies
    • Businesses with high monthly model usage
    • Leaders needing stronger control over AI operations

    Who This Is Not For

    • Low-volume experimental teams with non-sensitive data
    • Organizations without internal security ownership
    • Projects that cannot allocate migration planning time
    • Teams expecting immediate one-day cutover

    Our Recommendation

    Migrate in phases: map data boundaries, deploy private inference for sensitive workflows, and keep non-sensitive traffic on public systems where appropriate.

    • Document which workflows move first and why
    • Set latency, quality, and cost targets before cutover
    • Use /book to plan migration architecture and timeline
    Book Your Strategy Call

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    Apply private LLM selection criteria

    Frequently Asked Questions

    Can we migrate only some workflows first?

    Yes. Most organizations move sensitive workflows first and keep non-sensitive tasks on public services during transition.

    What is the first technical step?

    Data classification and routing design should happen before model or infrastructure decisions.

    How long does migration usually take?

    Pilot migration often takes 4 to 8 weeks, depending on integration complexity and compliance review cycles.