AI-Native Operations Packages

    Choose the first system. Build toward operational leverage.

    Start with a narrow workflow, validate the impact, then move into deeper AI-native systems for coordination, knowledge, automation, and internal operations.

    Progression Path

    1

    Find the leverage

    2

    Fix one workflow

    3

    Keep building with an embedded team

    Service Tracks

    Start focused, or bring us in deeper

    Both tracks produce usable operational assets, not strategy decks that wait for someone else to implement them.

    Focused Workflow

    Operational Leverage Sprint

    You get your biggest workflow improvement opportunities identified, then one painful workflow turned into a working AI-assisted system.

    A focused engagement for teams that want practical proof of AI leverage before making a larger commitment.

    Includes

    Workflow mapping
    Identification of the highest-leverage improvement opportunities
    1-off workflow rescue
    1 implemented automation or AI-assisted workflow
    Recommendations for future leverage opportunities

    Best For

    Teams that know operations are leaking time and want one concrete workflow fixed first.

    Example Workflows

    Customer intakeInvoicingReportingOnboardingApprovalsFollow-up flows

    Retainer

    Embedded Team

    You get an embedded AI operations team on retainer to keep building, deploying, and supporting workflow systems inside your organization.

    A continued partnership for organizations ready to move from one-off workflow fixes into an AI-native operating layer.

    Includes

    Retainer model for continued work
    Full Refactory Deployment Package
    AI readiness roadmap
    Ongoing workflow implementations
    Support, iteration, and operational enablement

    Best For

    Teams that want a durable implementation partner for AI readiness, Refactory deployment, and ongoing operational improvements.

    Schedule Consultation

    Tell us what is slowing the team down, what you are trying to build, or where AI feels useful but unclear.