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    Case Studies

    Thirteen production AI workflows.
    One operations team.

    Each case is a discrete workflow we shipped — file extraction, role-scoped assistants, autonomous queue sweeps, browser automation. Real vendors, real metrics, anonymized customer.

    Customer is "Meridian Operations." If a flow looks like one of yours, it probably is.

    Group 01

    Form-extraction pipelines

    Documents come in as attachments. They go out as structured rows in a system of record. File-type detection, reference enrichment, and self-improving via reviewer corrections.

    Group 02

    Role-scoped AI assistant

    One chat surface, five specialists. Each role has its own tool access and its own scope, so cross-domain hallucinations are structurally impossible.

    Group 03

    Autonomous & infrastructure patterns

    The queue checks itself. The mirror prevents rate limits. The browser handles systems without an API. Patterns that run without a person in the loop.

    Have a workflow shaped like one of these?

    If you have a queue where a person reads a document and types it into another system, or a chat surface that needs role-scoped tool access, the same patterns fit. We'll scope it on a 30-minute call.