The platform uses a multi-round optimization loop that pairs Bayesian acquisition with model-based re-ranking to iteratively generate and evaluate content edits against competitor snippets or full pages.

sequenceDiagram
    participant Seeder as Seeder / Ideator
    participant Acq as Bayesian Acquisition
    participant Ranker as Judge / Ranker
    participant Post as Beta Distribution

    Seeder->>Post: Initialize claims with priors
    loop Each Round
        Acq->>Post: Sample highest-potential hypothesis
        Acq->>Seeder: Craft targeted edit
        Seeder->>Ranker: Submit modified content
        Ranker->>Ranker: Compare vs competitor baseline
        Ranker->>Post: Update alpha/beta parameters
    end