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
endReferenced by