AI Mojo Pro acts as a single front-end to several model vendors and keeps its own history of every prompt and response. The cloud owns the model call. The plugin writes a row in its history table (typically wp_aimojo_history) for each run, and stamps generated posts with the model and run reference in wp_postmeta.

That history is exactly what an editorial or ops team needs to govern multi-model usage. SleekView reads the same rows. Title, status and author sit next to model, prompt template, tokens and run timestamp as real columns. Sort by date, filter to one model, or pull every published row tied to a specific prompt template.

Inline edits on related posts go through standard WordPress CRUD, so save_post hooks still fire. The history rows themselves are read-mostly: SleekView surfaces them as a queryable list rather than a credit-usage chart.

AI Mojo Pro routes prompts to several model vendors, which means the history table is more valuable than usual: it is the only place that records which model wrote what at what cost. The default dashboard turns that history into a credit-usage chart, useful for monthly reporting and not much else. SleekView reads the same wp_aimojo_history rows and renders them as a queryable list with model, template and tokens as real columns.

Editorial sees draft posture next to model. Ops sees the actual model mix instead of an aggregate. Governance traces a specific run from prompt to published post.

Same data, same plugin, very different operating posture.