AI ChatBot Pro records front-end conversations in its own tables (typically wp_chatbot_conversations for the session header and wp_chatbot_messages for each turn). The model and the response live in the vendor's cloud while the conversation is open. Once the turn is over the artifact (bot ID, user identifier, message text, timestamp and intent) sits in your WordPress database.

That artifact is what support and content teams need a real list for. SleekView reads the conversation header and joins the messages back, then surfaces bot, user, intent, message count and last-message timestamp as real columns. Sort by recency, filter to a single bot, scope to logged-out visitors only, or pull every conversation tied to a specific user.

Edits on related records (a logged-in user, a linked support ticket post type) run through standard WordPress CRUD. Conversation rows themselves are read-mostly: SleekView surfaces them as a queryable list rather than a static chat history page.

Chatbots produce volume that the default plugin admin was never designed to triage. A flat conversation history is fine for the first few weeks and miserable by month three. SleekView reads the same wp_chatbot_conversations and wp_chatbot_messages rows and turns them into a queryable list with bot, user, intent and message count as real columns.

Support staff triage escalated conversations in seconds. Sales filters to high-engagement sessions on the sales bot. Governance audits chatbot answers across bots and date ranges without a custom query.

Same data, same plugin, very different operating posture.