No. SleekView only reads rows from the mwai_logs and mwai_logs_meta tables that AI Engine Pro already wrote. Every OpenAI call still goes through Meow with the keys, models, and rate limits the plugin manages, so the dashboard never adds AI usage.

No. SleekView caches each chart card for the duration you set on the source and runs indexed group-by queries against mwai_logs. The reads happen in milliseconds and never block AI Engine from writing new log rows on chats or copilot calls.

Yes. mwai_logs_meta stores per-log metadata including the chatbot id that produced the call. SleekView Charts can join logs to logs_meta and group by that key to rank chatbots by total tokens or by call count across any date range.

Yes. AI Engine Pro writes log rows for every feature it ships, with the type column distinguishing chatbot, copilot, image, embedding, and moderation. SleekView can chart all of them on one dashboard or filter each card by a single type value.

Yes. SleekView dashboards have a role scope. Save the AI Engine dashboard for content_lead or finance and only users in that role see it, so editors don't see token costs and finance doesn't have to read chatbot transcripts.

Only if Meow renames the columns SleekView is reading. The mwai_logs shape, with type, model, total_tokens, price, userId, env, and time, has stayed stable across releases, and SleekView shows a clear error if anything ever changes.

Yes. Every saved chart view has a shortcode and a block. Drop it on a frontend dashboard page, scope the page to a client role, and the client sees the Meow numbers without ever logging into the AI Engine Logs screen.

Yes. Every SleekView chart card has a CSV export that pulls the same rows the chart was built on. Use it to hand finance a monthly token-spend file or feed an external BI tool, without touching the mwai_logs table directly.