AutomateWoo stores each workflow as an aw_workflow custom post with the trigger, rules, and actions in postmeta. Runs are recorded in wc_automatewoo_log. Abandoned cart sessions sit in wc_automatewoo_carts with status, customer ID, total, and timestamps. Guest customer activity is captured in wc_automatewoo_guests, and queued runs live in wc_automatewoo_queue. Figuring out which abandoned cart workflow recovered a specific order requires joining the carts table to WooCommerce orders by customer.

SleekAI exposes the workflow post type, the AutomateWoo tables, and the related WooCommerce orders as named variables. An admin types, how many orders did the abandoned cart workflow recover last month, and the bot queries the carts table, joins to wc_orders, and quotes the recovered revenue. Display conditions limit the bot to store managers and admins. A separate logged-in customer bot can read the customer's own active subscription or follow-up status under multibot.

Generic chatbots cannot query AutomateWoo's custom tables, and they have no concept of a workflow trigger or a queued run. SleekAI's Wizard maps the workflow post type, the log table, and the cart table in two clicks. Conversations log model name, tokens, and the page each question came from. Operations teams see which workflows actually break most often and which abandoned cart copies recover the most revenue per send, which informs the next quarter's plan.

AutomateWoo is the revenue engine on most serious WooCommerce stores. Abandoned cart emails, win-back campaigns, review requests, follow-ups, and subscription renewal reminders all run through it. Each of those workflows touches money.

When something stalls or breaks, the operations team needs answers in minutes, not hours. The current path is to open the workflow library, the runs log, the queue, the cart sessions, and the customer notes. That is too many tabs for a 9pm incident on a Sunday.

A chat interface compresses that loop. The admin types a plain question, the bot reads the same aw_workflow posts and the same wc_automatewoo tables AutomateWoo writes to, and the answer cites the recovered revenue, the stalled queue size, or the specific SMTP error string. That changes AutomateWoo from a black box with a busy log into an observable system that operations teams trust.

It also means store managers spend more time tuning copy than diagnosing infrastructure. SleekAI surfaces what AutomateWoo already knows, in a place store teams use.