Not via a built-in connector. SleekAI is a WordPress plugin that reads data the team maps inside WordPress (post types, postmeta, ACF, taxonomies, files). For vcita's hosted scheduling and payments, the bot acts as a pre-booking concierge and hands the visitor over to vcita's own widget on the page. That separation keeps the architecture honest and the data path easy to audit.

Anything you describe in WordPress. A common setup mirrors the service catalog into a custom post type with name, duration, price, policy, and a short description per service, plus a knowledge base of FAQs and intake notes. The bot answers from that mapped data on the page, then hands off to the vcita scheduling widget for the booking step itself.

Yes, in terms of WordPress user role and login state. vcita's own client portal sits in vcita's cloud, so the bot can't read a vcita client record by default. If you mirror key fields back into WordPress as user meta, the bot can use those without a custom integration on the vcita side.

Push them into an OpenAI Files vector store of up to one gigabyte per file. SleekAI handles the upload pipeline, and the model retrieves only the rows that match the question. That keeps the system message clean even for legal-heavy practices with hundreds of policy paragraphs.

Yes. Multibot lets you run several chatbots on one site, each with its own system message, data sources, and display conditions. A consulting-page bot, a coaching-page bot, and a therapy-page bot can coexist under one SleekAI install, each handing off into the relevant vcita service.

Not if you keep slot questions inside the vcita widget. The pattern that works is having the bot answer 'we have weekday-evening openings in May' from the mapped knowledge, then encouraging the visitor to pick a specific time in the vcita widget. That avoids the bot inventing slots that the cloud calendar doesn't actually have free.

Inside WordPress, with user, model, token usage, and page URL on every conversation. The practice owner can review the log to spot tone issues, recurring intake questions, or confusion around policies, and refine the system message or the policy page over time.

Yes. If WPML, Polylang, or TranslatePress translates your service pages, SleekAI reads whichever language is currently active on the request. You can also run separate chatbots per language with their own tone, which is useful when an English-speaking client pool sits next to a Spanish-speaking one.