AI chatbot for WPBakery Page Builder: read your real shortcode content
SleekAI parses the headings and text inside WPBakery's vc_* shortcodes, so the chatbot answers with the real copy on each page instead of guessing. Bring your own OpenAI, Anthropic, Google, or OpenRouter key.
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A chatbot grounded in your WPBakery page content
WPBakery stores layouts as nested shortcodes inside wp_posts.post_content, with row, column, and module attributes encoded inline. SleekAI's Wizard reads post_content and exposes a parser for common WPBakery shortcodes like vc_row, vc_column_text, vc_custom_heading, and vc_tta_accordion. The chatbot's system message receives the extracted heading and body text per section, in order, instead of raw shortcode soup.
That keeps the bot grounded in what the page actually says. When a visitor asks about a service the page advertises, the model has the section heading, the body copy, and any FAQ items captured from accordion modules, so the answer matches the real wording on the page. Edits in WPBakery show up automatically because the parser runs at request time.
Multibot scopes different chatbots to different page templates, so a services bot, a pricing bot, and a docs bot each read only the sections they need. For larger sites, push the extracted text for each page into an OpenAI Files vector store of up to one gigabyte per file. Conversation logs save every question with the model name and the page URL.
Workflow
How SleekAI plugs into WPBakery Page Builder
Enable the shortcode parser
Scope per template
Bring your own key
Review the logs
Try it now
A typical WPBakery visitor conversation
Comparison
Generic chatbot vs SleekAI for WPBakery Page Builder
Generic chatbot
- Sees raw shortcode soup, not real content
- Can't follow accordion or tab content
- Loses section structure on every page
- Mixes module text with attribute noise
- No way to scope answers per template
SleekAI chatbot
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Parses
vc_row,vc_column_text,vc_custom_heading,vc_tta_accordion - Extracts heading and body per section in order
- Per-template chatbots via display conditions
- OpenAI Files vector store for big sites
- Logs every conversation in WordPress
Features
What SleekAI gives you for WPBakery Page Builder
Shortcode-aware parser
The data source recognises common WPBakery modules and extracts the real heading and body text per section, so the prompt receives clean content instead of nested shortcode attributes.
Per-template bots
Scope different chatbots to different page templates using display conditions on post type, URL pattern, and category, so each bot reads only the sections relevant to that page family.
Audit logs
Conversation logs save inside WordPress with the model name and page URL. Use them to find questions your current modules answer poorly and tighten the copy in WPBakery.
Use cases
Where WPBakery sites use SleekAI
Agency portfolios
An agency bot answers questions about services and case studies using the real headings and body text on each page, which keeps the answer aligned with the language the team already approved.
Conversion pages
On long landing pages built with WPBakery rows and modules, the bot answers detail questions inline, so visitors who would otherwise scroll away to a competitor stay on the page and convert.
Internal site search
Run an admin bot that searches across WPBakery pages by extracted section text, so editors can find the page that mentions a specific phrase without remembering the title.
The bigger picture
Why parsing WPBakery shortcodes matters for chat
WPBakery sites tend to have a lot of structure on every page. Rows, columns, accordions, tabs, and custom modules each carry their own copy, and the layout matters: a price near the top of the page is a different commitment from a price hidden inside an accordion. A chatbot that flattens all of that into one long string loses the structure and ends up confused about which heading the answer belongs under.
Parsing the shortcodes properly fixes that. The bot sees a sequence of sections with headings and body, plus a separate list of accordion items, and can quote the right one. The team gets to keep using WPBakery without changing how it builds pages.
The chatbot, in turn, stops sounding like it has only skimmed the page and starts sounding like it has read it. That is the practical difference between a generic AI widget bolted on to a marketing site and a site-aware assistant that the team can trust on a sales page or a service description.
Questions
Common questions about SleekAI for WPBakery Page Builder
Yes. WPBakery layouts live as nested shortcodes inside post_content, and SleekAI's Wizard ships parsers for common module types. The chatbot's system message receives clean text per section, with headings and body separated, rather than the raw shortcode markup. Custom modules can be added through the Wizard's parser configuration.
Yes for the standard vc_tta_accordion, vc_tta_tabs, and vc_tta_tour modules. The parser extracts each panel's title and body and exposes them in order. Custom or third-party tab modules can be added by pointing the Wizard at the matching shortcode tag and field names.
WPBakery's add-ons and custom modules emit additional shortcodes. The Wizard parser can be extended to recognise their tag and attribute names, so the bot reads the right field. For brands of modules the team uses heavily, mapping them once unlocks every page that uses them.
Yes. Grid builders emit a wrapper shortcode and pull child posts based on a query, so the bot can be configured to read the child posts directly through the WordPress data source. That keeps grid content accurate even when the grid query changes.
The parser runs only when a chat message is sent, not on every page load. The chatbot's system message uses extracted text from the current page plus a small set of related pages, so the prompt stays compact even on long layouts. For very large sites, push extracted text into an OpenAI Files vector store.
Yes. Display conditions support post type, URL pattern, taxonomy term, user role, and logged-in state. A services bot can run on service templates, a pricing bot on the pricing template, and a docs bot on docs, all under the same SleekAI install with different system messages.
Yes. The frontend editor saves the same shortcode markup the backend editor produces, so SleekAI's parser does not need to know which interface the editor used. Whatever the editor saves is what the bot reads on the next chat message.
Most legacy themes that ship with WPBakery use the standard module set, which the Wizard parser handles. If a legacy theme adds custom modules, they can be mapped through the parser configuration. Older sites with deeply nested rows still work, since the parser walks the shortcode tree rather than relying on flat HTML.
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