✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount

AI chatbot for Foody Menu: dish and allergen help in chat

SleekAI binds to the Foody Menu custom post type and its postmeta, then answers visitor questions about courses, prices, allergens, and recommendations in chat using your own OpenAI, Anthropic, Google, or OpenRouter API key.

♾️ Lifetime License available

SleekAI chatbot for Foody Menu

A printed menu is not searchable. A chatbot can be.

Foody Menu and similar menu plugins do a great job of displaying a beautifully styled menu on a WordPress page. The menu items live in a custom post type, organized into categories, with prices, descriptions, photos, and dietary tags. The downside is the same as any printed menu: customers scroll, scan, and give up if the answer is more than two sections deep.

SleekAI sits on top of the menu data. The bot reads the menu item custom post type, the category taxonomy, the price and description postmeta, and any dietary or allergen flags you have configured. It uses that data on every turn, so questions like what's gluten-free under $20 turn into a 3-item list with prices and links to the relevant menu section, not a hopeful guess.

It also remembers context inside the conversation. A diner can ask for vegan starters, then ask about wine pairings on the third option, and the bot will quote both without losing track of which dish they meant.

Workflow

How SleekAI plugs into a menu site

1

Map menu item post type and meta

Expose the menu item post type, price meta, description, dietary tags, and any pairing fields you store. The bot reads them on every turn so the chat can quote real numbers.
2

Surface category and dietary taxonomies

Add the course taxonomy (starters, mains, desserts) and any dietary or allergen taxonomy as filter variables. The bot can then filter dishes by these terms when a diner asks.
3

Tune the persona

Set a system instruction with your house voice and pairing rules. Choose whether the bot can recommend off-menu (it cannot, by default) and whether it can promise a daily special before the kitchen has briefed staff.
4

Choose a model and launch

Drop in your OpenAI, Anthropic, Google, or OpenRouter key. SleekAI streams replies, logs each session inside WordPress, and tracks which dishes are most often mentioned for menu-engineering insight.

Try it now

A typical menu-browsing chat

Visitor on a Foody Menu page asks about allergen-friendly courses and recommendations. The bot reads menu posts and returns the right dishes with prices.

Comparison

Generic chatbot vs SleekAI for Foody Menu

Generic chatbot

  • Cannot read the Foody Menu post type or its postmeta
  • Misses dietary, allergen, and category tags on each menu item
  • Cannot filter dishes by price band or course in a chat reply
  • Loses context across multiple questions inside one conversation
  • Quotes a stale or invented price when the menu changes

SleekAI chatbot

  • Reads each menu item post and its price, description, and tags
  • Filters by course taxonomy and dietary postmeta in one query
  • Remembers which dish the diner just asked about for follow-ups
  • Surfaces recommendations grounded in your own menu, no inventions
  • Logs each chat with model, tokens, and the menu page URL

Features

What SleekAI gives you for Foody Menu

Every item, every detail

Map the menu item post type, price meta, description, and dietary tags as SleekAI variables. The bot quotes from the same data your menu shortcode renders, so a $19 dish is always $19 in chat.

In-chat filtering

Diners type the filter they actually want: vegan, under $20, no nuts. The bot runs that query against menu posts and returns a short, accurate list, with course tags so the visitor can jump straight to the right menu section.

Pairing recommendations

If you store wine and drink pairings on the dish, the bot quotes those too. If not, you can configure a system instruction that lets the bot suggest in-style pairings from the drinks list with consistent house-voice phrasing.

Use cases

Where this chatbot earns its keep

Dietary screening before sit-down

Diners check the menu the night before. Gluten, dairy, and nut filters give them confidence to book. The bot quotes the actual safe dishes instead of pointing them at a long PDF menu.

Price-band browsing

Customers planning a meal often want to stay inside a budget. The bot returns a 2-course or 3-course suggestion under their target, all from real menu items, not invented ones.

Recommendation chats

First-timers ask what's good. The bot offers your own house picks if you tagged them, or asks two clarifying questions and returns three concrete options grounded in actual menu posts.

The bigger picture

Why a menu deserves a chat layer

A restaurant menu is the most overworked content in any restaurant website. Diners scan it before booking, again before arriving, and a third time on their phone while waiting for the host. Every visit is filtered through some private question they did not type into the search bar: can I find something my kid will eat, can I avoid the dairy I had at lunch, what is actually under $20, what is the lowest-effort first course I can order so we get to the main faster.

None of those questions get asked of the menu page directly. They get asked of the server, or worse, of a generic chatbot that has no idea what the menu actually says today. SleekAI changes the calculus.

The bot reads the same menu posts and metadata your shortcodes render. It can filter dishes by course, by dietary tag, by price. It can hold context across three or four turns, so the diner can drill into a specific dish without retyping the original filter.

It can recommend pairings from the drinks list with your own house voice attached. And because it reads the database on every turn, a daily-special post that goes up at 4pm is in the bot's answers by 4:01. The diner gets a real-time answer to the question they were going to ask the server anyway.

The server gets a shorter list of repeated questions. The menu page becomes more than a static document and the website starts doing the work that used to wait until someone walked through the door.

Questions

Common questions about SleekAI for Foody Menu

It works with any menu plugin that stores menu items as a WordPress custom post type with postmeta. That covers Foody Menu, Food and Drink Menu, Restaurant Menu by MotoPress, Five Star Restaurant Menu, and most custom menu builds. SleekAI binds to post type and meta keys, not to a specific plugin.

 

Yes. If your menu posts are translated through WPML or Polylang, SleekAI picks up the post in the active language. Configure two system instructions, one per language, and display conditions on locale will route visitors to the right bot.

 

Yes. The chat supports markdown image rendering. If your menu item posts include a featured image, the bot can reference and link the image URL when the diner asks what does it look like, without copying every photo into chat by default.

 

Yes. The bot reads the database on every turn, so if you publish or unpublish menu items the chat reflects that immediately. No reindex step is required, which makes it good for seasonal menus and daily specials posts.

 

Yes. If a visitor lands on the Starters category archive, the bot uses that taxonomy term as default scope, so what's good defaults to starters. You can override the scope with the visitor's question at any time.

 

Yes. The chatbot only needs read access to your menu. If a diner asks to book a table or place an order, the bot can hand off to your reservation or ordering plugin's standard flow, optionally pre-populating with the dishes they already discussed.

 

Only if you allow it in the system instruction. By default the bot answers from mapped meta only and politely says it does not know rather than invent ingredients. That avoids food-safety problems on allergen-sensitive conversations.

 

In your own WordPress database as a custom post type with model name, token count, originating menu page URL, and the dishes the bot quoted during the chat. That last list is a surprisingly useful dataset for menu engineering over time.

 

Pricing

More than 1000+
happy customers

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EUR

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  • 1 year of updates
  • 1 year of support

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  • Unlimited websites
  • 1 year of updates
  • 1 year of support

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