01 / MENUTOUR / CONNECTED F&B PLATFORM
In development · Pilot target: August 2027
The Commerce Graph for Food.
Discover a dish, place an order and look forward to your next visit. MenuTour is developing a platform that connects the records customers, restaurants and suppliers currently keep in separate systems.
A great restaurant remembers you.
Your favorite dish. The drink you ordered with it. The way you like to spend an evening. A great restaurant builds on what it knows about you.
Every visit leaves a trace. But reservations, orders, payments, reviews and preferences still live in separate systems.
Connect those records, and the reasons behind the next choice become clearer.
From the dish you choose to your next meal.
GUEST EXPERIENCE · PERSONAL DISCOVERY
What you love. What you need to avoid.
An allergy shared before a visit. A drink ordered with a favorite dish. Remembering these details changes the way a menu is suggested.
CURATED FOR YOUYour taste. Thoughtfully served.
A PERSONAL PAIRINGBeef steak + cola
- 01Allergies first
Check the guest’s registered crustacean allergy
- 02Check every sauce
Exclude dishes and sauces containing crustaceans
- 03Pair their favorites
Reflect a preference for beef and cola pairings
Feature concept in development · Uses consented records and holds recommendations with unknown ingredients. Confirm ingredients and cross-contact with the restaurant before ordering.
We are developing a journey from menu discovery to booking and ordering, with shared preferences informing later suggestions. Explore the prepared screen examples below.
Separate apps for discovery, booking, ordering and reviews→Together in MenuTour
MenuTourDiscover
A dish for your taste
Mushroom pasta
Savory flavors · With wine
- Discover
- Book / join waitlist
- Order
- Payment
- Review
- Return
Illustrative screens for a service in development. No booking, order or payment is made here. Supply reviews use aggregates that exclude personal requests.
From guest requests to orders, operations and supply.
Connect guest requests with actual orders to inform menu suggestions and restaurant operations.
DOCUMENTED BUILDPRODUCT IMPLEMENTATION · 2024
- 01HUMAN CONTEXT
- 02STRUCTURED INTENT
- 03MENU DATA
- 04MT TRANSACTION ID · EXAMPLE MTX-9F28A1
- 05MENUTOUR POS
- 06Payment
- 07Receipt
- 08Dining records
Ingredients, prices and pairings belong with the menu.
DISH
- Ingredient
- Price
- Dietary
- Pairing
- Availability
- Context
Menu information and visit requests connect with orders, payments and reported experiences to inform later suggestions and operations.
Future integration: we are preparing to connect order and payment records from external POS systems. Confirm supported scope during adoption discussions.
REGISTERED PATENTKR 10-2453378→How we collect information
Does the service collect every kind of information described in the patent?
The technology described in the patent is distinct from the information collected by the service. A patent description is neither a collection list nor consent. MenuTour is being developed to explain the information needed for each feature and its purpose, and to use information within the scope of explicit user consent.
Will SNS or wearable information be collected automatically?
This introduction website does not connect to SNS or wearable accounts or collect their data. If such integrations are offered in a future service, our principle is to explain the information, purpose, retention and disconnection process and obtain separate consent before collection. Describing technology in a patent does not automatically collect account information.
Demand begins with a human decision.
We aim to aggregate which menus were chosen, where and when, and the responses they received, to inform supply proposals and inventory and production planning.
Menu responses can inform a supply proposal.
For example, more mushroom orders and positive reviews across a restaurant group could inform a supplier’s ingredient proposal. We envisage using subsequent order volumes to review inventory and production plans.
A long-term direction requiring usage rights and data quality. Personal booking requests and contact details are not passed to suppliers. Observed responses do not establish purchase causes or fixed production quantities.
Explore supply collaborationTurn a request understood by AI into a real dining experience.
LONG-TERM ARCHITECTUREAPI · MCP · TOOLS
Our goal is to connect dining requests received by AI with menu, booking and ordering information.
A request for mushroom dishes and wine in a quiet setting needs real menu, price and availability information. MenuTour is preparing a structure to connect that information with booking and ordering functions.
Explore the technical connection
API · MCP · Tools
A design for future integrations, not a claim of partnerships or live connections with particular AI services.
Product records and scope to discuss.
Screens from the 2024 implementation. They do not establish current service availability or operating results.
Scope is discussed around existing devices, payment methods and required workflows.
External POS integrations, AI connections and aggregated demand analysis are long-term development directions, not currently offered features.
Product implementation screens from 2024. Figures are not current operating results; inquire about availability.