Aerial view of a Caribbean coastline with beachfront hotels

More time for your guests.

Agents that handle bookings around the clock, turn reviews into decisions and control kitchen purchasing and costs.

3 scenarios · Tourism, hospitality and F&B Scroll

Operations today

Guest experience is built in service, not in the back office.

Bookings, reviews, inventory and reconciliations take time away from teams that should be serving guests.

01

Unanswered messages

Inquiries and bookings arriving after hours via WhatsApp and social media.

02

Scattered reviews

Comments on Google, TripAdvisor and social media that nobody consolidates.

03

Blind kitchen costs

Purchasing, waste and cost per dish calculated at month-end.

04

Too many platforms

POS, delivery and online travel agency sales reconciled by hand.

Scenarios

Three processes an agent can run today.

Every scenario starts from a real process and is adapted to your rules and systems in the Binaria Scan.

Scenario 01
Booking agentActive
  • 23:12Received an availability request for 4 guests
  • 23:12Checked the booking system and offered 2 options
  • 23:14Confirmed the booking and sent the details to the guest
  • 23:14Saved preferences: anniversary, terrace table
Tourism, hospitality and F&BBooking agent

24/7 bookings and guest service on WhatsApp

The problem. A group of hotels and restaurants receives inquiries and bookings via WhatsApp, Instagram and phone, many after hours. Those not answered in time go to the competition.

  1. 1Answers availability, rate and service questions in seconds.
  2. 2Books directly in your system, with a deposit when needed.
  3. 3Remembers each guest's preferences and special occasions.
  4. 4Escalates groups, events and special cases to the team.
Connects withWhatsApp BusinessInstagramBooking systemPayment gateway
Expected impact
<1 minresponse time
+20%direct bookings
24/7service without extra shifts
Scenario 02
Reviews agentActive
  • 07:00Collected 326 new reviews from Google, TripAdvisor and social media
  • 07:02Classified each comment by topic, sentiment and location
  • 07:03Spotted a rise in wait-time complaints at one location
  • 07:05Sent each manager a summary with real examples
Tourism, hospitality and F&BReviews agent

Smart review dashboard

The problem. A chain receives hundreds of reviews and comments every week across platforms. Nobody can read them all, and recurring complaints surface only after they have hurt the rating.

  1. 1Collects reviews and comments from social media and platforms.
  2. 2Classifies each comment by topic, sentiment and location.
  3. 3Detects trends, recurring complaints and sudden shifts.
  4. 4Summarizes what matters for each manager, with real examples.
Connects withGoogleTripAdvisorInstagram and FacebookDelivery platforms
Expected impact
100%of reviews read and classified
Dailysummary per location
Hoursnot weeks, to spot a problem
Scenario 03
Kitchen cost agentActive
  • 22:30Matched the day's sales with 84 standard recipes
  • 22:32Calculated theoretical usage against actual inventory
  • 22:33Found 12% protein waste at one location
  • 22:35Generated tomorrow's suggested supplier order
Tourism, hospitality and F&BKitchen cost agent

Kitchen purchasing and inventory with recipe costing

The problem. Restaurants buy based on the chef's experience and calculate cost per dish at month-end. Waste and supplier price increases eat into margin before anyone notices.

  1. 1Matches point-of-sale sales with standard recipes.
  2. 2Calculates theoretical usage, actual inventory and waste by location.
  3. 3Costs every dish at current supplier prices.
  4. 4Proposes purchase orders based on demand and stock.
Connects withPoint of saleInventorySuppliersERP
Expected impact
−15%kitchen waste
Dailyupdated cost per dish
+3 ptsgross margin

Implemented cases

Results measured in real operations.

We will soon publish cases with verified figures alongside the teams that use them.

Coming soon

Our first cases, with verified figures.

We are measuring results with the teams that use our agents. Each case will be published with its baseline and the result achieved.

I want to be the next case