Product AI-Driven No Show and Fake Reservation Catcher
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AI-Driven No Show and Fake Reservation Catcher

By RobosizeME
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RobosizeME's AI-Powered No-Show and Fake Reservation Catcher

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Stephen Burke
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Ralph Melis

Hotel and travel distribution technology

About Ralph Melis

Overview

Launch year

2024

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Compatible integrations

8

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Description

RobosizeME introduces an innovative, AI-driven anti-fraud detection system designed to verify reservations based on specific parameters. This smart solution significantly reduces no-shows by assigning a risk score to each reservation. The higher the score, the more likely a no-show becomes, allowing hotels to take proactive measures.

Details

Infrastructure detailsCloud
Support languagesEN
CategoryRobotics and automation
SubcategoryAutomation Solutions
Integrations

Integration to PMS required (API or UI). Alternatively, a daily data extract can be submitted.

IndustryHospitality

Screenshots, videos and other resources

Product features

Automation

Workflow Automations
Alert Aggregation And Distribution
Pre-Assessment And Prioritizing Data
Digital Workers

Payment processes

PMS Processes

Data processes

Reads data from PDF reports
Extracts columns or rows
Copies and pastes from a file to another
Builds new reports
Sends reports by email
Converts data format

Other processes

AI-powered process automation
Machine learning integration

Support Level

Office Hours Online Support
Dedicated Account manager and Implementation Manager
Dedicated customer success manager
Dedicated onboarding specialist

Integrations

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OPERA Cloud Property Management

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Vendor: Oracle HospitalityCategory: Hospitality operationsSubcategory: Property Management System (PMS)
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OPERA 5 Property Management

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Vendor: Oracle HospitalityCategory: Hospitality operationsSubcategory: Property Management System (PMS)
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Shiji Enterprise Platform

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Vendor: ShijiCategory: Hospitality operationsSubcategory: Property Management System (PMS)
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Apaleo Open PMS

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Vendor: ApaleoCategory: Hospitality operationsSubcategory: Property Management System (PMS)
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protel Air cloud PMS

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Vendor: XN Protel SystemsCategory: Hospitality operationsSubcategory: Property Management System (PMS)
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Maestro PMS

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Vendor: Maestro PMSCategory: Hospitality operationsSubcategory: Property Management System (PMS)
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Mews PMS

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Vendor: MewsCategory: Hospitality operationsSubcategory: Property Management System (PMS)
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Cloudbeds PMS

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Vendor: CloudbedsCategory: Hospitality operationsSubcategory: Property Management System (PMS)

Technical specifications

Specifications

We recommend the RobosizeME hosted option: With the RobosizeME hosted option, all operations are managed on our RPA infrastructure. We provide virtual machines, and as our client, you will need to whitelist our IP addresses. The automations connect to your applications within our environment.

Configurations

The configuration varies from system to system but is usually straight forward. One of our technical experts will guide you through all required steps.

For the automation to run successfully, we need to have insights to your No Show history as well as a few parameters defined by you (average lead time, ADR per room type, etc.).

Scalability

All of our automations are cloud-hosted, which allows for incredibly quick adaptation to changes as well as easy scaling. Therefore suitable for individual hotels, central offices and hotel chains of all sizes.

Fee structure

Monthly Flat Fee
Starting from:
$163
Pricing:

One-Time Implementation Fee of €599.00. Therafter €149.00 ($163)** per property and month.


**Starting price. Price depends on the number of reservations the automation needs to check on a monthly basis. Up to 2’500 reservations are €149.00 a month, up to 6’000 reservations are €339.00. 

Buyers

FAQs

How do I get started?

This could not be any simpler. Provide a daily PMS reservation extract - we specify the exact criteria based on your PMS and can assist in the extract creation.

Can I use this automation with my PMS?

This automation works with any PMS as long as we have insights in your reservation details on-the-books.

What's the ROI when I implement this use case?

Preventing just two potential no-shows monthly covers the investment.

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