Car rental
D-30
Unreserved cars150 cars
D-7
Unreserved cars132 cars
D-1
Unreserved cars67 cars
Rental day passed
Past rental day67 cars unsold
AI Dynamic Pricing for Car Rental · Airlines · Hotels
Demand changes
every day.
Your pricing
should too.
Monetai connects to the backend of your existing booking and inventory systems,
calculates prices based on booking flow and remaining inventory, and learns from live operating results.
Book a consultation
RESULTS
Revenue +14.5% for a leading mobility company
Revenue+14.5%
Payment conversion+23.6%
ARPU+14.5%
After applying Monetai for 12 weeks, revenue rose 14.5%.
Versus the control group, payment conversion rose 23.6% and revenue per user (ARPU) rose 14.5%.
PROBLEM
Inventory not sold today
cannot be sold tomorrow.
Rental days, airline seats, and hotel rooms
are perishable inventory once their selling window closes.
Car rental
Airlines
D-30
Seats unsold54 seats
D-7
Seats unsold32 seats
D-1
Seats unsold12 seats
Flight departure
Past departure12 seats unsold
Hotels
D-30
Rooms unsold20 rooms
D-7
Rooms unsold12 rooms
D-1
Rooms unsold8 rooms
Stay date passed
Past stay date8 rooms unsold
Rental days, airline seats, and hotel rooms have a fixed selling window.
Demand changes with dates, locations, routes, and remaining inventory,
but fixed rate tables and manual work cannot fully keep up.
Price too low means giving up revenue and margin you could have captured.
Adjust prices to booking flow
and remaining inventory.
Car rental Select rate candidates using booking patterns and available cars by location, vehicle class, and rental date.
Airlines Select fare candidates using booking patterns, remaining seats, and time until departure by flight.
Hotels Select room rate candidates using booking patterns and available rooms by stay date and room type.
These industry screens illustrate pricing workflows.
HOW IT WORKS
Keep your existing systems.
Connect the pricing model to the backend.
Monetai connects to your existing RMS, PMS, booking, and inventory systems
without replacing them.
Existing operating systems
Booking · sales
Inventory
RMS · PMS and more
Existing sales channels
Owned web · app
Booking sites
Partner channels
Data integration
Price delivery
AI pricing model
Apply policies · allowed rangeSelect a price candidate
Learn from sales results for the next price selection
Monitoring dashboard
View pricing operations and performance
Monetai does not replace your customer-facing screens or operating systems.
It receives data from your existing booking, inventory, and sales systems, calculates the price to apply,
and sends the result back to those systems and sales channels.
CAPABILITIES
Understand pricing, design the rules,
operate, and learn.
❶ Understand
Understand how price affects demand.
Analyze pricing and booking response
to find opportunities for improvement.
Same price, different booking response
DayPriceBooking response
Weekday$80
Low
Weekend$80
High
❷ Design
Design the rules for pricing operations.
Set target metrics, an allowed price range,
margin thresholds, and approval rules.
Pricing operation rules
Allowed price range
Operate within this range
$50$90
Minimum marginApproval rules
❸ Optimize
Operate prices and learn from results.
Select prices within the allowed range
and apply sales results to the next choice.
Price candidates that meet operating rules
Candidate A$72
Candidate B$80
Candidate C$88
Learn from sales results for the next price selection
Frequently asked questions
What kind of service is Monetai?
Monetai is a B2B AI pricing operations system. It uses price, product, booking, inventory, and demand data to calculate the price to apply within each customer's operating rules. We build it progressively, from pricing structure diagnosis and policy design to live price operations and learning from results.
Do we need to replace our booking or inventory systems?
No. Your existing systems stay in place. Monetai connects to the required backend data, calculates prices, and sends the results back to your existing systems and sales channels. The exact integration method is determined after reviewing your current environment.
What data is needed to get started?
We typically use product and rate data; booking, payment, and cancellation history; remaining inventory; and sales data by time and channel. The required data set is finalized after reviewing the industry and the data currently available.
When do prices change, and who defines the range?
The price-change cadence is designed for each industry and operating model. Monetai reflects remaining inventory, time, booking flow, and seasonality, while minimum and maximum prices, margin thresholds, change frequency, and approval methods stay within rules agreed with the customer. The AI does not change prices without limits.
How do you validate the impact?
Before implementation, we agree on metrics such as revenue, margin, conversion rate, booking rate, and inventory sell-through. We compare a Monetai-enabled test group with a control group using the existing pricing policy through an A/B test, and validate the improvement, sample size, and statistical significance.
How does implementation begin?
We first review your current pricing structure, available data, and pricing decision process. Then we agree on the scope, success metrics, integration method, and pricing guardrails before running a proof of concept in a live production environment.