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Revenue Management Software Development for Hotels and Hospitality Groups

ELITEX are hospitality software development company founded in 2015. Most of our engineers sit at the senior level, which counts for something when a pricing engine moves rates across a few hundred rooms with nobody watching it. We write custom code for hotel revenue management software development, working with teams who have already found the ceiling of what their current pricing setup can do. This page covers how we approach that work and what you can expect from us as a partner.

Related Services

Product Development
Product Enhancement
Legacy Software Modernization
Software Audit Services
Hospitality IT Solutions
Hospitality Software Development Services

What We Build

A revenue system decides what a room should cost and how many of them you're willing to sell at that price. So we build it in parts, and each part has to survive the day the data behind it goes strange.

Demand Forecasting

Forecasts run on your own booking curve and the pace against the same period last year. We keep the model auditable, because a number nobody can explain gets overridden until it stops being used at all.

Pricing and Rate Recommendations

A recommendation engine only earns its place if the revenue manager trusts what comes out of it. ELITEX build the rules and the constraints that hold pricing inside commercial reality, along with the reasoning trail that shows why a rate moved.

Market Data and Rate Shopping

Competitor rate feeds arrive late as often as they arrive complete. So, we build the ingestion layer with staleness handling included, so yesterday's scrape never quietly becomes today's pricing input.

Inventory Controls and Restrictions

Minimum stay and closed to arrival rules are where a forecast turns into an actual decision. We build the controls so a restriction applies at the level you meant it, and so nobody has to guess which rule wins.

Rate Distribution and PMS Handoff

A price that never reaches the channel is a price you didn't set. ELITEX write the handoff into your property management system and out to distribution, including the failure handling for the push that silently doesn't land.

Reporting and Override Tracking

Every manual override is data about where the model is wrong. We build the logs and the variance reporting that compare recommended rates against what actually sold, so the gap surfaces well before quarter end.

Who This Service Is For 

Hotel revenue management software development by ELITEX works best for operators running enough rooms that pricing has outgrown a spreadsheet and a morning meeting. A group with twenty properties and one revenue team splitting attention across all of them fits well. So does an operator whose licensed RMS prices transient demand competently and handles everything else badly. We're the wrong choice if you want a revenue product configured and live inside a month, because we write custom code and don't sell a licence. We're also a poor fit for a single property with steady demand and a short rate structure, since an off the shelf tool will cover that for far less than we will.

Why Choose ELITEX as a Revenue Management Development Partner?

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  • Seniors Write The Code

    Most of our engineers are senior level, and forecasting code punishes the assumptions a junior brings to it. A pricing error crashes nothing. It just costs money quietly for a quarter.

  • Hospitality Work Since 2015

    We've been in this vertical long enough to know how a booking curve behaves against how the textbook says it should. That knowledge saves discovery time you'd otherwise pay for.

  • You Own Everything

    Code and repositories sit in your accounts from the first commit, along with the infrastructure they run on. No lock in, and no licence tying you to us after launch.

  • We Say When Something Won't Work

    If your historical data can't support the model you're asking for, you hear it during discovery. We'd take a smaller project over a rebuild conversation in month six.

Our Hotel Revenue Management Software Development Services

New Build From Scratch

We settle the forecasting model and the rate structure before a single pricing rule gets written, since that foundation is the hardest thing to change once decisions depend on it. Pricing logic comes first, and the dashboards come after the numbers hold up against history.

Replatforming Away From a SaaS RMS

Many of our clients have outgrown a hosted revenue management system and need the same pricing logic running on software they control. So ELITEX rebuild the forecasting layer and the rule engine on an owned stack, matching current behaviour first and improving it second.

Integration Layer

A PMS and a channel manager rarely agree on what a rate plan means, and that disagreement shows up as a price that moved everywhere except where it mattered. We build the translation layer that reconciles those definitions, including the cases where one system counts a group block as sold while the other still shows those rooms as available.

Data Migration

In case of migration, we map historical reservations and rate history onto the new schema, then reconcile both datasets before the old system gets switched off. A full season of parallel running catches what the mapping missed.

Custom Module Work

The system stays, and one piece of it gets built or replaced. Group displacement analysis and length of stay pricing tend to be the modules clients want written to their own commercial rules.

Maintenance and Support After Launch

Someone has to notice when a rate shopping feed changes format without warning. That's why ELITEX keep the data pipelines current and stay available for the incidents that land at the wrong hour.

How We Work

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Discovery and Requirements

First, we look at how pricing decisions actually get made today, including the spreadsheet the revenue manager trusts more than the system. The overrides tell us more than the requirements doc does.

Architecture and Integration Mapping

Then, we decide which system owns the rate and which one only displays it. Every data feed gets documented at this stage, including the market report someone still downloads by hand each Monday.

Data Model and Migration Planning

Demand history and rate structures get designed here, because a forecast is only as good as the record behind it. Migration scope is settled at the same time.

Build

After that, the work ships in slices, with each release covering a working part of the pricing engine. Our engineers use AI tooling for code generation and review, which cuts the time spent on boilerplate and leaves more of the budget for the logic that needs judgment.

Testing and Hardening

We backtest the model against seasons you already lived through, since a forecast that fits last year badly won't do better next year. Load testing covers the nightly repricing run.

Launch and Support Handover

Finally, cutover runs in shadow mode first, with recommendations produced and nothing published. Your team gets documentation and a handover period with the engineers who wrote the code.

Revenue Management Integrations ELITEX Handle

When a system has no documented API, we build the connector ourselves. File based feeds and screen level integrations are both workable, and we've done both.

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  • PMS Platforms

    Opera Cloud, Mews, Apaleo, RoomRaccoon

  • Channel Managers and Distribution

    SiteMinder, Cloudbeds

  • Market and Rate Shopping Data

    Lighthouse, STR

  • Reporting and Analytics

    Snowflake, Power BI

Compliance and Data Handling

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Payment and Reservation Data

A revenue system reads reservation records, and those records often arrive with payment details still attached. We keep card data out of the pricing layer entirely, which leaves PCI scope where it belongs, with your processor.

GDPR and Data Residency

Guest booking history feeds the forecast, so storage location becomes an architectural decision at design time. We build for hosting that matches whatever your market requires.

Access Control and Audit Logging

Revenue staff and property teams need different rights over what a rate is allowed to do. Every override and every published rate change gets logged with the user behind it, which settles the argument about who dropped the price on a sold out night.

Guest Data Retention

Booking history carries forecasting value and a shelf life that regulation defines. We build retention rules into the data layer, keeping aggregated demand curves alive after the personal records expire.

FAQs

Still have a question?

Reach out to our specialist!

Let's talk about your project

Drop us a line! We would love to hear from you.

Kate
calendlyBook a calllinkedInKate PrysiazhnaPartnership Manager
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