# A working RMS, included

Rule-based fare-class optimization on live booking data, same platform as reservations and inventory, with analyst override authority on every decision.

- Rule-based class management
- Real-time inventory sync
- Analyst dashboard and overrides
- Included in the per-passenger fee

## Revenue management<br/>doesn't belong in Excel
Spreadsheet workflows lag the booking curve, can't be audited,<br/>and don't scale past a handful of routes.

### Exports lag the booking curve

Analysts work from yesterday's CSV. By the time the surge shows up in the spreadsheet, the seats are gone.

### Class moves get re-keyed by hand

Decision made in Excel, re-entered into the PSS. Two systems, two records, two chances to get it wrong.

### No rules, every flight is manual

Every class open, every bucket close, every fare deck change is a human action. The team caps at the number of routes one analyst can hold in their head.

### No audit trail

Who closed class Y on ZZ-204 last Tuesday? No one knows. Spreadsheets don't log overrides.

## Live data, rule engine,<br/>analyst control

Farel RMS runs on the same database as inventory and reservations. The pace it sees is the pace right now - and every class move it makes lands in inventory the instant it's made.

## What the RMS<br/>actually does
Built into the platform, not bolted onto it.

### Fare classes and buckets

Define them per route, flight, and season; the system applies them automatically.

### Rule-based class movements

Open and close classes by booking window, load factor, or custom rule. Auto or analyst-reviewed.

### Real-time booking pace

Live load factor, velocity, and bucket fill from the same database as reservations. No batch import.

### Analyst dashboard and overrides

Override at the flight, route, or class level. Nothing is locked.

### Channel-aware pricing

Different fares per route, channel, agency, and season. Edit and publish without redeploying.

## The RMS reads from your live database

Standalone RMS systems import PSS data in batches - hourly, every six hours, sometimes once a day. By the time the system sees the surge, the seats are sold. Farel RMS doesn't import anything. It reads from the same records as reservations and inventory, so booking pace, load factor, and bucket fill are accurate to the second.

## Define a rule once,<br/>run it on every flight

Open class Y at 45 days out. Close class M above 75% load factor. Move a bucket down a class when the next one sells out. Rules are defined in plain logic per route, season, or fleet. The system applies them automatically; analysts handle exceptions.

## Overrides land in inventory instantly

A class move in the analyst dashboard writes directly to the inventory record. No re-keying, no batch sync, no PSS round-trip. Channels - direct, agency, OTA, API - see the new availability the moment the analyst confirms.

## Before you decide
Answers to the questions we hear most from airline teams.

### How does this compare to PROS or Sabre Revenue Optimizer?

Different category. PROS and Sabre RM run O&D optimization with ML demand forecasting, designed for airlines with dedicated RM teams using them daily. Farel RMS is rule-based, leg/class-based, and built for airlines that don't have an RMS today and are doing class moves in spreadsheets. If you're already running a best-of-breed RMS and it's working, we integrate with third-party RMS through the platform's open API - the rest of Farel still runs on live data.

### Is this AI or rule-based?

Rule-based today, with ML demand forecasting on the roadmap. The current engine runs on triggers and actions analysts define themselves - readable, predictable, and overridable at every level. The AI layer will sit on top of the same rule engine, not replace it.

### Can analysts override system decisions?

Yes, at any level. Rules, classes, flights, individual bookings. Every override is logged but none are blocked. The system never locks an analyst out of their own pricing.

### What data does the RMS use?

Live booking pace, current load factor, historical sales for the route, fare conditions, and the rules you've defined. All from the same database as reservations and inventory - no exports, no imports, no batch jobs.

### Does it work for charter and ad-hoc flights?

Yes. The same rule engine applies. Aircraft layout, fare structure, and inventory rules work the same way for scheduled and unscheduled service.

### How long to go live?

RMS goes live with the rest of the platform - 2 to 8 weeks. Your team defines the initial rules, fare structures, and class logic - they know the routes and the commercial intent better than anyone. Farel's onboarding team trains, supports, and configures the system around what you bring.