The Revenue Management & Pricing System for Hospitality
Propeter sits alongside your PMS. It reads your inventory, reservations and occupancy, combines them with market and competitor data, and produces explainable rate recommendations. Your team approves them, individually or in bulk, and approved rates are published through your connected PMS and distribution systems.
You decide
Every rate approved before it publishes
Your PMS
Stays your system of record
Hourly
Recommendation runs by default
Your team checks explainable risk flags
Recommend, Review, Approve, Publish
Every rate Propeter influences goes through the same four steps, and the decision to publish always sits with your team.
- 1. Data in: Propeter syncs room types, rate plans, inventory, reservations and occupancy from your PMS, and adds competitor rates (from your Lighthouse subscription or competitors you configure) and, where enabled, scored local events from PredictHQ.
- 2. Forecast and recommend: demand forecasts and per-room-type price-elasticity estimates feed a pricing run (hourly by default), which applies your strategy and guardrails and produces a recommended rate for each room type and date.
- 3. Review and approve: recommendations land in an approval queue with their calculation inputs and risk flags. Your team approves individually or in bulk; recommendations that break your rules are blocked.
- 4. Publish: approved rates are published through your connected PMS where the integration supports rate publishing, and from there to your distribution systems. Every approval is logged with the user who made it.
Propeter Is Not a PMS. It Works With Yours.
Your PMS stays your system of record for reservations, folios and the night audit. Propeter reads from it and publishes approved rates back to it where the integration supports that. Exactly what is exchanged depends on the PMS and is confirmed during implementation planning.
- RMS Cloud: two-way. Propeter reads configuration, inventory, reservations and occupancy, and publishes approved rates back
- Oracle OPERA Cloud: integrates through supported OHIP/OXI interfaces; active
- Mews and Cloudbeds: both integrations active; data exchanged and scope are confirmed during implementation planning
- Channels: approved pricing is distributed through supported PMS and channel connectivity, alongside your channel manager
Failures Are Visible and Recoverable, Not Silent
PMS APIs time out, credentials expire and vendors run maintenance. Propeter is built so that when an integration fails, your team can see it and the work can be recovered.
- Reservation delivery uses durable queues, retries, idempotency keys and a dead-letter queue
- Idempotency keys prevent duplicate processing of retried requests
- Scheduled integration health checks and a sync-failure log your team can review
- Cloud-hosted: pricing and direct booking do not depend on your on-site internet connection
One Pricing Workflow, From One Property to a Portfolio
Hotel groups and management companies run the same recommendation and approval workflow for each property, with a portfolio view across them and access scoped to the properties each person manages.
- Property and portfolio dashboards for occupancy, ADR, RevPAR and pickup, refreshed as PMS data syncs
- Role-based access control, with property-scoped access for owners
- Strategies and guardrails set per property, reviewed in one place
Architecture Built for Accountable Pricing
The details technical evaluators usually ask about first.
Tenant Data Isolation
Tenant data is isolated with PostgreSQL Row-Level Security; property-level access is enforced by roles.
Tamper-Evident Audit Log
Rate overrides, approvals and user actions are logged with time and user, in a hash-chained audit log that makes tampering detectable.
PMS Integrations
RMS Cloud, Oracle OPERA Cloud (OHIP/OXI), Mews and Cloudbeds integrations are active. Scope is confirmed during implementation planning.
Forecasting & Elasticity
Gradient-boosted occupancy forecasts and per-room-type price-elasticity estimates built from your own booking history.
Queued Background Processing
Pricing runs, PMS syncs and deliveries run as background jobs on BullMQ queues on Redis, so failed work is retried and logged.
Hosted Card Payments
Card payments on the Propeter booking engine are processed by Windcave on its hosted payment page; Propeter never stores card numbers.
How Data Moves Through Propeter
PMS and market data come in, recommendations are produced and approved by your team, and approved rates go back out through your PMS.
PMS & Market Data
Inventory, reservations and occupancy from your PMS, plus competitor rates and, where enabled, local events.
Forecasts, Rates & Approval
Demand forecasts and price-elasticity estimates feed an hourly pricing run that applies your strategy and guardrails. Recommendations wait in an approval queue.
Approved Rates Out, Data Protected
Approved rates are published through your PMS where supported. Tenant data is isolated with PostgreSQL Row-Level Security; property-level access is enforced by roles.
Frequently Asked Questions
Walk Through the Architecture With Our Team
See the recommendation flow, how Propeter would connect to your PMS, and how failures are handled. USD 5 per room per month, all modules included; implementation is scoped and quoted separately.