What the client needed
RoomPriceGenie helps independent hoteliers optimize room rates using market demand, competitor data, and property management signals - updating prices frequently without manual spreadsheet work.
The platform needed reliable ingestion from external pricing and booking sources, fast search across large rate histories, and integrations with dozens of PMS and channel manager partners.
How SparkScribe approached it
Before build, SparkScribe worked with RoomPriceGenie to translate their SaaS Platform goals into an actionable plan - not an off-the-shelf template.
Discovery & planning
- Reviewed PMS and channel manager partner requirements before designing rate recommendation push flows.
- Separated market data ingestion, pricing analytics, and hotelier override UX into clear ownership layers.
- Validated autopilot vs. co-pilot modes with lean hotel teams who need transparency before trusting automation.
Our engagement covered Backend development, Data pipelines, API integrations, Search infrastructure - scoped in phases with staging parity and admin self-service so RoomPriceGenie could run day-to-day operations without waiting on engineering.
How we solved it
SparkScribe contributed to the Django core - REST APIs, admin workflows, and AWS-hosted services - alongside Scrapy-based market data collection and Elasticsearch for pricing analytics and search.
Integration layers push rate recommendations back to partner systems while keeping hoteliers in control through transparent autopilot and manual review modes described on roompricegenie.com.
How we helped the client
RoomPriceGenie remains a trusted RMS for independent hotels worldwide - with integrations across 70+ PMS and channel platforms and pricing updates driven by live market signals.
- Data reliability: Pipelines ingest competitor and market signals for rate recommendations hoteliers can understand and override.
- Search at scale: Elasticsearch supports analytics and lookup across large pricing histories.
- Partner ecosystem: API integrations align with the PMS connectivity RoomPriceGenie markets publicly.
- Operator trust: Autopilot automation with co-pilot control matches how lean hotel teams actually work.
Technologies we used
Technologies we used
- Django
- REST
- Scrapy
- AngularJS
- Elasticsearch
- AWS
How we applied the stack
Django REST APIs and admin workflows anchor the product core on AWS. Scrapy collects competitor and market pricing signals; Elasticsearch indexes rate histories for analytics and search. Integrations push recommendations back to 70+ PMS and channel partners while preserving hotelier control.
