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Hospitality 5 months

Hotel Revenue Management System for BoutiqueStay

Built an AI revenue management system that improved RevPAR by 22% across 45 boutique properties in 8 cities.

Machine Learning Custom Software Development Data Analytics & BI
Verified Results NDA Signed US-Based PM Fixed Price
+22%
RevPAR Improvement
45
Properties Managed
Hourly
Rate Update Frequency
+35%
Direct Bookings
+22%
RevPAR Improvement
45
Properties Managed
Hourly
Rate Update Frequency
+35%
Direct Bookings

The Challenge

BoutiqueStay's 45 properties were setting rates manually using basic spreadsheets, updated weekly. They were consistently underpricing during demand surges and not adjusting quickly enough for local events, leaving significant revenue on the table.

Our Solution

We built an AI revenue management system that pulls data from 12 signals — local events, weather, competitor rates from OTAs, historical patterns, and current bookings — to update room rates every hour across all channels automatically.

Our Approach

ML models were trained on 5 years of booking data per property. Event detection uses a custom scraper for local events calendars. Pricing rules allow properties to set guardrails while AI handles optimization within those bounds.

"

Our revenue per room has increased 22% since deploying TechVerse's system. The AI catches demand opportunities we were completely missing — local events, competitor price drops — and responds in minutes.

A
Andrew Blake
VP Revenue, BoutiqueStay Hotels

Project Details

ClientBoutiqueStay Hotels
IndustryHospitality
Timeline5 months
Team Size6
ROI340

Technologies Used

Python Django React PostgreSQL Redis Celery AWS Scrapy Opera PMS API Docker
3 slots open · AI-first development

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150+
Projects Delivered
80+
Happy Clients
98%
Satisfaction Rate
48h
Average Kickoff