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Modernization of Revenue Management System for Hospitality Industry
  1. case
  2. Modernization of Revenue Management System for Hospitality Industry

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Modernization of Revenue Management System for Hospitality Industry

altoroslabs.com
Hospitality & leisure
Information technology

Current System Limitations

Legacy .NET Framework architecture with tightly coupled components causing maintenance difficulties, performance bottlenecks, and scalability issues. Lack of modular API integration capabilities. Risk of human error in price overrides. Inefficient deployment processes and slow system response times impacting operational effectiveness.

About the Client

Provider of integrated software solutions for hotel revenue optimization, serving 32,000 hotels across 150 countries

Strategic Modernization Goals

  • Migrate to modern technology stack with domain-driven architecture
  • Implement modular API ecosystem for internal/external integrations
  • Optimize system performance and deployment efficiency
  • Enhance revenue prediction accuracy through algorithm improvements
  • Establish automated validation and error prevention mechanisms

Core System Capabilities

  • Custom API gateway for suite integration and third-party connections
  • Dynamic pricing engine with occupancy prediction algorithms
  • Multi-threaded data processing for real-time analytics
  • Automated validation rules for price override safeguards
  • CI/CD pipelines for rapid feature deployment

Technology Stack

.NET Core
Azure DevOps
Domain-Driven Design (DDD)
RESTful API architecture
Automated testing frameworks

System Connectivity

  • Single Sign-On (SSO) with existing platform
  • Third-party hospitality management systems
  • Cloud infrastructure autoscaling capabilities

Operational Requirements

  • 4x performance improvement in data loading times
  • 10-minute deployment cycles
  • High-availability architecture
  • Scalable cloud infrastructure
  • Comprehensive unit test coverage

Expected Business Outcomes

4x faster system response times enabling real-time revenue decisions, 10-minute feature deployment accelerating time-to-market, 30% reduction in maintenance costs through modular architecture, enhanced pricing accuracy through optimized algorithms, and improved operational efficiency via automated validation checks preventing revenue leakage.

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