Coforge partnered with a leading North American LTL and freight logistics provider to transform its pricing operations and modernize its enterprise Pega ecosystem. The initiative focused on building a predictive AI-powered pricing and rating engine while simultaneously upgrading and stabilizing a complex landscape of enterprise applications.
The engagement replaced an incumbent partner and introduced a factory-driven modernization model, enabling faster upgrades, improved platform performance, and a clear roadmap toward cloud-native deployment.
Transformation Timeline
Platform assessment and upgrade strategy definition
AI-powered pricing engine development and deployment
Pega upgrade factory implementation and execution
Optimization, stabilization, and cloud-readiness enablement
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The Challenge
The client faced significant operational and technical challenges across both pricing operations and platform modernization.
Key challenges included:
- Lengthy and inefficient upgrade cycles taking 6–12 months with limited business value
- High risk of operational disruption across critical systems, including driver mobility and dispatch
- Complex multi-environment landscape leading to duplication, inefficiency, and extended timelines
- Parallel development during upgrades causing rework and instability
- Large data volumes impacting upgrade performance and recovery
- Mobile compatibility issues across different platform versions
Our Approach
AI-Powered Dynamic Pricing and Rating Engine
Developed a predictive pricing engine to automate freight rating and significantly reduce cycle time for pricing agreements, improving efficiency and accuracy.
Pega Upgrade Factory Model Implementation
Introduced a factory-driven upgrade model to standardize and accelerate upgrades across 15 enterprise-grade Pega applications.
Optimized Upgrade Strategy and Execution
Adopted a near-production clone upgrade approach, reducing dependency on multiple environments and accelerating production rollout timelines.
Architecture and Data Optimization
Implemented split-schema architecture, archival, and data purging strategies to enhance performance, resilience, and minimize downtime.
Automation and Governance Enablement
Leveraged rule-based comparison utilities, test optimization strategies, and continuous reporting to ensure consistency, transparency, and quality across upgrades.
Cloud-Ready Architecture Definition
Established a future-ready architecture aligned with containerized deployments on AWS and Azure, enabling seamless transition to a cloud-native ecosystem.
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Impact to Date
30%+
Improvement in auto-rating accuracy
Significant reduction
In pricing cycle time from weeks to hours or days
70-85%
Zero or near-zero
20+
Stabilized platform
Business Impact
- Accelerated pricing operations with improved accuracy and responsiveness
- Reduced operational risk through standardized and efficient upgrade processes
- Decreased infrastructure and maintenance costs through environmental rationalization
- Improved system stability and performance across enterprise applications
- Enabled continuous modernization with a scalable, factory-driven model
- Established a clear roadmap for cloud-native transformation
By combining AI-driven pricing innovation with a factory-based modernization approach, Coforge enabled the organization to accelerate operations, reduce risk, and simplify its complex technology landscape. The result is a high-performance, future-ready platform that delivers faster business outcomes today while positioning the enterprise for scalable, cloud-native growth.
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