Case Study

Modernizing Customer Care Operations with a Cloud-Native Data Platform on AWS

Industry

Travel & Transportation (Railways)

Location

Europe

Our Contributions

Customer Care Data Modernization, Cloud-Native Data Engineering, Real-Time & Batch Integration, Data Quality & Governance, Analytics Enablement, Change & Adoption Support

Railway operators manage high volumes of customer interactions across journeys, complaints, service disruptions, and loyalty programs. Delivering consistent, compliant, and personalized customer care requires seamless integration of CRM systems, digital channels, and operational data, supported by real-time insights and scalable infrastructure.

As legacy systems reach the end of life, transportation organizations are modernizing customer care platforms using cloud-native architectures that enable 360-degree customer visibility, real-time workflows, and regulatory alignment, while minimizing disruption to ongoing operations.

The Challenge

The railways group was replacing its legacy EL-OK CRM system, which had supported core customer care functions but could no longer meet scalability, integration, and compliance demands. Multiple internal systems needed consolidation to provide a unified customer view across interactions, knowledge bases, communications, and rewards.

Standard complaint management processes were misaligned with regulatory obligations and operational realities, introducing compliance risks. Rigid workflows limited the ability to handle complex, high-impact customer scenarios, while the transition to the new EL-OK environment required seamless integration and strong adoption support to avoid operational disruption.

Our Approach

Coforge implemented a modern, cloud-native Customer Care data solution on AWS, enabling integrated, real-time, analytics-driven customer care operations.

Cloud-Native Customer Care Foundation

Designed and provisioned scalable AWS infrastructure to support high-volume digital and CRM workloads, with secure, low-latency connectivity enabled through AWS Direct Connect.

Real-Time & Batch Data Integration

Implemented real-time and batch pipelines using AWS Glue, Kafka, Lambda, and Python, supported by the DataFlux artifact, to enable structured data ingestion and transformation across internal systems.

Unified Customer Views & Analytics

Integrated multiple internal systems to create 360-degree customer visibility, and delivered Power BI dashboards providing insights into customer satisfaction, KPIs, and service performance.

Data Quality, Governance & Workflow Enablement

Applied data quality rules using the Agentic DQ Resolver, along with exception handling, monitoring, and analytics integration with Appian workflows to ensure compliance and control.

Adoption & Continuous Optimization

Supported rollout through documentation, knowledge transfer, continuous monitoring, and feedback-driven optimization to accelerate adoption and minimize disruption.

Impact to Date

The AWS-based modernization delivered measurable improvements in integration speed, customer visibility, compliance, and service effectiveness.

360° Customer View

Unified Customer Intelligence

~40% Faster

Data Integration