Sonata Software successfully migrated Western Union's legacy systems to AWS cloud infrastructure, saving $20M+ in annual cost savings, real-time customer communication capabilities and scalable microservices architecture that enables rapid application development without complexity concerns.
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Wired for fintech velocity - Building a fintech-grade, scalable infrastructure for Western Union through AWS migration
Pricing without borders - Modernizing Western Union’s pricing system with next-gen AWS architecture
Sonata helped Western Union with a next-generation pricing system built on AWS, enabling personalized financial services, real-time pricing optimization and a significantly improved digital footprint. The transformation allowed Western Union to reach underserved communities and deliver adaptive pricing strategies aligned with evolving customer needs.
Recruitment rebooted - Enhancing AI chatbot accuracy for recruiters with Sonata’s design-centric testing
Sonata helped an innovative startup significantly improve the robustness and accuracy of its AI-based recruitment chatbot by leveraging a design-led testing methodology. The engagement resulted in a high-performing, scalable and fraud-resistant recruitment bot that is adaptable for future use across industries like retail banking.
Wheels of change - Migration and co-existence testing for a global car rental enterprise
Sonata enabled a smooth and efficient migration testing experience for a global car rental leader by ensuring seamless coexistence of legacy and modern systems, improving data quality, accelerating test cycles and enhancing reporting capabilities.
Wings of assurance - Delivering seamless omnichannel airline experiences through accelerated regression testing
Sonata enabled a leading US airline to achieve consistent and seamless customer experiences across channels by optimizing regression testing and meeting demanding QA goals. Through advanced automation frameworks and intelligent regression strategies, Sonata helped reduce testing time and cost by targeting a 30% reduction within 6 QA cycles.