Success Story

The client is a B2B2C travel loyalty and technology company, that powers white-label travel and rewards programs for partners worldwide. Its distributed network of sales agents and call center managers supports member bookings, creating the need for consistent, real-time coaching at scale.

Fragmented systems and manual coaching processes were limiting operational speed, consistency, and personalization. The client faced the following challenges:

• Manually evaluating and coaching agents could not scale across a large, growing team handling high call volumes.
• Best practices from top-performing agents were hard to identify and replicate across teams.
• Member data, call transcripts, and enterprise knowledge lived in disconnected systems, slowing down agents and managers.
• Service quality varied by agent, since there was no unified, real-time view of member data to enable personalization.

Through its AI-native product engineering capabilities, Cybage developed a unified platform for real-time coaching and scalable performance analytics. The solution included:

• Built scalable ingestion pipelines for call transcripts and enterprise knowledge base, enabling graph- and vector-based contextual retrieval.
• Implemented role-aware prompt orchestration to deliver persona-specific responses and contextual insights.
• Designed and iteratively refined AI use cases using real-world question sets to align responses with operational needs.
• Enabled incremental AI adoption through a phased rollout from knowledge ingestion to production use cases.
• Implemented secure, automated Azure deployment using Terraform and Azure Key Vault.

• Scaled AI-driven coaching through six unified, context-aware capabilities across the workforce, improving productivity.
• Enabled personalized AI experiences for agents and managers, driving more relevant coaching and decision support.
• Reduced response time and improved answer consistency through real-time knowledge access.