About the Client
A leading life insurance and financial services organization headquartered in the United States manages a broad customer base across claims, policy servicing, and support operations. As one of the most established providers in the sector, the company receives a high volume of customer communications daily—many of which are critical to maintaining service quality and regulatory adherence.
To support its commitment to responsiveness and customer satisfaction, the organization operates a large-scale customer service division. However, the growing volume of inbound emails and the complexity of categorizing them accurately began to challenge both efficiency and employee well-being.
Business Challenge
The client’s customer service team managed an overwhelming influx of over 150,000 customer emails every month, covering topics such as claims, policy inquiries, and general support.
Manual triaging was the norm—each message required human review to determine urgency, category, and routing. This process resulted in several operational challenges:
- Delayed response times, often extending resolution cycles and frustrating customers.
- Frequent routing errors, where misdirected messages required multiple handoffs before reaching the correct team.
- High agent fatigue and burnout, caused by repetitive and monotonous triaging tasks.
- Rising operational costs, as staffing had to scale with email volume.
These inefficiencies directly impacted customer satisfaction, eroded productivity, and limited the client’s ability to maintain service-level commitments in a cost-effective manner.
Approach
To address these challenges, Trianz implemented a GenAI-powered email understanding pipeline that brought intelligence and automation to the triaging process. The solution was built using AWS Bedrock and Claude 3.5 Sonnet, leveraging advanced natural language understanding (NLU) and adaptive learning.
Key aspects of the solution included:
- Automated classification and routing of incoming emails with 90% accuracy, ensuring that messages were directed to the right teams or systems without manual intervention.
- Integration with Salesforce, enabling automated creation and assignment of cases, and triggering the appropriate workflows for faster response cycles.
- A human-in-the-loop review mechanism for high-priority or ambiguous emails, ensuring accuracy and accountability in sensitive cases.
- Implementation of adaptive learning models that continuously improved triaging performance based on user feedback and system outcomes.
- Real-time monitoring and auditability features to maintain compliance with data handling and service quality standards.
This end-to-end intelligent pipeline redefined how the client processed and prioritized customer communication—balancing automation speed with human judgment where needed.
Technology Components
The solution was powered by a combination of AWS Bedrock and AWS Lambda, enabling secure, scalable, and event-driven automation.
- AWS Bedrock provided access to Claude 3.5 Sonnet, a GenAI model capable of understanding nuanced customer queries and intent, driving accurate classification and contextual routing.
- AWS Lambda handled the orchestration and real-time execution of triaging logic, ensuring elastic scalability without infrastructure overhead.
This architecture ensured continuous operation with minimal latency, allowing for 24×7 responsiveness while maintaining governance, traceability, and adaptability.
Transformational Effects
The AI-driven transformation delivered significant and quantifiable improvements across both operations and customer experience:
- 75% reduction in manual triaging, freeing service agents to focus on higher-value interactions.
- 40% faster average response times, leading to stronger customer engagement and improved SLAs.
- 30% increase in customer satisfaction, as measured through post-interaction surveys and NPS metrics.
- 24×7 operational coverage, eliminating dependency on staffing hours and improving responsiveness during peak volumes.
- Reduced agent fatigue, resulting in better morale and lower attrition rates.
- Higher process efficiency, with adaptive AI models continuously refining routing accuracy and prioritization.
By automating email understanding and routing through GenAI, the client successfully transitioned from a reactive, resource-intensive support model to an intelligent, always-on service ecosystem that drives speed, consistency, and customer delight.
