Case Study

Transforming Digital Customer Engagement Using Generative AI on AWS

Background

A leading digital customer service platform leveraged Amazon Bedrock to enhance chat and voice support with multilingual, context-aware conversational AI, reducing operational costs while improving customer satisfaction. 

The Challenge

The customer sought to enhance its digital customer service platform to deliver faster, more accurate, and cost-efficient support.

  • Improve response accuracy across high-volume customer interactions.

  • Scale multilingual support to serve a global user base effectively.

  • Deliver more human-like conversational experiences without escalating costs or adding human agents.

Our Solution

Rambunct implemented a secure, AWS-powered generative AI solution to enable multilingual, context-aware conversational assistants across chat and voice channels.

  • Deployed Amazon Bedrock foundation models (Anthropic Claude, Amazon Titan) for multi-turn understanding and response generation.

  • Integrated AWS Lambda to fetch real-time customer interaction context.

  • Used Amazon CloudWatch for monitoring, logging, and operational optimization.

  • Secured the environment with Amazon VPC, AWS IAM, and AWS KMS encryption to meet compliance requirements.

The Result

The solution delivered measurable improvements in customer experience, efficiency, and cost optimization.
  • 18% increase in Customer Satisfaction (CSAT) scores.

  • 45% reduction in human agent handoffs, driving higher self-service containment.

  • 60% faster response times for common support queries.

  • 35% overall savings in operational costs compared to the previous AI infrastructure.