Building an AI-Powered Contact Center for Smarter Customer Experiences

U Mobile is modernizing its customer-service operations through the AICC North Star program, moving from its existing Genesys environment to Amazon Connect. The initiative is designed to consolidate customer interaction channels onto a unified cloud platform while introducing AI-driven self-service, real-time agent assistance, advanced analytics, workforce management, and automated quality evaluation. UMobile Use Case(2)

DataSleek designed an AI-enabled contact-center architecture centered on Amazon Connect Customer AI Agent, with Retrieval-Augmented Generation (RAG), controlled backend tool execution, multilingual conversational capabilities, AI-assisted agent functionality, operational monitoring, and human-agent escalation. Solution Architecture- UMobile

The result is a production architecture designed to provide customers with more conversational self-service while giving agents the context, knowledge, and AI assistance required to handle interactions effectively.

The Challenge: Moving Beyond a Traditional Contact Center

U Mobile’s Genesys-based contact center serves approximately 3 million interactions per month across voice, email, and limited digital channels. The existing environment presented several challenges, including ageing infrastructure with limited AI/ML capabilities, siloed channel management, limited self-service, manual quality assurance, an inflexible IVR, and limited real-time visibility into operational performance. UMobile Use Case(2)

At the same time, customers increasingly expect seamless interactions across channels, shorter wait times, personalized service, and the ability to resolve common requests without always requiring an agent.

U Mobile therefore required a contact-center architecture capable of bringing channels together while introducing conversational automation, intelligent knowledge retrieval, secure integration with enterprise systems, improved operational visibility, and reliable escalation to human agents when automation could not complete an interaction.

The Solution: Amazon Connect + Agentic AI-Powered Customer Engagement

DataSleek designed U Mobile’s production architecture around Amazon Connect and AWS-managed AI services. Amazon Connect manages customer interactions and contact-flow orchestration, while the Customer AI Agent provides conversational reasoning, knowledge retrieval, backend tool invocation, customer-context handling, and controlled live-agent escalation. Solution Architecture- UMobile

The solution incorporates Amazon Connect, Amazon Lex V2, Amazon Bedrock capabilities, knowledge bases, AWS Lambda, Amazon S3, Amazon OpenSearch Serverless, Amazon CloudWatch, AWS KMS, and AWS Secrets Manager, together with controlled integrations to U Mobile’s enterprise systems. Statement of Work- U Mobile

1. Unified Omnichannel Contact Center

Amazon Connect provides the foundation for consolidating customer engagement across voice, chat, email, SMS, WhatsApp, and social media, with interactions managed through a unified agent environment. UMobile Use Case(2)

This approach replaces fragmented channel handling with a common contact-center platform and provides a foundation for consistent routing, customer context, analytics, workforce management, and AI capabilities.

The program also includes IVR migration, digital channels, outbound capabilities, workforce management, reporting, and AI assistance as part of the broader Amazon Connect transformation. UMobile Use Case(2)

2. Agentic AI and Conversational Self-Service

A major component of the architecture is Amazon Connect Customer AI Agent, which provides agentic self-service capabilities rather than relying solely on traditional menu-driven interactions.

The AI layer supports conversational reasoning, knowledge-grounded responses, controlled backend tool execution, customer-context handling, and escalation to live agents. Amazon Lex V2 supports the conversational interaction layer, while contact attributes preserve important context across the customer journey. Solution Architecture- UMobile Solution Architecture- UMobile

This enables U Mobile to automate appropriate customer-service journeys while retaining a clear path to human assistance when a request cannot or should not be completed automatically.

3. Retrieval-Augmented Generation and Enterprise Knowledge

The solution uses Retrieval-Augmented Generation (RAG) to ground AI responses in U Mobile’s approved enterprise knowledge.

Knowledge sources are incorporated into the AI architecture using AWS-managed services, including knowledge bases, Amazon S3 and Amazon OpenSearch Serverless. The architecture also supports Amazon Bedrock capabilities as part of the knowledge-grounding and AI layer. Solution Architecture- UMobile

This approach allows the AI experience to retrieve relevant organizational knowledge rather than depending only on general model knowledge, helping provide responses grounded in U Mobile-controlled information.

4. Secure Backend Tool Execution

Conversational orchestration is separated from backend execution. AWS Lambda implements API and tool logic so that the AI Agent can invoke controlled business functions without directly embedding enterprise integration logic within the conversational layer.

Backend execution includes timeout and failure-handling controls, helping ensure unsuccessful integrations do not leave customer interactions in an undefined state. Solution Architecture- UMobile

The architecture includes integration with OTP, ZSmart, campaign-management capabilities, and other U Mobile enterprise systems, enabling the conversational experience to work with operational customer-service processes rather than functioning only as an informational chatbot. Solution Architecture- UMobile

5. AI-Assisted Agent Experience

Automation is complemented by AI capabilities for human agents. The target environment includes real-time agent assistance and knowledge retrieval, enabling agents to access relevant information while serving customers.

The broader program is designed to improve agent productivity through capabilities including a unified desktop, AI assistance, auto-summarization, knowledge retrieval, and AI-enabled coaching as the transformation progresses. UMobile Use Case(2)

When an automated interaction requires human assistance, the architecture supports controlled escalation to a live agent while preserving relevant interaction context, reducing the need for the customer to restart the journey.

6. Conversational Analytics and Quality Management

U Mobile’s existing quality-assurance process covered only a small sample of customer interactions, creating a need for broader and more scalable quality monitoring. UMobile Use Case(2)

The Amazon Connect program introduces Contact Lens analytics and quality evaluation, together with real-time dashboards and automated operational monitoring. The target-state program includes automated quality evaluation for AI-eligible voice interactions, with human review retained where appropriate. UMobile Use Case(2)

This creates a stronger foundation for identifying interaction trends, monitoring service quality, evaluating customer conversations, and supporting continuous improvement.

7. Security, Monitoring and Operational Control

Security and operational governance are built into the production architecture.

AWS KMS and AWS Secrets Manager support encryption and secure management of sensitive configuration and credentials, while Amazon CloudWatch provides monitoring and operational visibility. The architecture also incorporates access control, auditability, production support, resilience, and failure-handling considerations. Solution Architecture- UMobile

The production architecture is designed around AWS-managed and serverless services, reducing dependence on manually managed infrastructure while allowing individual integration and AI components to be governed independently. Solution Architecture- UMobile

The Impact: A Foundation for Measurable Customer-Service Improvement

The U Mobile architecture establishes a modern operating model for customer engagement by combining omnichannel contact handling, conversational AI, enterprise knowledge, backend automation, agent assistance, analytics, and quality management on AWS.

The program is designed to improve several important contact-center KPIs, including:

• Self-service containment, through AI-powered chatbot and voice automation
• Average Handle Time (AHT), through real-time agent assistance
• First Contact Resolution (FCR), through intelligent routing and knowledge retrieval
• Customer satisfaction, through more seamless omnichannel interactions and reduced waiting
• Agent productivity, through a unified workspace, AI assistance, and automation
• Quality coverage, through automated interaction evaluation
• Operational visibility, through real-time dashboards, workforce forecasting, monitoring, and analytics UMobile Use Case(2)

These are documented program objectives rather than validated percentage improvements, so unsupported before-and-after performance figures should not be presented as achieved results.

Built for Continued AI Innovation

U Mobile’s contact-center modernization provides more than a platform migration. It establishes an architecture in which Amazon Connect, Agentic AI, enterprise knowledge, serverless integrations, analytics, and human agents operate as part of a connected customer-service environment.

The architecture separates conversational orchestration, enterprise knowledge, and backend tool execution, allowing individual capabilities to evolve without tightly coupling the complete customer journey to a single component. Solution Architecture- UMobile

With a production architecture supporting customer-facing AI self-service, RAG, enterprise integrations, live-agent escalation, AI-assisted agent capabilities, security, monitoring, and operational resilience, U Mobile has a foundation for continuing to expand intelligent customer engagement as its requirements evolve.