Real-Time AI Insights Platform for a Leading BPO

Evaluate AI-enablement of core business processes

This engagement demonstrates how BETSOL helped organizations evaluate AI integrations into their customer-facing business processes through structured cloud enablement and support. Establishing a working environment allows enterprises to assess real-time agent assistance and analytics capabilities before full-scale adoption.

The challenge

The client’s contact center operations faced several limitations:

• Manual QA sampling covered less than 5% of interactions
• Reactive assistance for agents
• Minimal actionable analytics
• Need to evaluate AI-driven improvements to customer experience.

The solution

A structured environment was established to support the evaluation of AI-enabled real-time assistance and post-call analyses within the client’s contact center landscape.

Process

• Enabled cloud environment for PoC: Supported cloud enablement and environment setup in collaboration with client.
• Configured AWS infrastructure: Assisted with VPC, multi-AZ networking, security, and logging/monitoring to host the AI platforms.
• Integrated contact center components: Supported integration of AI systems with the client’s call center and agent desktop ecosystem.
• Coordinated ADC platform setup: Assisted with Digital Companion (ADC) platform setup and lifecycle coordination.
• Resolved connectivity and access issues: Troubleshot integration across contact center, cloud, and analytics components.
• Delivered training and knowledge transfer: Coordinated enablement sessions across client, AI systems, and delivery teams.
• Supported security and compliance readiness – Addressed PCI/PII considerations, Log4J awareness, and resilience planning.

Results

The engagement produced working environments and implementation artifacts that informed the client’s evaluation of AI-assisted contact center capabilities.

The initiative delivered learning value and technical validation, although it did not progress to full production at that time due to product maturity gaps and unmet functional expectations.

Key features

• AWS environment configuration
• Multi-AZ networking and security setup
• Digital Companion (ADC) platform coordination
• Cross-system connectivity troubleshooting
• Training and knowledge transfer sessions

Technical implementation details

• AI platforms: Enterprise agent-assist and conversational analytics platform
• Cloud: AWS (VPC, multi-AZ)
• Security: PCI/PII considerations, Log4J awareness

Business impact

• Established a production-capable environment for AI-driven contact center interactions
• Enabled repeatable multi-region deployments through infrastructure automation
• Improved operational visibility with regional dashboards and monitoring
• Prepared client teams to manage NLP flows through targeted training and enablement