Case Study

Empowering Contact Center Agents with Real‑Time Conversational AI Assistance

Industry

Banking & Financial Services

Location

Global

Our Contributions

Conversational AI, Speech-to-Text, NLP & Sentiment Analysis, Real-Time Analytics, Scalable AI Architecture, Call Center Integration

Global banks manage millions of customer interactions through contact centers, where agents are required to process complex conversations, access relevant information instantly, and resolve issues efficiently. However, long-duration customer calls and unstructured audio streams make it difficult to derive actionable insights in real time, limiting an agent’s ability to respond proactively.

To enhance agent effectiveness and customer experience, banks are increasingly adopting conversational AI and real-time analytics to transform live call data into actionable guidance, enabling faster responses, smarter recommendations, and improved service outcomes.

The Challenge

The bank captured long customer service sessions, often lasting up to eight hours, as continuous audio streams. However, this data remained largely unusable in its raw form, making it difficult to process, summarize, and analyze conversations while the calls were still in progress.

Without real-time insights, agents lacked contextual guidance during live interactions, limiting their ability to respond effectively to customer needs. The challenge was compounded by the need to process high call volumes reliably while ensuring seamless integration with existing call center systems.

Our Approach

Coforge designed a real-time conversational AI solution that combines streaming analytics, speech processing, and NLP, enabling agents to receive actionable insights during live customer interactions.

Streaming & Real-Time Processing

Built a robust streaming architecture capable of splitting long audio call streams into manageable segments for continuous, real-time analysis.

Speech-to-Text & Conversation Understanding

Implemented speech-to-text transcription services to convert call audio into text, enabling downstream analysis, searchability, and summarization.

NLP-Driven Insights & Sentiment Analysis

Applied natural language processing algorithms to extract key insights, contextual information, and sentiment from live call transcriptions.

Call Center Integration & Scalability

Integrated conversational insights directly into the bank’s existing call center software, providing agents with real-time suggestions. Designed the architecture to scale for high call volumes while ensuring reliability through redundancy and failover mechanisms.

Impact to Date

The conversational AI solution delivered measurable improvements in agent productivity, operational efficiency, and customer experience by enabling real-time intelligence across contact center interactions.

↑ Up to 20% Faster

Product Go-Live

↓ Up to 10%

Lower Cost per Project

↑ 10–15%

Improvement in Customer Satisfaction

↑ 15–30%

Time Savings for Agents