OUR PROJECTS
NLP Call Analytics & Quality Scoring Service

AI-powered call analytics platform designed to analyze customer conversations, identify sentiment, and generate actionable business insights through natural language processing.

Duration
1 Year
Year
2024
Region
USA
Natural language processing platform using AI to understand text, automate communication and extract business insights

NLP Call Analytics is an intelligent speech and conversation analytics solution developed to help organizations gain valuable insights from customer interactions. The platform leverages natural language processing, machine learning, and sentiment analysis to evaluate call quality, identify customer concerns, and improve service performance.

By automatically processing large volumes of call recordings, the solution helps businesses monitor customer experience, optimize agent performance, and make data-driven decisions.

Key Highlights

  • Real-Time Call Analysis
  • Sentiment Analysis
  • Conversation Intelligence
  • Speech-to-Text Processing
  • Customer Experience Monitoring
  • Agent Performance Evaluation
  • Scalable NLP Framework
  • Automated Insights Generation

Benefits

  • Improved customer satisfaction
  • Enhanced service quality monitoring
  • Reduced manual call reviews
  • Faster identification of customer issues
  • Better agent performance management
  • Data-driven business decisions

Use Cases

  • Customer Support Analytics
  • Contact Center Optimization
  • Customer Sentiment Monitoring
  • Quality Assurance Automation
  • Sales Call Evaluation
  • Customer Experience Analysis

Problems

Contact-center teams needed automated and consistent call quality scoring at scale.

Opportunities

Operationalize NLP-driven call evaluation as a consumable API service.

Solutions

Implemented Django REST endpoints for evaluate/retrieve flows with schema checks and standardized response handling.

Future Trends

Real-time coaching signals, rubric personalization, and multilingual call-quality intelligence.

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