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AI-Powered Call Processing for Optimized Customer Support Operations

Enhancing Efficiency and Quality Assurance

Goal

Automate call auditing to increase coverage from 5% to 100%, flagging discrepancies for human auditors to review, improving efficiency and results.

Solution

Utilized multiple AI models for speaker identification, speech-to-text, language processing along with heuristics to automate call auditing and flagging.

Result

100% call audits with reduced review time, improved productivity, boosted overall operations & enhanced analysis with fewer manual errors.

Business Introduction

The company was a leading provider of customer support services, operating a large-scale call center. They handled a high volume of incoming calls daily from customers across various industries, seeking assistance with products, services, and support inquiries. Maintaining consistent quality standards and efficient operations was crucial for delivering exceptional customer experiences and ensuring client satisfaction.

Efficient Call Transcription, Analysis, and Quality Assurance

Calls needed transcription and analysis for quality assurance and targeted training
Accurately identifying different speakers (agents and customers) in recordings was needed to prevent rule application on customer conversation.
Identifying instances of non-compliance of SOP for all customer calls

AI-Driven Call Processing and Quality Evaluation

Built a Pipeline for processing call recordings, starting with accurate transcription

Speaker identification to distinguish agents and customers

Natural Language Processing to detect slang, filler words, and other quality parameters

Heuristics + AI Pipeline for evaluating call quality based on criteria

Integrated platform for call playback, transcription, and diarization verification

Local call processing for data privacy and security

Detailed reports with KPIs for insights into call center performance

Built a Pipeline for processing call recordings, starting with accurate transcription
Speaker identification to distinguish agents and customers
Natural Language Processing to detect slang, filler words, and other quality parameters
Heuristics + AI Pipeline for evaluating call quality based on criteria
Integrated platform for call playback, transcription, and diarization verification
Local call processing for data privacy and security
Detailed reports with KPIs for insights into call center performance

Automated Transcription, Speaker Identification, Quality Scoring

Accurate call transcription
Speaker diarization for agent-customer classification
Slang and filler word detection for call professionalism
ATSI-compliant call quality scoring
Integrated verification and reporting platform

Measurable Results and Impact

Reduced call review time, improving employee productivity
Boosted overall call center productivity
Enhanced call analysis results in reduction in missing non-compliant calls
Comprehensive call quality evaluation and reporting

Key Achievements

Developed a robust call processing pipeline with AI capabilities
Integrated transcription, speaker identification, language processing
Implemented ATSI-compliant call quality scoring system
Enabled efficient call verification and performance insights
Improved operational efficiency and quality assurance

Conclusion

We developed a comprehensive call processing pipeline that streamlined and enhanced call center operations by leveraging call transcription, speaker identification, and language processing. The system’s ability to automate transcription, identify speakers accurately, detect slang and filler words, and evaluate call quality based on industry standards led to improved productivity, reduced manual errors, and enhanced quality assurance. The integrated platform for verification and reporting further facilitated efficient call center management and performance insights.

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