A Fujitsu North America AI architect presents a four-stage pipeline for extracting structured business intelligence from contact center audio streams in real time. The pipeline covers voice capture with stereo channel separation and PII masking, speech-to-text transcription requiring 90%+ accuracy with domain-specific dictionaries, a generative AI core using few-shot prompting and hallucination checks to produce structured JSON summaries, and a CRM sync layer with human verification. Deployed results show after-call work time cut from 6.3 to 3.1 minutes (~50% reduction) across 500-seat contact centers. Current challenges include STT accuracy for heavy accents, LLM token costs on long transcripts, and PII compliance overhead. The roadmap includes explainable AI for operator coaching, predictive staffing from intent data, and real-time abuse detection to protect agent mental health.
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