AI Data Labeling & Quality Evaluation – Voice and Conversational Data
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I’ve worked extensively with real customer conversation data—voice, chat, and email—used to train and evaluate AI systems in customer-facing operations. My work involved reviewing and labeling interactions to identify intent, sentiment, resolution quality, compliance gaps, and escalation signals.
This was not theoretical data. These were high-volume, high-stakes conversations where accuracy directly affected customer trust and business outcomes. I worked closely with product and data teams to ensure the labels reflected real operational reality and could be reliably used in production systems.
I’ve worked extensively with real customer conversation data—voice, chat, and email—used to train and evaluate AI systems in customer-facing operations. My work involved reviewing and labeling interactions to identify intent, sentiment, resolution quality, compliance gaps, and escalation signals. This was not theoretical data. These were high-volume, high-stakes conversations where accuracy directly affected customer trust and business outcomes. I worked closely with product and data teams to ensure the labels reflected real operational reality and could be reliably used in production systems.
2023 - 2024