Customer Service Call Dataset [Multisector] | 25,000 Hours of Customer Support Audio with Transcripts for AI Training | Machine Learning (ML) Data

This dataset contains transcribed customer support calls from companies in over 160 industries, offering a high-quality foundation for developing customer-aware AI systems and improving service operations. It captures how real people express concerns, frustrations, and requests — and how support teams respond. Included in each record: - Full call transcription with labeled speakers (system, agent, customer) - Concise summary of the conversation - Sentiment tag for the overall interaction: positive, neutral, or negative - Company name, duration, and geographic location of the caller - Call context includes industries such as eCommerce, banking, telecom, and streaming services Common use cases: - Train NLP models to understand customer service calls and detect churn risk - Power complaint detection engines for customer success and support teams - Create high-quality LLM training sets with real support narratives - Build summarization and topic tagging pipelines for CX dashboards - Analyze tone shifts and resolution language in customer-agent interaction This dataset is structured, high-signal, and ready for use in AI pipelines, CX design, and quality assurance systems. It brings full transparency to what actually happens during customer service moments — from routine fixes to emotional escalations." The more you purchase, the lower the price will be.