At Gong, we have over a dozen different live machine learning models in multiple domains (NLP, audio/speech, video and classical ML), used in practice across hundreds of enterprise customers. We will review how those models are built, evaluated, deployed and used in real-life scenarios. We will outline different types of models (domain-agnostic vs. domain specific, supervised vs. unsupervised, deep learning vs. classical ML), and cover how data is obtained, how the models are evaluated (pre and post production), and how they’re used for new predictions. We will show case studies of data flows and pipelines, and discuss where humans (general labelers + domain experts) come into the loop.