Building Intelligent Retention Engines - Real-Time Churn Detection

Explore how to build intelligent customer retention systems using real-time churn detection in this 20-minute conference talk from Conf42 KN 2025. Learn about the critical importance of customer retention and discover the limitations of traditional retention models compared to AI-powered approaches. Examine a comprehensive Kubernetes-native AI architecture designed for scalable churn prediction, including the machine learning techniques most effective for detecting customer churn patterns. Dive into the core technologies and orchestration strategies needed to implement these systems, covering production infrastructure requirements for deploying ML models at scale. Understand the essential considerations around model fairness, transparency, ethics, and privacy management when building customer-facing AI systems. Gain practical insights into moving from traditional reactive retention strategies to proactive, AI-driven approaches that can identify at-risk customers in real-time and enable targeted intervention strategies.