In this session, you’ll learn how to operationalize machine learning end‑to‑end. We’ll share lessons from developing MLOps tools and processes for corporate clients in the FMCG, ecommerce and utilities sectors, explore the key business drivers behind MLOps investments, and introduce our “MLOps Pillars” framework for structuring each engagement. Along the way, we’ll blend Data Science and ML Engineering perspectives on building self‑service pipelines, enforcing environment separation, integrating GitHub Actions for CI/CD, and leveraging observability and autoticketing tooling.