Garrett Frere

Itron is redefining grid management by delivering structure-level Powerflow analysis for the world’s largest energy utilities. Electrification is fundamentally reshaping demand. Learn how Itron is using Snowflake ML to generate granular, high-frequency insight across both load and generation to maintain reliability, manage congestion and control emissions.

At PayPal, third-party providers could predict interchange and scheme fees but granular transaction-level fees were arriving only at the end of the month. This would take one month for most cases and three days in best-case scenarios with an error-prone process. In this session, PayPal engineers explain how PayPal built a modern near real-time AI/ML pipeline in Snowflake to accurately predict merchant fees daily at the transaction level. Learn how this accelerates settlement times, saves costs and enables faster and more expansive merchant acquisition.

Snowflake ML enables efficient development and deployment of advanced models without any data movement. With multi-GPU support, MLOps integration and Git-based workflows, Container Runtime provides a scalable environment for training, and Snowflake ML’s products such as Model Registry and Model Serving make it easy to deploy these models in production. This session explores best practices for scalable ML workflows and the creation of production-ready ML pipelines in Snowflake.