Snowflake helps scale AI pipelines fed by Snowplow event data by providing:

• Elastic Compute: Snowflake's automatic scaling capabilities handle variable loads from Snowplow event streams, ensuring consistent performance for AI model training and inference
• Data Sharing: Snowflake's secure data sharing enables collaboration between data science teams while maintaining data governance over Snowplow behavioral data
• ML Integration: Native integration with ML platforms like Databricks, SageMaker, and Snowpark ML enables seamless model development using Snowplow's rich behavioral datasets
• Real-time Features: Snowflake's streaming capabilities support real-time feature engineering from Snowplow events for online ML inference and personalization

This architecture supports both batch ML training and real-time inference at enterprise scale.