To integrate real-time data into ML models for inference:

1. Use Snowplow to capture live user or system events.
2. Stream this enriched data into real-time processing systems such as Apache Kafka, Flink, or AWS Lambda.
3. Apply real-time transformations or lightweight feature engineering on the fly.
4. Route the processed data to deployed models for inference, enabling immediate predictions.

This setup allows ML models to act on the most recent data, supporting use cases like fraud detection, personalization, or recommendation systems.