Kafka provides essential streaming infrastructure for AI-powered applications that require immediate insights from behavioral data.

Real-time data ingestion:

• Collects and streams real-time behavioral data that feeds into AI models for immediate inference
• Supports use cases including personalized recommendations, predictive maintenance, and fraud detection
• Enables low-latency data delivery to AI/ML services and applications

Model deployment patterns:

• Use Kafka Streams to push event data through trained AI models in real-time
• Deploy models on cloud-based services like Databricks, Azure ML, or AWS SageMaker
• Support both on-premises and cloud-based AI inference architectures

Continuous learning capabilities:

• Allows continuous model updates by feeding new data back into training pipelines
• Supports online learning and adaptive AI systems that improve with new data
• Enables real-time model performance monitoring and automated retraining

This infrastructure supports sophisticated AI applications powered by Snowplow's comprehensive behavioral data collection.