What is event-driven architecture in classification systems?

Event-driven architecture processes classification tasks asynchronously using events and message streams.

Instead of synchronous API calls, classification systems consume events from streaming platforms like Kafka or Kinesis. Each event triggers feature updates, inference, or retraining pipelines. This architecture improves scalability and resilience but introduces eventual consistency. It is widely used in real-time fraud detection and recommendation systems.