What is real-time inference pipeline architecture in classification systems?

A real-time inference pipeline processes incoming requests instantly through feature retrieval, model inference, and response generation.

Real-time classification pipelines are optimized for low latency and high throughput. They typically include API gateway, authentication layer, feature store lookup, inference engine, and post-processing logic. Systems often use in-memory caches, async processing, and GPU acceleration. Bottlenecks usually occur in feature retrieval or network hops, so architectures minimize cross-service calls.