What is asynchronous inference architecture in classification systems?

Asynchronous inference decouples request submission from prediction computation to improve scalability.

In async inference systems, requests are queued and processed independently from client response cycles. This allows better throughput and load handling, especially for heavy models. Results may be delivered via callbacks, polling, or streaming. Tradeoff is increased latency but improved system resilience under high load.