Asynchronous Inference Job Scheduling And Result Streaming

via “request batching and async inference for high-throughput workloads”

AI application platform — run models as APIs with auto GPU management and observability.

Unique: Implements dynamic batching that groups requests arriving within a time window (e.g., 100ms) into a single batch, maximizing throughput without requiring explicit batch submission. Uses priority queues to prevent starvation of high-priority requests.

vs others: More efficient than sequential inference (higher GPU utilization) and simpler than self-managed batch processing systems (no queue infrastructure needed)