APIs power real-time AI systems, but scaling them at the edge comes with challenges like high-frequency data, low-latency processing, and balancing cloud vs. on-device inference. This talk explores event-driven architectures that keep things fast and efficient, using gRPC for low-latency commands, WebRTC for real-time telemetry, and MQTT for lightweight event streaming. We’ll also cover how APIs can bridge cloud and edge AI, when to run inference locally for speed and privacy, and when to offload to the cloud. Whether you’re building automation, AI-driven applications, or large-scale API ecosystems, you’ll leave with practical strategies for making event-driven APIs work at scale.