...Itβs implemented in C++ for scalability and efficiency, making it suitable for both edge and cloud deployments where inference workloads must be reliable and high throughput. The server exposes model inference via standard network protocols like REST and gRPC, allowing any client that speaks those protocols to request predictions remotely, abstracting away the complexity of where and how the model runs. It supports model deployment in diverse environments including Docker, bare-metal machines, and Kubernetes clusters, and is especially useful in microservices architectures where AI services need to scale independently. ...