An Inference Pipeline is a series of steps that processes new data and produces a prediction, decision, or result using a trained AI model. It typically receives input, prepares the information, sends it through the model, and delivers the output. Each stage works together to turn raw data into a useful result, allowing AI systems to respond consistently and efficiently.
For example, a security camera can use an inference pipeline to capture a video frame, prepare the image, identify a person, and trigger an alert when needed. This makes automated systems faster and more reliable. It is useful in image recognition, voice assistants, fraud detection, recommendation systems, and other AI applications where quick and consistent results are required.
