Model Serving
The process of making an AI model available for inference by deploying it behind an interface that accepts requests and returns predictions or generated outputs.
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Related terms
A software service that hosts one or more AI models and processes inference requests by receiving inputs, executing model predictions, and returning outputs through APIs while managing resources, batching, scaling, and hardware acceleration.
Model RegistryA centralized system for storing, versioning, organizing, and managing AI models and their deployment metadata.
Inference APIAn API that enables applications to send input data to a deployed AI model and receive generated predictions or outputs, providing programmatic access to inference capabilities without managing the underlying model infrastructure.
Deployment PipelineAn automated workflow that builds, tests, validates, and deploys applications or AI systems across development, staging, and production environments.