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This cluster consolidates concepts, platforms, and practices around AI models and their operational environments.
Defines scope for integration of AI platforms and models: interfaces, data flows, deployment pipelines, versioning, authentication, monitoring and connectors to external systems. Excludes model training, algorithm development, content-level data preparation and end-user interfaces. Includes API specifications, data schemas and runtime orchestration; focuses on technical integration points and boundaries.
Concept for connecting applications and services via defined interfaces to automate and coordinate data and process flows.
Coordination and control of the lifecycle and production deployment of machine learning models across platforms.