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Amazon Augmented AI (Amazon A2I) adds the benefit of human judgment to any machine learning * application. When an AI application can't evaluate data with a high degree of confidence, * human reviewers can take over. This human review is called a human review workflow. To create * and start a human review workflow, you need three resources: a worker task * template, a flow definition, and a human * loop.

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For information about these resources and prerequisites for using Amazon A2I, see Get Started with * Amazon Augmented AI in the Amazon SageMaker Developer Guide.

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This API reference includes information about API actions and data types that you can use * to interact with Amazon A2I programmatically. Use this guide to:

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Amazon A2I integrates APIs from various AWS services to create and start human review * workflows for those services. To learn how Amazon A2I uses these APIs, see Use APIs in * Amazon A2I in the Amazon SageMaker Developer Guide.

* * @packageDocumentation */ export * from "./SageMakerA2IRuntimeClient"; export * from "./SageMakerA2IRuntime"; export type { ClientInputEndpointParameters } from "./endpoint/EndpointParameters"; export type { RuntimeExtension } from "./runtimeExtensions"; export type { SageMakerA2IRuntimeExtensionConfiguration } from "./extensionConfiguration"; export * from "./commands"; export { Command as $Command } from "@smithy/core/client"; export * from "./pagination"; export * from "./schemas/schemas_0"; export * from "./models/enums"; export * from "./models/errors"; export * from "./models/models_0"; export { SageMakerA2IRuntimeServiceException } from "./models/SageMakerA2IRuntimeServiceException";