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Build end-to-end document processing pipelines with Amazon Textract IDP CDK Constructs

AWS Machine Learning

Orchestration pipelines need to be created to introduce business logic, and also account for different processing techniques depending on the type of form inputted. Run the processing pipelines for each form type or page of form with the appropriate Amazon Textract API (Signature Detection, Table Extraction, Forms Extraction, or Queries).

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Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

AWS Machine Learning

SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts. With this launch, account owners can grant access to select feature groups by other accounts using AWS Resource Access Manager (AWS RAM).

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Build a receipt and invoice processing pipeline with Amazon Textract

AWS Machine Learning

One area that holds significant potential for improvement is accounts payable. On a high level, the accounts payable process includes receiving and scanning invoices, extraction of the relevant data from scanned invoices, validation, approval, and archival. It is available both as a synchronous or asynchronous API.

APIs 97
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Knowledge Bases for Amazon Bedrock now supports hybrid search

AWS Machine Learning

Use hybrid search and semantic search options via SDK When you call the Retrieve API, Knowledge Bases for Amazon Bedrock selects the right search strategy for you to give you most relevant results. You have the option to override it to use either hybrid or semantic search in the API.

APIs 116
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Customize Amazon Textract with business-specific documents using Custom Queries

AWS Machine Learning

You can use the adapter for inference by passing the adapter identifier as an additional parameter to the Analyze Document Queries API request. Adapters can be created via the console or programmatically via the API. What is the account#? What is the account name/payer/drawer name? MICR line format). Who is the payee?

APIs 108
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Build a foundation model (FM) powered customer service bot with agents for Amazon Bedrock

AWS Machine Learning

The action is an API that the model can invoke from an allowed set of APIs. Action groups are mapped to an AWS Lambda function and related API schema to perform API calls. Customers converse with the bot in natural language with multiple steps invoking external APIs to accomplish subtasks.

APIs 93
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Build a secure enterprise application with Generative AI and RAG using Amazon SageMaker JumpStart

AWS Machine Learning

These SageMaker endpoints are consumed in the Amplify React application through Amazon API Gateway and AWS Lambda functions. To protect the application and APIs from inadvertent access, Amazon Cognito is integrated into Amplify React, API Gateway, and Lambda functions. You may need to request a quota increase.