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Build well-architected IDP solutions with a custom lens – Part 6: Sustainability

AWS Machine Learning Blog

An intelligent document processing (IDP) project typically combines optical character recognition (OCR) and natural language processing (NLP) to automatically read and understand documents. Building a production-ready IDP solution in the cloud requires a series of trade-offs between cost, availability, processing speed, and sustainability.

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Build well-architected IDP solutions with a custom lens – Part 1: Operational excellence

AWS Machine Learning Blog

The IDP Well-Architected Lens is intended for all AWS customers who use AWS to run intelligent document processing (IDP) solutions and are searching for guidance on how to build secure, efficient, and reliable IDP solutions on AWS. This post focuses on the Operational Excellence pillar of the IDP solution.

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Build well-architected IDP solutions with a custom lens – Part 4: Performance efficiency

AWS Machine Learning Blog

When a customer has a production-ready intelligent document processing (IDP) workload, we often receive requests for a Well-Architected review. The IDP Well-Architected Custom Lens in the Well-Architected Tool contains questions regarding each of the pillars. This post focuses on the Performance Efficiency pillar of the IDP workload.

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Derive meaningful and actionable operational insights from AWS Using Amazon Q Business

AWS Machine Learning Blog

Amazon Q Business is a fully managed, secure, generative-AI powered enterprise chat assistant that enables natural language interactions with your organization’s data. compliant identity provider (IdP) configured in the same AWS Region as your Amazon Q Business application. The collected data can be analyzed using Amazon Q Business.

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How the UNDP Independent Evaluation Office is using AWS AI/ML services to enhance the use of evaluation to support progress toward the Sustainable Development Goals

AWS Machine Learning Blog

Data ingestion and extraction Evaluation reports are prepared and submitted by UNDP program units across the globe—there is no standard report layout template or format. The data ingestion and extraction component ingests and extracts content from these unstructured documents.

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Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

AWS Machine Learning Blog

Automate intelligent document processing (IDP) – Agent Creator can extract valuable data from invoices, purchase orders, resumes, insurance claims, loan applications, and other unstructured sources automatically. The architecture employs an event-driven model, where the completion of one snap triggers the next step in the workflow.