Remove IDP Remove Information Remove Metadata
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Unleashing the multimodal power of Amazon Bedrock Data Automation to transform unstructured data into actionable insights

AWS Machine Learning Blog

In a world whereaccording to Gartner over 80% of enterprise data is unstructured, enterprises need a better way to extract meaningful information to fuel innovation. IDP is powering critical workflows across industries and enabling businesses to scale with speed and accuracy. billion in 2025 to USD 66.68

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Build a generative AI enabled virtual IT troubleshooting assistant using Amazon Q Business

AWS Machine Learning Blog

Todays organizations face a critical challenge with the fragmentation of vital information across multiple environments. This solution helps streamline information retrieval, enhance collaboration, and significantly boost overall operational efficiency, offering a glimpse into the future of intelligent enterprise information management.

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Discover insights from Gmail using the Gmail connector for Amazon Q Business

AWS Machine Learning Blog

Google Drive supports storing documents such as Emails contain a wealth of information found in different places, such as within the subject of an email, the message content, or even attachments. It can be tailored to specific business needs by connecting to company data, information, and systems through over 40 built-in connectors.

IDP 117
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Secure a generative AI assistant with OWASP Top 10 mitigation

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This is typically done through some sort of an identity provider (IdP) capability like Okta, AWS IAM Identity Center , or Amazon Cognito. This comprehensive security setup addresses LLM10:2025 Unbound Consumption and LLM02:2025 Sensitive Information Disclosure, making sure that applications remain both resilient and secure.

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Build private and secure enterprise generative AI applications with Amazon Q Business using IAM Federation

AWS Machine Learning Blog

Amazon Q Business is a conversational assistant powered by generative artificial intelligence (AI) that enhances workforce productivity by answering questions and completing tasks based on information in your enterprise systems, which each user is authorized to access.

IDP 127
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Cost-effective document classification using the Amazon Titan Multimodal Embeddings Model

AWS Machine Learning Blog

Manually processing these documents to classify and extract information remains expensive, error prone, and difficult to scale. Categorizing documents is an important first step in IDP systems. For more information, see Amazon Comprehend document classifier adds layout support for higher accuracy.

IDP 128
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Build a receipt and invoice processing pipeline with Amazon Textract

AWS Machine Learning Blog

The most important pieces of information such as price, vendor name, vendor address, and payment terms are often not explicitly labeled and have to be interpreted based on context. You can visualize the indexed metadata using OpenSearch Dashboards. Additional output information is also available on the AWS CloudFormation console.

IDP 117