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Amazon Cognito

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Headlines · 2

  1. Build self-improving document processing with Amazon Bedrock AgentCore

    AWS published a technical guide for building an agentic intelligent document processing (IDP) system on Amazon Bedrock AgentCore, in which eight specialized agents collaborate across two graph workflows built with the open-source Strands Agents SDK. A new document type goes through a training workflow — an Analyzer extracts text with Amazon Textract, a Matcher searches Amazon S3 Vectors, an Instructions agent generates extraction prompts, an Extractor produces structured JSON and a Validator checks it against schemas and business rules in Amazon Aurora DSQL — while documents matching a known layout skip prompt generation in an automation workflow. In the sample purchase-order scenario, the first run took 3 minutes 49 seconds and a repeat document took 1 minute 30 seconds, and AWS estimates about $58 per month for 10 training plus 1,000 processed documents in US East (N. Virginia), with model inference roughly 85 percent of that cost. AWS cites IDC figures that document-related challenges cost organizations $19,732 per information worker annually and cut productivity by 21.3 percent.

    AWS Machine Learning Blog · 🔥 0
  2. AWS ships MCP server to promote Amazon Quick resources across accounts

    An AWS blog post details the Amazon Quick Resource Migrator, a sample Model Context Protocol server hosted on Amazon Bedrock AgentCore runtime that promotes Amazon Quick agents, action connectors, knowledge bases, flows and spaces from a development AWS account to production. It reads and recreates resources through the Amazon Quick (Quick Sight) API, replays source permissions in the target account, offers a read-only preview, is idempotent across re-runs, and writes versioned S3 backups with a restore tool. S3 documents behind knowledge bases are not copied, and connector credentials are created as placeholders and must be re-authenticated in the target account; full source is in an aws-samples repository.

    AWS Machine Learning Blog · 🔥 0

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