Extract Data with On-demand and Batch Pipelines Dynamically

📰 AWS Machine Learning

Learn to extract data with on-demand and batch pipelines dynamically using Amazon Bedrock for flexible document processing

intermediate Published 11 Jun 2026
Action Steps
  1. Build an intelligent document processing pipeline using Amazon Bedrock
  2. Configure on-demand inference for real-time document processing
  3. Set up batch inference for bulk document processing
  4. Test the pipeline with sample documents to ensure accuracy
  5. Compare the costs and processing times of on-demand and batch pipelines
Who Needs to Know This

Data engineers and machine learning engineers can benefit from this pipeline to efficiently process documents and extract relevant data

Key Insight

💡 Use Amazon Bedrock to create a flexible document processing pipeline that balances time and cost efficiency

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📄 Extract data dynamically with on-demand & batch pipelines on Amazon Bedrock! 💡

Key Takeaways

Learn to extract data with on-demand and batch pipelines dynamically using Amazon Bedrock for flexible document processing

Full Article

This post demonstrates an intelligent document processing pipeline that consists of both on-demand inference and batch inference options on Amazon Bedrock to enable the flexibility on the document processing time and cost.
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