Bedrock Data Automation (Preview): Simplifying Unstructured Data Processing

Bedrock Data Automation (BDA) is a cloud-based service that simplifies the process of extracting valuable insights from unstructured content—such as documents, images, video, and audio. Come learn how BDA leverages generative AI to automate the transformation of multi-modal data into structured formats, enabling developers to build applications and automate complex workflows with greater speed and accuracy.

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Amazon Bedrock Data
Automation
Arnab Sinha
Senior Solutions Architect
AWS
AMAZON WEB SERVICES
Jean Malha
Specialist Solutions Architect – Amazon Bedrock
AWS

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What’s on deck
The multi-modal content challenge
What is Amazon Bedrock Data Automation
Use Cases and Applications Overview
Demo
Questions and Resources

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Why is multi-modal content hard?
Unprecedented scale of
content generation
Hard to get the
desired accuracy
ML is promising but requires
specialized expertise
Lack of standardized
tooling
Complex postprocessing to
adapt and integrate ML output
with downstream systems
Diverse formats and
variations in asset types

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Amazon Bedrock Data Automation
A generative AI-powered capability to transform multi-modal
unstructured content from documents, images, video, and
audio into structured data easily, accurately, and at scale.

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Key Features
Single inference API to
handle production scale
Built-in Responsible AI
with visual grounding,
confidence scores, and
toxic content detection
Simple and intuitive
interface to define output
schemas and fine-grained
business rules
Orchestration across
state-of-the-art task-specific
models and foundation
models to generate highly
accurate, consistent output
Integration with Amazon
Bedrock features and
Knowledge base

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How it works
TYPES OF OUTPUT THAT BDA CAN RETURN
Standard Output
Linearized text representation of asset
Gen-AI optimized output: reading / viewing order,
semantically related output groupings, etc.
Controls to optimize output based on downstream
systems with simple selection knobs
Automatic modality routing based on semantic
modality, not just file type
Supported Modalities for Standard Output
Custom Output
Developer supplied schema based on your
downstream systems (Blueprint)
Supports tasks such as extraction, key and value
normalization, transformations, reasoning,
splitting and classification
Simple NL interface to define business rules and
task logic for each field
Console-based assistant to create bespoke
blueprints in minutes with sample and desired
output description
Supported Modalities for Custom Output
ImagesDocumentsAudioVideo ImagesDocuments

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Key usecases
What are the types of applications where multi-modal content processing is needed?
Media Asset
Analysis &
Monetization
Intelligent
Document Processing
Intelligent
Speech Analytics
Multimodal Intelligent search

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Getting Started with BDA is Easy
INPUTS / OUTPUTS
Input Asset
Amazon Bedrock
Data Automation2
optional
Desired Output Instructions
Output Response
1
ImagesDocumentsAudioVideo
Standard Output
Configuration
List of Custom Output
Resources (Blueprint)
Linearized Text
representation of the
asset based on
configuration
Output returned as JSON +
additional files if
selected in configuration
Custom Schema based for
each asset based on
matched blueprint
Output returned as JSON

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BDA Demo – in console

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Next steps
HOW TO GET STARTED
17
How to get started in
consoleSolutions Guidance