AI-Powered Document Summarizer with Claude 3.7 on AWS

Automate document summaries using AWS serverless and Claude AI. Turn complex docs into quick insights. Scale effortlessly, deploy instantly, save time.

Zechariah Kasina

Published Jun 6, 2025

Last modified Jun 6, 2025

Introduction: Transforming Document Processing with AI

We're all drowning in information. Reports, articles, research papers, and business documents pile up faster than anyone can read them. But what if you could automatically extract the key points from any document in seconds? That's exactly what this system does: a Serverless document summarization system powered by Claude 3.7 Sonnet, one of the most sophisticated language models available on AWS Bedrock.

Let's walk through how this system is built, from the key architectural decisions to the nitty-gritty implementation details. Whether you're writing code, designing systems, or making business decisions, you'll find practical insights on using AI to revolutionize document processing.

The Challenge: From Information Overload to Actionable Insights

Organizations everywhere share a common pain point: making sense of vast document collections. Traditional approaches have serious limitations:

Manual review is painfully slow and doesn't scale
Rule-based systems are rigid and miss important context
Older AI models often produce mediocre results

This solution tackles these challenges head-on by combining serverless architecture with cutting-edge AI, creating a system that automatically generates nuanced, accurate summaries of any document, regardless of its complexity.

Solution Architecture: Smart, Scalable, and Cost-Effective

This serverless solution has below key components:

Document Upload: Drop your documents (PDF, TXT, DOCX) into an Amazon S3 bucket
Automatic Processing: A Lambda function springs into action the moment a file lands
AI Magic: Claude 3.7 Sonnet works its magic through Amazon Bedrock
Instant Results: Summaries land in DynamoDB, and you get notified via SNS

Why did I choose this approach? It's:

Light on your wallet (pay-as-you-go)
Infinitely scalable (from one document to thousands)
Maintenance-free (no server headaches)
Rock-solid secure (with encryption and tight access controls)

Implementation:

This guide will walk you through setting up and deploying the AI-powered Document Summarization Application on AWS, which uses Claude 3.7 Sonnet on Amazon Bedrock for intelligent document summarization.

Prerequisites

Before you begin, make sure you have the following:

AWS Account: You need an AWS account with appropriate permissions to create resources.
AWS CLI: Install and configure the AWS Command Line Interface. Refer this document for more details.

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pip install awscli
aws configure

AWS SAM CLI: Install the AWS Serverless Application Model CLI.

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pip install aws-sam-cli

Python 3.13: The Lambda function uses Python 3.13.
Amazon Bedrock Access: Ensure you have access to Amazon Bedrock and the Claude 3.7 Sonnet model.

Deployment Steps:

1. Clone the Repository

Clone or download this repository to your local machine.

2. Enable Amazon Bedrock Access

Before deploying the application, make sure you have enabled Amazon Bedrock in your AWS account:

Go to the AWS Management Console
Navigate to Amazon Bedrock
Complete the onboarding process if you haven't already
Go to "Model access" in the left navigation
Find "Claude 3.7 Sonnet" and click "Access model"
Accept the terms and conditions
Wait for access to be granted (this may take a few minutes)

3. Deploy the Application

Run the AI setup script to deploy the application:

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chmod +x setup.sh
./setup.sh

The script will:

Check if Amazon Bedrock is enabled in your account
Verify access to the Claude 3.7 Sonnet model
Build the application using AWS SAM
Deploy the CloudFormation stack
Create the necessary resources (S3 bucket, Lambda function, DynamoDB table, SNS topic)
Provide you with the resource names and ARNs

4. Subscribe to Notifications

To receive notifications when documents are processed:

Use the SNS topic ARN provided after deployment
Subscribe your email or other endpoint to the topic:

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aws sns subscribe \
    --topic-arn <TOPIC_ARN> \
    --protocol email \
    --notification-endpoint your-email@example.com

Confirm the subscription by clicking the link in the email you receive

5. Upload Documents

Upload documents to the S3 bucket to trigger the AI processing:

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aws s3 cp your-document.pdf s3://<BUCKET_NAME>/

The application supports the following document types:

PDF (.pdf)
Text files (.txt)
Word documents (.docx)

6. View AI-Generated Summaries

You can view the AI-generated document summaries in the DynamoDB table:

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aws dynamodb scan --table-name AIDocumentSummaries

Testing the Application

Upload a Sample Document

To test the application with a sample document:

Create a sample text file:

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cat > sample_document.txt << EOL
# Sample Document for AI Summarization
## Introduction
This is a sample document to test the AI-powered document summarization application using Claude 3.7 Sonnet on Amazon Bedrock.
## Key Points
1. The application uses serverless architecture on AWS
2. Documents are uploaded to an S3 bucket
3. A Lambda function processes the documents
4. Claude 3.7 Sonnet on Amazon Bedrock generates intelligent summaries
5. Summaries are stored in DynamoDB
6. Notifications are sent via SNS
## Benefits
- Automated document processing
- High-quality AI-generated summaries with Claude's advanced language capabilities
- Larger context window handling (up to 150,000 characters)
- Improved comprehension and summarization accuracy
- Scalable serverless architecture
- Real-time notifications
## Conclusion
This sample demonstrates how Claude 3.7 Sonnet can be used to extract meaningful insights from documents automatically.
EOL

Upload the sample document:

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aws s3 cp sample_document.txt s3://<BUCKET_NAME>/

Wait for the notification (this may take a minute or two)

Check the DynamoDB table for the summary:

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aws dynamodb scan --table-name AIDocumentSummaries

Monitoring and Troubleshooting

Monitoring Lambda Execution

To monitor the Lambda function execution:

Go to the AWS Management Console
Navigate to CloudWatch
Go to "Log groups"
Find the log group for your Lambda function: /aws/lambda/ai-document-summarization-app-DocumentProcessorFunction
View the logs to see the execution details

Common Issues and Solutions

Bedrock Access Error:

Error: "User is not authorized to access this resource"
Solution: Ensure you have enabled Amazon Bedrock and have access to the Claude 3.7 Sonnet model

Document Processing Error:

Error: "Error processing document"
Solution: Check the CloudWatch logs for detailed error messages

Model Invocation Error:

Error: "Error invoking model"
Solution: Verify that the Claude 3.7 Sonnet model is available in your region and you have access to it

Document Format Error:

Error: "Error reading document content"
Solution: Ensure the document is in a supported format and is properly encoded

Checking Bedrock Model Access

To verify that you have access to the Claude 3.7 Sonnet model:

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aws bedrock list-foundation-models --query "modelSummaries[?modelId=='anthropic.claude-3-7-sonnet-20250219-v1:0']" --output text

If this command returns information about the model, you have access. If it returns an empty result or an error, you need to request access to the model.

Customization

Modifying the Prompt

To customize the prompt used for summarization:

Edit src/document_processor_ai.py
Modify the prompt variable in the generate_summary_with_bedrock() function:

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prompt = f"""
Please provide a comprehensive summary of the following document.
Focus on [YOUR CUSTOM INSTRUCTIONS HERE].
DOCUMENT:{document_content}
SUMMARY:
"""

Adjusting Model Parameters

To adjust the Claude 3.7 Sonnet model parameters:

Edit src/document_processor_ai.py
Modify the parameters in the request_body dictionary:

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request_body = {
    "anthropic_version": "bedrock-2023-05-31",
    "max_tokens": 4000,  # Adjust the maximum length of the summary
"temperature": 0.2,  # Adjust for creativity (higher) vs. determinism (lower)
"messages": [
        {
            "role": "user",
            "content": prompt
        }
    ]
}

Cleanup

To remove all resources created by this application:

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aws cloudformation delete-stack --stack-name ai-document-summarization-app

Additional Resources

Conclusion: The Future of Document Processing Is Here

Combining Serverless architecture with Claude 3.7 Sonnet isn't just a neat trick – it's a game-changer in how we handle information. Tasks that used to bog down your best people for hours now happen automatically in seconds, with impressive quality and accuracy.

By implementing this solution, you're not just automating a task. You're fundamentally transforming how your organization interacts with information. The result? Faster insights, better decisions, and more time for the creative and analytical work that humans do best.

Comment your feedback below or create an issue/feature request for this solution on the Github repository .

# genai # amazonq # amazonbedrock # claude # ai

Any opinions in this article are those of the individual author and may not reflect the opinions of AWS.

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AI-Powered Document Summarizer with Claude 3.7 on AWS

Zechariah Kasina

Introduction: Transforming Document Processing with AI

The Challenge: From Information Overload to Actionable Insights

Solution Architecture: Smart, Scalable, and Cost-Effective

Implementation:

Prerequisites

Deployment Steps:

1. Clone the Repository

2. Enable Amazon Bedrock Access

3. Deploy the Application

4. Subscribe to Notifications

5. Upload Documents

6. View AI-Generated Summaries

Testing the Application

Upload a Sample Document

Monitoring and Troubleshooting

Monitoring Lambda Execution

Common Issues and Solutions

Checking Bedrock Model Access

Customization

Modifying the Prompt

Adjusting Model Parameters

Cleanup

Additional Resources

Conclusion: The Future of Document Processing Is Here