How I used Amazon Nova-Lite to build an AI-powered legal Document Analyzer

Introduction

Have you ever clicked "I agree" without reading the Terms and Conditions? You're not alone. Legal documents, contracts, user agreements, or privacy policies are often filled with dense, complex language that most people skip.

What if AI could help streamline this process? That's exactly what I set out to build: an AI-powered legal document analyzer using Amazon Bedrock's Nova models.

Enter Amazon Bedrock and Amazon Nova

Amazon Bedrock provides serverless access to powerful foundation models through a unified API. For this project, I leveraged the Nova Lite model (`amazon.nova-lite-v1:0`), which offers an excellent balance of performance and cost-effectiveness for text analysis tasks.

The Architecture

I used the recent Nova Models to build a solution that summarizes, extracts key clauses, and flags risks from contracts, terms and conditions, and agreements.

The application follows a simple workflow:

Document Upload: Users upload their legal documents through the Streamlit interface
Text Extraction: For PDFs, Amazon Textract extracts the text content
AI Analysis: The extracted text is sent to Amazon Nova with specialized prompts
Results Presentation: The analysis is displayed in an organized, user-friendly format

The Magic Behind the Scenes: Prompt Engineering

The key to getting high-quality legal analysis lies in effective prompt engineering. I created specialized system prompts that instruct the Nova model to act as a legal document assistant:

For each analysis task, I crafted specific user prompts:

Summary generation: "Summarize the following legal contract in bullet points..."
Clause extraction: "Extract all important legal clauses and their purposes..."
Risk identification: "Identify any potential risks or unusual terms..."

Implementation Highlights

S3 Integration

The `s3_upload.py` script handles secure document storage:

Text Extraction with Textract

The extraction function module uses Amazon Textract to process PDF documents:

Nova Model Integration

This is how I implemented the Nova Model:

User Interface

The Streamlit-based frontend provides an intuitive experience:

Take a look at the final solution:

Results and Benefits

The finished application delivers impressive results:

Time savings: Analysis that would take hours is completed in minutes
Comprehensive review: Consistent extraction of key information from any contract
Risk identification: Highlights potential issues that might be overlooked
User-friendly output: Presents findings in a clear, organized format
Downloadable reports: Allows users to save and share analysis results

Lessons Learned

Building this application taught me several valuable lessons:

Prompt engineering is crucial: The quality of AI outputs depends heavily on how you structure your prompts
Error handling matters: Robust error handling ensures a smooth user experience
AWS service integration: Combining multiple AWS services creates powerful workflows
Iterative improvement: Testing with real legal documents helped refine the system

Conclusion

This contract analyzer is a great example of how AI can help anyone—lawyers, business owners, or everyday users—understand complex contracts, terms, and agreements.

If you have your idea or workflow to improve with AI, Amazon Bedrock makes it easy. You can use Amazon Nova to build smart apps without worrying about infrastructure or model tuning.

👉 Start building with Nova on Bedrock

Check Out the Repo here : AI-Legal Reviewer Project

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