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Implementation of Secure AWS-Based Generative AI Architecture for Legal Document Intelligence

Cloud
Posted On: 20 February, 2026

About the Client

The client provides a legal management platform that integrates case management, client intake, analytics, and document generation into a unified system. ​
The platform enables law firms to automate workflows, improve collaboration, and enhance client engagement throughout the case lifecycle.​

Business Needs | Enable scalable GenAI-powered document intelligence within a secure AWS environment

The client sought to enhance document intelligence capabilities to improve information accessibility and automate document-driven workflows across its legal platform.

  • Implement extractive summarization and entity extraction for prioritized legal document types​
  • Provide an “Ask a Document” capability to enable contextual document querying​
  • Establish a scalable foundation to support future enhancements such as sentiment analysis and anomaly detection​
  • Enable structured tracking, evaluation, and continuous improvement of GenAI outputs​
  • Deliver a rapid prototype to validate business value and accelerate user adoption​
  • Ensure strict data privacy, security, and compliance within an AWS-controlled environment

Solutions | Deploy secure, scalable Generative AI services on AWS with prompt engineering lifecycle management

We designed and implemented a cloud-native Generative AI architecture fully deployed within AWS to support document processing, summarization, and contextual querying.

  • Used Amazon Textract to extract structured data from legal documents stored in Amazon S3​
  • Leveraged Amazon Bedrock foundation models to enable extractive summarization and entity extraction​
  • Implemented Bedrock Guardrails to enforce responsible AI controls and output moderation​
  • Developed an “Ask a Document” capability using Bedrock-powered contextual response generation​
  • Built a prompt engineering management framework using Amazon DynamoDB for prompt storage and versioning, enabling dynamic prompt selection and A/B testing​
  • Deployed serverless processing pipelines using AWS Lambda and Amazon API Gateway​
  • Secured credentials and configuration using AWS Secrets Manager​
  • Enabled observability and prompt evaluation through Langfuse integration​
  • Implemented infrastructure-as-code using AWS CloudFormation orchestrated via the AWS Cloud Development Kit (CDK) to ensure consistent, repeatable, and auditable deployments​​

All data processing remained within the AWS environment to maintain enterprise-grade security and compliance.​

Business Impact

By integrating Generative AI capabilities into its platform, the client enhanced document processing efficiency and user experience.

  • Reduced manual data entry through automated form filling and entity extraction​
  • Improved document comprehension using extractive summarization and contextual querying​
  • Increased productivity through AI-assisted information retrieval​
  • Established a scalable AI foundation to support future capabilities such as sentiment analysis and anomaly detection​
  • Strengthened data security posture by keeping all GenAI workloads within AWS​​

The solution provides a scalable, AWS-native foundation for continued innovation in AI-powered legal document management.

Technology Stack

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Implementation of Secure AWS-Based Generative AI Architecture for Legal Document Intelligence
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