Revolutionizing Document Generation Process by leveraging Amazon Bedrock Multi-Agent Framework & Nova Pro LLM

Co-authored by: @diptc99 & @amit873

Generating standardized project documentation such as Proof of Concept (POC) documents, Statement of Work (SOW) documents, Technical design documents, planning documents, handover documentation is a time-consuming tasks over the entire project tenure which includes all the cycles like sales, delivery, operation for most consultants and architects in all service integrator organizations. Integrator uses a standard set of formats to deliver the above mentioned documentation. This blog provides an overview of how content generation power of LLM and automation capability of AI-powered Agents are being leveraged to revolutionize the document creation process. By leveraging this solution as an accelerator, different personas like Architects, Consultants who are involved in different project cycles can increase their productivity by 50-60% resulting in a faster time-to-market to deliver the documentations.

Business Challenge
In recent time, Organizations are focused on creating documentations from sales cycles to operation cycle. Creating these documents manually is labor-intensive, prone to inconsistencies, and significantly extends project initiation timeframes. Document creation often becomes a bottleneck, delaying critical project initiatives and consuming valuable consultant hours that could be better utilized in high-value activities.
The solution aims to accelerate the documentation process by automating the generation of standardized project artifacts while maintaining quality and consistency across all documentation.
Solution Approach leveraging Agentic AI
The solution was conceptualized with an objective to accelerate the documentation generation process by enhancing the productivity of diverse personas working across the project lifecycle. The multi-agent architecture enables intelligent automation of document creation with specialized agents handling specific document types while ensuring consistency in formatting, content quality, and adherence to organizational standards.
The agentic approach provides several key advantages:

1. Specialized Document Intelligence: Each agent is designed with specific knowledge about its document type, understanding the structure, required sections, and content expectations.
2. Context-Aware Document Generation: Agents can process existing documents or minimal inputs to generate comprehensive new documents while maintaining contextual relevance.
3. Collaborative Document Creation: The orchestrator coordinates between specialized agents, selecting the appropriate agent based on document requirements and user intent.
4. Continuous Learning and Improvement: The system can be enhanced over time by incorporating feedback on generated documents and expanding the capabilities to handle additional document types.
5. Input Validation and Error Handling: Built-in validation ensures proper document formats and sizes are provided, improving the overall quality of generated outputs.
6. Dynamic Content Generation: Each agent employs advanced prompt engineering techniques to generate appropriate content for specialized document sections such as executive summaries, scope statements, and deliverables. Process flow diagram for document generation is given below:

Here are the key personas involved in the process and how the solution improves their productivity:

Solution Architecture on AWS
The solution was designed and developed with the following core objectives:
• Automated Generation of Project Documentation
A specialized Bedrock Agent framework driven by advanced language models was developed to generate comprehensive project documentation based on minimal user input or existing documentation.
• Multi-Document Type Support
The solution supports multiple document types, for example:
o POC Documents with complete executive summaries, success criteria, and deliverables.
o State of work Documents tailored to client requirements.
o Technical design document tailored to client requirements.
• Intelligent Document Processing
The system can process existing SOW documents to extract relevant information and generate standardized filled documents aligned with best practices.
• User Experience and Analytics
The solution features an intuitive React-based UI with Cognito integration for secure authentication and comprehensive usage analytics to track and optimize the document generation process.
Solution Components Overview
The overall solution is built using Amazon Bedrock Multi-Agent Framework, various AWS services for processing and storage, and a responsive user interface.

Amazon Bedrock Agents – The solution utilizes multiple specialized agents within the Bedrock Multi-Agent Framework, for example:
• Orchestrator Agent acts as the supervisor, routing user requests to the appropriate document generation agent.
• POC Document Generation Agent specializes in creating comprehensive POC documentation.
For each document type, there will be 1 agent to serve.
AWS Services Utilized:
• Amazon Bedrock Nova Pro for the foundation large language model capabilities.
• Amazon S3 for document storage and retrieval.
• Amazon DynamoDB for document metadata management.
• Amazon Cognito for user authentication and access control.
• AWS Lambda for serverless processing of document requests.
• Amazon API Gateway for API management.
• Amazon ECS with Fargate for containerized application hosting.
• Amazon ECR for container registry services.
• AWS Route 53 for DNS management.
• AWS Load Balancer for traffic distribution.
• Amazon CloudWatch for monitoring and operational insights.
User Interface and Analytics:
• React-based responsive UI with modern design principles.
• Cognito integration for secure authentication and user management.
• Comprehensive usage of analytics dashboard for system administrator.
• Document generation metrics and user behavior tracking.
Security Considerations
Below are the attributes considered for building a robust secure solution.

Usage Scenarios
Here are the examples of the primary usage scenarios for the solution:
Scenario 1 – POC Document Generation
• The user logs into the React-based UI using Cognito authentication.
• The user interacts with the system requesting a POC document and provides a brief description or summary of the POC requirements.
• The Orchestrator Agent routes the request to the POC Document Generation Agent.
• The agent processes the input and generates a comprehensive POC document with standardized sections including Executive Summary, Project Success Criteria, Assumptions, Scope of Work, Milestones and Deliverables, and Acceptance Criteria.
• The completed document is stored in S3, and the document path is provided to the user.
• Usage metrics are captured in the analytics dashboard.
Scenario 2 – SoW Document Generation
• The authenticated user uploads an existing Project SOW document in PDF format through the UI.
• The Orchestrator Agent validates the document format and size before routing to the SoW Document Agent.
• The agent analyzes the input document and generates a comprehensive SoW.
• The document generated includes Executive Summary, Project Success Criteria, Assumptions, Scope of Work, Milestones and Deliverables, Acceptance Criteria, and Duration of Work.
• The document is stored in S3 with a unique Document ID for future reference.
• The system logs the document generation event and time taken for analytics purposes.
User Interface and Analytics Dashboard
The solution includes a comprehensive React-based user interface with secure Cognito authentication and an administrative analytics dashboard:
• User Authentication and Management
o Secure login with Amazon Cognito integration.
o Role-based access control for different user types (administrators, regular users).
o Self-service password management and multi-factor authentication.
• Document Generation Interface
o Intuitive document type selection.
o User-friendly input forms for document parameters.
o File upload capability for source documents.
o Real-time status updates during document generation.
o Document history and retrieval functionality.
• Analytics Dashboard The administrative dashboard provides comprehensive insights into system usage:
o User Engagement Metrics
 Active users per day/week/month.
 Average session duration.
 Login frequency and patterns.
 User retention rates.
o Document Generation Analytics
 Documents generated by type (POC, SoW, Technical Design).
 Document generation requests per user/team.
 Success and error rates for document generation.
Solution Benefits and Future Enhancements
• By leveraging this solution as an accelerator, different personas like Architects, Consultants who are involved in different project cycles can increase their productivity by 50-60%
• The solution accelerator is being further enhanced to create a single pane of view of writer, reviewer and approver. Also, multilingual support will be enabled in future.
Challenges and Issues
While implementing the solution, several challenges were addressed:
• Document Size Limitations: API restrictions for document processing were overcome by implementing chunking strategies and S3 integration for larger documents.
• Document Format Standardization: Robust validation ensures only PDF documents under 1MB are accepted for processing.
• Content Quality Assurance: The agents were fine-tuned to maintain consistent document quality and structure across all generated artifacts.
• User Authentication Security: Implemented Cognito with multi-factor authentication and proper role-based access controls.
• Analytics Data Privacy: Ensured compliance with data protection regulations while collecting meaningful usage statistics.
Conclusion
The solution demonstrates how AWS Bedrock Multi-Agent Framework can be leveraged to build a comprehensive platform for accelerating documentation generation. By automating the creation of standardized project documents, organizations can significantly reduce the time required for project initiation while ensuring consistency and quality across all documentation.
This automation solution not only increases productivity but also allows project teams to focus on higher-value activities instead of routine documentation tasks. The framework can be further extended to support additional document types and customized to meet specific organizational requirements.