Build an intelligent contract management solution with Amazon Quick Suite and Bedrock AgentCore

Organizations managing hundreds of contracts annually face significant inefficiencies, with fragmented systems and complex workflows that require teams to spend hours on contract review cycles. This solution addresses these challenges through multi-agent collaboration—specialized AI agents that can work simultaneously on different aspects of contract analysis, reducing cycle times while maintaining accuracy and oversight.

This guide demonstrates how to build an intelligent contract management solution using Amazon Quick Suite as your primary contract management solution, augmented with Amazon Bedrock AgentCore for advanced multi-agent capabilities.

Why Quick Suite augmented with Amazon Bedrock AgentCore

Quick Suite serves as your agentic workspace, providing a unified interface for chat, research, business intelligence, and automation. Quick Suite helps you seamlessly transition from getting answers to taking action, while also automating tasks from routine daily activities to complex business processes such as contract processing and analysis.

By using Amazon Bedrock AgentCore with Quick Suite, you can encapsulate business logic in highly capable AI agents more securely at scale. AgentCore services work with many frameworks including Strands Agents, in addition to foundation models in or outside of Amazon Bedrock.

Solution overview

This solution demonstrates an intelligent contract management system using Quick Suite as the user interface and knowledge base, with Amazon Bedrock AgentCore providing multi-agent collaboration functionality. The system uses specialized agents to analyze contracts, assess risks, evaluate compliance, and provide structured insights through a streamlined architecture, shown in the following figure.

Architecture components

The components of the solution architecture include:

• Quick Suite components:
  • Spaces for contract management workflows
  • Chat agents for conversational contract interactions
  • Knowledge bases for integrating legal documents stored in Amazon S3
  • Topics for integrating structured contract data
  • Actions for connecting to custom agents developed with Amazon Bedrock AgentCore
  • Flows for recurring semi-manual document review processes
  • Automate for daily and monthly contract automation tasks
• Multi-agent system powered by AgentCore:
  • Contract collaboration agent: Central orchestrator coordinating workflow
  • Legal agent: Analyzes legal terms and extracts key obligations
  • Risk agent: Assesses financial and operational risks
  • Compliance agent: Evaluates regulatory compliance
• Supporting infrastructure:
  • Amazon API Gateway and AWS Lambda for managing API requests
  • Amazon Simple Storage Service (Amazon S3) for document storage
  • Amazon Redshift for structured data

Contract management workflow

The solution implements a streamlined contract management workflow that significantly reduces processing time while improving accuracy. The system processes contracts through coordinated AI agents, typically completing analysis within minutes compared to days of manual review.

Let’s explore an example of processing a sample service agreement contract. The workflow consists of the following steps:

1. The contract collaboration agent identifies the document as requiring legal, risk, and compliance analysis.
2. The legal agent extracts parties, payment terms, and obligations.
3. The risk agent identifies financial exposure and negotiation leverage points.
4. The compliance agent evaluates regulatory requirements and flags potential issues.
5. The contract collaboration agent consolidates findings into a comprehensive report.

Prerequisites

Before setting up Quick Suite, make sure you have:

• An AWS account with administrative permissions
• Access to supported AWS Regions where Quick Suite is available
• Appropriate AWS Identity and Access Management (IAM) roles and policies for Quick Suite service access

Setup part 1: Set up Quick Suite

In the following steps we set up the Quick Suite components.

Enable Quick Suite

Your AWS administrator can enable Quick Suite by:

1. Signing in to the AWS Management Console
2. Navigating to Quick Suite from the console
3. Subscribing to Quick Suite service for your organization
4. Configuring identity and access management as needed

After Quick Suite is enabled, navigate to the Amazon Quick Suite web interface and sign in with your credentials.

Create the contract management space

In Quick Suite, create a new space called Contract Management to organize your contract-related workflows and resources. You can then use the assistant on the right to ask queries about the resources in the space. The following figure shows the initial space.

Set up a knowledge base for unstructured data (Amazon S3)

Follow these steps:

1. Navigate to Knowledge bases: In the Integrations section, select Knowledge bases.
2. Add Amazon S3 integration:
   • Select Amazon S3 as your data source.
   • Configure the S3 bucket that will store your contract documents.
   • After the knowledge base is created, add it to the Contract Management space.

Set up a knowledge base for structured data (Amazon Redshift)

Follow these steps:

1. Add dataset: In the Datasets section, configure your contract data warehouse (Amazon Redshift) for structured contract data. Follow these instructions in Creating a dataset from a database and wait until your dataset is configured.
2. Add data topics: In the Topics section, integrate structured contract data sources such as:
   • Contract databases
   • Vendor information systems
   • Compliance tracking systems

For adding topics in Quick Suite, see Adding datasets to a topic in Amazon Quick Sight.

3. Add topics to your space: Add the relevant topics to your Contract Management space.

Setup part 2: Deploy Amazon Bedrock AgentCore

Amazon Bedrock AgentCore provides enterprise-grade infrastructure for deploying AI agents with session isolation, where each session runs with isolated CPU, memory, and filesystem resources. This creates separation between user sessions, helping to safeguard stateful agent reasoning processes.

1. You can find the required code in this GitHub repository. Go to the subfolder legal-contract-solution/deployment.
2. The solution includes a comprehensive deploy_agents.py script that handles the complete deployment of the AI agents to AWS using cloud-centered builds. These instructions require Python>=3.10.

pip3 install -r requirements.txt
python3 deploy_agents.py

What the deployment script does

The deployment process is fully automated and handles:

• Dependency management:
  • Automatically installs bedrock-agentcore-starter-toolkit if needed
  • Verifies the required Python packages are available
• AWS infrastructure setup:
  • Creates IAM roles with the necessary permissions for agent execution
  • Sets up Amazon Elastic Container Registry (Amazon ECR) repository for container images
  • Configures Amazon CloudWatch logging for monitoring
• Agent deployment:
  • Deploys four specialized agents
  • Uses AWS CodeBuild for cloud-centered ARM64 container builds
  • No local Docker required—the builds happen in AWS infrastructure
• Configuration management:
  • Automatically configures agent communication protocols
  • Sets up security boundaries between agents
  • Establishes monitoring and observability

After the agents are deployed, you can see them in the Amazon Bedrock AgentCore console, as shown in the following figure.

Setup part 3: Integrate Amazon Bedrock AgentCore with Quick Suite

Quick Suite can connect to enterprise solutions and agents through actions integrations, making tools available to chat agents and automation workflows.

Deploy API Gateway and Lambda 

Go to the subfolder legal-contract-solution/deployment and run the following command: python3 deploy_quicksuite_integration.py

This will provision Amazon Cognito with a user pool to permission access to the API Gateway endpoint. The Quick Suite configuration references the OAuth details for this user pool. After successful deployment, two files will be generated for your Quick Suite integration:

• quicksuite_integration_config.json – Complete configuration
• quicksuite_openapi_schema.json– OpenAPI schema for Quick Suite import

Set up actions integration in Quick Suite

In the Actions section, prepare the integration points that will connect to your agents deployed by AgentCore:

1. Get the OpenAPI specification file quicksuite_openapi_schema.json from the working folder.
2. In the Integrations/Actions section, go to OpenAPI Specification. Create a new OpenAPI integration by uploading the api_gateway_openapi_schema.json file, and enter the following Name and Description for the provided agents. Enter the endpoint with the URL by using the information from the quicksuite_integration_config.json file.
   • Name: Legal Contract Analyzer
   • Description: Analyze a legal contract using AI agents for clause extraction, risk assessment, and compliance checking

Set up chat agent definition details

In the Chat agents section, set up the following agent and enter the following details:

• Name: Legal Contract AI Analyzer
• Description:

  An AI-powered system that analyzes legal contracts and performs comprehensive risk 
  assessments using advanced machine learning capabilities to identify potential issues, 
  compliance gaps, and contractual risks.

• Agent identity:

  You are an expert legal contract analysis AI system powered by advanced GenAI 
  capabilities. Your purpose is to provide comprehensive contract review and risk 
  assessment services.

• Persona instructions:

  Use the legal contract analyzer when possible. Always categorize risks by 
  severity (High, Medium, Low). Highlight non-standard clauses, missing provisions, 
  and potential compliance issues. Provide specific recommendations for contract improvements. 
  When analyzing liability clauses, pay special attention to indemnification, limitation of 
  liability, and force majeure provisions. Flag any unusual termination conditions or intellectual 
  property concerns.

• Communication style: Professional, precise, and analytical with clear legal terminology.
• Response format: 

  Provide structured analysis with clear risk categorization, severity levels, and actionable 
  recommendations. Use bullet points for key findings and numbered lists for prioritized recommendations.

• Length: 

  Comprehensive analysis covering all critical aspects while maintaining clarity and focus on actionable insights.

• Welcome message: 

  Welcome to the Legal Contract AI Analyzer. Upload contracts for intelligent analysis and risk assessment.

• Suggested prompts: 
  • Analyze this contract for potential legal risks and compliance issues
  • Review the liability clauses in this agreement for red flags
  • Assess the termination conditions and notice requirements in this contract

Test your contract management solution

Now that you’ve deployed the infrastructure and configured Quick Suite, you can test the contract management solution by selecting the Contract Management space. You can use the agent interface to ask questions about the knowledge base and instruct agents to review the documents. Your space will look like the following figure:

Clean up

There are associated infrastructure costs with the deployed solution. Once you no longer need it in your AWS account, you can go to the subfolder legal-contract-solution/deployment and run the following command for clean up:python3 cleanup.py

Conclusion

The combination of Amazon Quick Suite and Amazon Bedrock AgentCore offers procurement and legal teams immediate operational benefits while positioning them for future AI advancements. You can use Amazon Bedrock multi-agent collaboration to build and manage multiple specialized agents that work together to address increasingly complex business workflows. By implementing this intelligent contract management solution, you can transform your organization’s procurement processes, reduce contract cycle times, and enable your teams to focus on strategic decision-making rather than administrative tasks. Because of the solution’s extensible architecture, you can start with core contract management functions and gradually expand to address more complex use cases as your organization’s needs evolve. Whether you’re looking to streamline routine contract reviews or implement comprehensive procurement transformation, the intelligent contract management solution provides a powerful foundation for achieving your business objectives. To learn more about Amazon Quick Suite and Amazon Bedrock AgentCore, see:

• Amazon Quick Suite
• Amazon Bedrock AgentCore

About the authors

Oliver Steffmann is a Principal Solutions Architect at AWS based in New York and is passionate about GenAI and public blockchain use cases. He has over 20 years of experience working with financial institutions and helps his customers get their cloud transformation off the ground. Outside of work he enjoys spending time with his family and training for the next Ironman.

David Dai is an Enterprise Solutions Architect at AWS based in New York. He works with customers across various industries, helping them design and implement cloud solutions that drive business value. David is passionate about cloud architecture and enjoys guiding organizations through their digital transformation journeys. Outside of work, he values spending quality time with family and exploring the latest technologies.

Krishna Pramod is a Senior Solutions Architect at AWS. He works as a trusted advisor for customers, guiding them through innovation with modern technologies and development of well-architected applications in the AWS cloud. Outside of work, Krishna enjoys reading, music and exploring new destinations.

Malhar Mane is an Enterprise Solutions Architect at AWS based in Seattle, where he serves as a trusted advisor to enterprise customers across diverse industries. With a deep passion for Generative AI and storage solutions, Malhar specializes in guiding organizations through their cloud transformation journeys and helping them harness the power of generative AI to optimize business operations and drive innovation. Malhar holds a Bachelor’s degree in Computer Science from the University of California, Irvine. In his free time, Malhar enjoys hiking and exploring national parks.

Praveen Panati is a Senior Solutions Architect at Amazon Web Services. He is passionate about cloud computing and works with AWS enterprise customers to architect, build, and scale cloud-based applications to achieve their business goals. Praveen’s area of expertise includes cloud computing, big data, streaming analytics, and software engineering.

Sesan Komaiya is a Solutions Architect at Amazon Web Services. He works with a variety of customers, helping them with cloud adoption, cost optimization and emerging technologies. Sesan has over 15 year’s experience in Enterprise IT and has been at AWS for 5 years. In his free time, Sesan enjoys watching various sporting activities like Soccer, Tennis and Moto sport. He has 2 kids that also keeps him busy at home.

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