Lightweight Multi-Agent Framework for Amazon Bedrock
A lightweight multi-agent framework for building AI workflows on Amazon Bedrock using AWS CDK, fully powered by AWS Managed Services—no third-party tools.
Published Feb 12, 2025
Last Modified Feb 13, 2025
As AI-driven automation evolves, the need for multi-agent systems has become essential in enabling scalable, intelligent, and collaborative AI workflows. Amazon Bedrock provides an excellent foundation for orchestrating multiple agents, ensuring they work together to solve complex tasks efficiently.
In this blog, we introduce the Multi-Agent Lightweight System for Amazon Bedrock, an open-source solution designed to streamline the creation, deployment, and testing of multi-agent workflows. Whether you are validating contracts, analyzing documents, or integrating with retrieval-augmented generation (RAG) systems, this solution offers a modular and adaptable framework.
Traditional AI models often operate in isolation, tackling single tasks without interacting with other models. Multi-agent systems overcome this limitation by enabling:
- Task Specialization – Different agents focus on specific tasks, ensuring domain expertise.
- Collaboration & Coordination – A Supervisor Agent orchestrates multiple Collaborator Agents to break down complex processes.
- Scalability – The system can dynamically adapt and introduce new agents as required.
- Multi-Modal Capabilities – Agents can handle text-based and image-based documents, enhancing automation capabilities.
You know that feeling when you're searching for a solution, and you just want to get started fast without reading a novel? Don't worry—I've got you covered! 🎯 You'll find a complete README in the GitHub Repo (and a TL;DR for the impatient ones who just want to get building right away). 🚀
GitHub Repo Link : agentic-workflows-amazon-bedrock
The Multi-Agent Lightweight System for Amazon Bedrock provides a CDK-based infrastructure to deploy and manage multi-agent workflows. The architecture enables users to define custom AI agents through a YAML configuration file and interact seamlessly with Amazon Bedrock’s AI capabilities.
- AWS CDK-powered deployment for easy infrastructure management.
- Customizable multi-agent orchestration using Supervisor and Collaborator Agents.
- Lambda-backed AI tools for retrieving and analyzing documents or any other capabilities required through custom ad-hoc code.
- Seamless integration with Amazon Bedrock’s foundation models.
Below is the high-level architecture of the multi-agent system:
- Supervisor Agent: Coordinates workflow execution and assigns tasks.
- Collaborator Agents: Handle specialized tasks like text validation, compliance checks, and image analysis.
- Knowledge Base & RAG: Retrieves relevant content to enrich responses.
- Amazon Bedrock Agents: Execute AI-driven tasks using Claude, Titan, and other foundation models.
- Agent Tools (Lambda Functions): Provide auxiliary services such as document retrieval and image analysis.
To illustrate the capabilities of this system, let’s explore an automated contract validation use case. In this scenario, multiple agents work together to process, validate, and analyze a Statement of Work (SoW) document.
The following agents are orchestrated by a Supervisor Agent to ensure a structured and modular validation process:
- Analyse Image Document Agent 📷
- Extracts and analyzes images from the SoW document to provide visual insights.
- Uses the Claude 3 Sonnet model for enhanced image interpretation.
- Structural Compliance Agent 📄
- Ensures the document follows standard structural and formatting guidelines.
- Verifies adherence to predefined SoW templates that have been shared through a prompt
- Technical Scope Validation Agent 🏗️
- Validates the technical feasibility of the SoW.
- Ensures all technical specifications are aligned with best practices.
- Business Financial Validation Agent 💰
- Evaluates the financial aspects of the contract.
- Reviews cost breakdowns, investments, and budget allocations.
- Risk & Compliance Agent ⚖️
- Identifies potential risk factors and compliance issues.
- Flags areas that may require additional due diligence.
- Delivery Milestones Validation Agent 📆
- Ensures that project milestones and delivery schedules are well-defined.
- Verifies if deliverables are achievable within the proposed timelines.
- AI Consistency Agent 🤖
- Validates AI-related elements within the SoW.
- Ensures correct AI model selection and feasibility.
- AWS Architecture Validation Agent 🏛️
- Analyzes AWS architecture diagrams for best practices compliance.
- Extracts AWS service details and validates security considerations.
- Supervisor Agent 🎯
- Orchestrates the workflow execution and aggregates responses from all agents.
- Ensures smooth collaboration between specialized agents.
Detailed AWS Architecture:
The Multi-Agent Lightweight System is a work in progress, and there’s always room to grow! Here are some areas where the system could be enhanced to provide even better multi-agent coordination and AI-driven automation:
- Implement Bedrock Guardrails to enforce ethical AI usage and prevent hallucinations.
- Extend beyond DEFAULT orchestration to custom workflows, enabling flexible agent interactions (AWS Docs).
- Introduce a reranker model to enhance retrieval-augmented generation (RAG) responses, improving knowledge retrieval quality.
- Implement decorators to simplify tool development, allowing testing before deployment.
The Multi-Agent Lightweight Framework for Amazon Bedrock simplifies the development, deployment, and testing of multi-agent workflows. By leveraging AWS Bedrock, CDK, and serverless components, this solution empowers developers to build scalable, intelligent, and adaptable AI-powered automation.
Ready to get started? Clone the repo, deploy the stack, and start building your AI-powered multi-agent workflows on AWS today! 🚀