Deep Insight

Production-ready multi-agent framework for building scalable data analysis workflows without infrastructure headaches

Why Deep Insight? ◆ Quick Start ◆ Demo ◆ Architecture

Latest News 🔥

• [2025/11] Added per-agent token tracking with detailed metrics - monitor input/output tokens and cache reads/writes for complete cost visibility and optimization
• [2025/11] Added editable DOCX report generation - all analysis results are exportable to fully editable Word documents for easy customization and sharing
• [2025/10] Released Deep Insight Workshop (Korean | English)
• [2025/10] Added support for Claude Sonnet 4.5 with extended thinking and enhanced reasoning capabilities
• [2025/09] Released Deep Insight framework built on Strands SDK and Amazon Bedrock with hierarchical multi-agent architecture

Are You Facing These Challenges?

에이전트 설계, 어디서부터 시작해야 할지 고민이신가요? (Struggling with Agent Architecture?)

Deep Insight provides a proven hierarchical architecture with Coordinator, Planner, Supervisor, and specialized tool agents. Start with a working production-grade system and customize from there—no need to design from scratch.

프로덕션급 성능의 에이전트, 어떻게 만들어야 할지 막막하신가요? (Need Production-Grade Performance?)

Get production-grade multi-agent workflows out of the box with prompt caching, streaming responses, token tracking, and battle-tested performance patterns. Deploy with confidence using architecture validated in real-world scenarios.

민감한 데이터를 안전하게 처리하고 싶으신가요? (Concerned About Data Security?)

Deploy Deep Insight in your own AWS VPC for complete data isolation and control. All data processing happens within your secure VPC environment, with Amazon Bedrock API calls staying in AWS infrastructure—never exposed to the public internet.

Why Deep Insight?

Transform weeks of manual reporting work into minutes using hierarchical multi-agent systems built on Strands SDK and Amazon Bedrock.

• 🎨 Full Customization & Control - Modify agents, prompts, and workflows with complete code access in your AWS VPC
• 🔒 Enterprise-Grade Security - Single-tenant VPC deployment with complete data isolation
• 🤖 Advanced Multi-Agent Architecture - Hierarchical workflow with Coordinator, Planner, Supervisor, and specialized tool agents
• 🧠 Flexible Model Selection - Choose different Claude models for each agent (Sonnet 4, Haiku 4, etc.) via simple .env configuration
• 📊 Transparency & Verifiability - Reports with calculation methods, sources, and reasoning processes
• 🚀 Beyond Reporting - Extend to any agent use case: shopping, support, log analysis, and more

Quick Start

Deep Insight provides a self-hosted deployment that you can run locally or in your AWS VPC with complete code access and customization.

Self-Hosted Deployment

Run agents locally or in your VPC with full control over:

• ✅ Complete code access to agents, prompts, and workflows
• ✅ Rapid iteration during development (no rebuild required)
• ✅ Flexible infrastructure management
• ✅ Simple setup in ~10 minutes

Get Started: ./self-hosted/

• 📖 Read: Self-Hosted README

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Demo

Fresh Food Sales Data Analysis

Task: "Create a sales performance report for Moon Market. Analyze from sales and marketing perspectives, generate charts and extract insights, then create a docx file. The analysis target is the ./data/Dat-fresh-food-claude.csv file."

Workflow: Input (CSV data file: Dat-fresh-food-claude.csv) → Process (Natural language prompt: "Analyze sales performance, generate charts, extract insights") → Output (DOCX report with analysis, visualizations, and marketing insights)

▶️ Watch Full Demo on YouTube

Sample Outputs

📄 English Report | 📄 Korean Report

Contributing

We welcome contributions! See CONTRIBUTING.md for details.

Quick Start for Contributors

# Fork the repository on GitHub, then clone your fork
git clone https://github.com/aws-samples/sample-deep-insight.git
cd sample-deep-insight

# Follow the self-hosted setup instructions
cd self-hosted && follow the README.md

# Create feature branch
git checkout -b feature/your-feature-name

# Make changes, test, then commit and push
git add .
git commit -m "Add feature: description"
git push origin feature/your-feature-name

# Open a Pull Request on GitHub

Contribution Areas

• New Agent Types: Add specialized agents for specific domains
• Tool Integration: Create new tools for agent capabilities
• Model Support: Add support for additional LLM providers
• Documentation: Improve guides, examples, and tutorials
• Bug Fixes: Fix issues and improve stability
• Performance: Optimize streaming, caching, and execution

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

Philosophy

"Come From Open Source, Back to Open Source"

We believe in the power of open collaboration. Deep Insight takes the excellent work of the LangManus community and extends it with AWS-native capabilities, then contributes those enhancements back to the community.

Contributors

Name	Role	Contact
Dongjin Jang, Ph.D.	AWS Sr. AI/ML Specialist SA	Email · LinkedIn · GitHub · Hugging Face
Gonsoo Moon	AWS Sr. AI/ML Specialist SA	Email · LinkedIn · GitHub · Hugging Face
Chloe(Younghwa) Kwak	AWS Sr. Solutions Architect	Email · LinkedIn · GitHub · Hugging Face
Yoonseo Kim	AWS Solutions Architect	Email · LinkedIn · GitHub
Jiyun Park	AWS Solutions Architect	Email · LinkedIn · GitHub

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Built with ❤️ by AWS KOREA SA Team
_{Empowering enterprises to build customizable agentic AI systems}