End-to-End-Agentic-Ai-Automation-Lab
Hands-on projects and code examples for multi-agent systems
GraphCanon updated Sep 12, 2026 · GitHub synced Sep 12, 2026
36views this month
Decision brief
End-to-End-Agentic-Ai-Automation-Lab offers hands-on projects and code for multi-agent systems using technologies like LangChain, AutoGen, CrewAI, RAG, MCP, and n8n on Docker, AWS, BentoML.
Good fit when
- For developing complex multi-agent systems with automated workflows
- When you need detailed examples of deploying agents in cloud or container environments
Avoid when
- If your project does not involve multi-agent systems or automation layers like n8n
- If you are looking for a simpler introductory tool to AI without the focus on deployment details
Observed Jul 16, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Slowing (92d since push)
- As of Sep 12, 2026
- Provenance
- Not a fork · Personal account
- As of Sep 12, 2026
- Security (OSV)
- No criticals
- As of Jul 15, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/MDalamin5/End-to-End-Agentic-Ai-Automation-LabHow it fits your stack(1)
Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.
Similar tools
Same-category neighbours not already linked as typed edges.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Repository includes hands-on projects, code examples and deployment workflows for exploring multi-agent systems, LangChain, AutoGen, CrewAI, RAG, MCP, n8n automation, scalable agent deployment using Docker, AWS, BentoML.
Capability facts
- Languages
- jupyter notebook
Source: github.language · Sep 12, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 12, 2026)
pip install -r requirements.txtSource link
Tags
README
3. Install Dependencies Dependencies may vary per module. Navigate to the specific project folder and install the requirements: 📜 License & Connect Distributed under the MIT License . See for more information. <div align="center" Developed with 💡 by Md Al Amin If you find this...
For agents
This page has a .md twin and JSON over the API.