🗼 AI powered supply chain control tower with BigQuery and GPT-4o

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Tags: Supply Chain, Logistics, Control Tower Context Hey! I’m Samir, a Supply Chain Engineer and Data Scientist from Paris, and the founder of [LogiGreen Consulting](https:...

Best for

Internal Wiki automation workflows
AI RAG automation workflows
intermediate n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.agent, n8n-nodes-base.stickynote, @n8n/n8n-nodes-langchain.toolworkflow, n8n-nodes-base.googlebigquery, n8n-nodes-base.executeworkflowtrigger, n8n-nodes-base.code, @n8n/n8n-nodes-langchain.memorybufferwindow

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Samir Saci.

Original n8n.io source

1.1 Workflow description

Title: 🗼 AI powered supply chain control tower with BigQuery and GPT-4o
Workflow name: 🗼 AI powered supply chain control tower with BigQuery and GPT-4o

Tags: Supply Chain, Logistics, Control Tower

Context

Hey! I’m Samir, a Supply Chain Engineer and Data Scientist from Paris, and the founder of LogiGreen Consulting.

We design tools to help companies improve their logistics processes using data analytics, AI, and automation—to reduce costs and minimize environmental impact.

> Let’s use N8N to build smarter and more sustainable supply chains!

📬 For business inquiries, you can add me on LinkedIn

Who is this template for?

This workflow template is designed for logistics operations that need a monitoring solution for their distribution chains.

Connected to your Transportation Management Systems, this AI agent can answer any question about the shipments handled by your distribution teams.

How does it work?

The workflow is connected to a Google BigQuery table that stores outbound order data (customer deliveries).

Here’s what the AI agent does:

🤔 Receives a user question via chat.
🧠 Understands the request and generates the correct SQL query.
✅ Executes the SQL query using a BigQuery node.
💬 Responds to the user in plain English.

Thanks to the chat memory, users can ask follow-up questions to dive deeper into the data.

What do I need to get started?

This workflow requires no advanced programming skills.

You’ll need:

A Google BigQuery account with an SQL table storing transactional records.
An OpenAI API key (GPT-4o) for the chat model.

Next Steps

Follow the sticky notes in the workflow to configure each node and start using AI to support your supply chain operations.

🎥 Watch My Tutorial

🚀 Curious how N8N can transform your logistics operations?

Notes

The chat trigger can easily be replaced with Teams, Telegram, or Slack for a better user experience.
You can also connect this to a customer chat window using a webhook.

This workflow was built using N8N version 1.82.1
Submitted: March 24, 2025

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - OpenAI Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.2

Block 2 - AI Control Tower Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.8

Block 3 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 4 - Sticky Note2

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 5 - Call Query Tool

Type / Role: @n8n/n8n-nodes-langchain.toolWorkflow - toolWorkflow
Config choices: Version 2

Block 6 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 7 - Query Database

Type / Role: n8n-nodes-base.googleBigQuery - googleBigQuery
Config choices: Version 2.1

Block 8 - Trigger Executed by the AI Tool

Type / Role: n8n-nodes-base.executeWorkflowTrigger - executeWorkflowTrigger
Config choices: Version 1.1

Block 9 - Sanitising the Query

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 10 - Chat Memory

Type / Role: @n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices: Version 1.3

Block 11 - Chat with the User

Type / Role: @n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
Config choices: Version 1.1

Block 12 - Sticky Note3

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

3. Summary Table

Workflow	🗼 AI powered supply chain control tower with BigQuery and GPT-4o
Complexity	intermediate
Nodes	12
Categories	Internal Wiki, AI RAG
Author	Samir Saci
Published	24 Mar 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/3305/3305.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Internal Wiki workflows AI RAG workflows

Frequently asked questions

What does 🗼 AI powered supply chain control tower with BigQuery and GPT-4o do?

Tags: Supply Chain, Logistics, Control Tower Context Hey! I’m Samir, a Supply Chain Engineer and Data Scientist from Paris, and the founder of [LogiGreen Consulting](https:...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Internal Wiki, AI RAG use case.

Samir Saci

31 workflows

Nodes

@n8n/n8n-nodes-langchain.lmchatopenai @n8n/n8n-nodes-langchain.agent n8n-nodes-base.stickynote @n8n/n8n-nodes-langchain.toolworkflow n8n-nodes-base.googlebigquery n8n-nodes-base.executeworkflowtrigger n8n-nodes-base.code @n8n/n8n-nodes-langchain.memorybufferwindow

Complexity

intermediate

Published 24 Mar 2025

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/3305/3305.json

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🗼 AI powered supply chain control tower with BigQuery and GPT-4o

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Context

Who is this template for?

How does it work?

What do I need to get started?

Next Steps

Notes

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - OpenAI Chat Model

Block 2 - AI Control Tower Agent

Block 3 - Sticky Note1

Block 4 - Sticky Note2

Block 5 - Call Query Tool

Block 6 - Sticky Note

Block 7 - Query Database

Block 8 - Trigger Executed by the AI Tool

Block 9 - Sanitising the Query

Block 10 - Chat Memory

Block 11 - Chat with the User

Block 12 - Sticky Note3

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions