đź—Ľ AI powered supply chain control tower with BigQuery and GPT-4o
Needs changesNeeds changes. This template uses 1 thing(s) that n8n 3.0 removes: AI Agent v1 (old agent modes). 1 breaking item(s) found. Static check, last run 2026-10-19.
What to replace before upgrading
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) AI Control Tower Agent (v1.8) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (8)
- OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - AI Agent
@n8n/n8n-nodes-langchain.agent - Call n8n Workflow Tool
@n8n/n8n-nodes-langchain.toolWorkflow - Google BigQuery
n8n-nodes-base.googleBigQuery - Execute Workflow Trigger
n8n-nodes-base.executeWorkflowTrigger - Code
n8n-nodes-base.code - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger
What it does
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. !Supply Chain Control Tower 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). !BigQuery Table Here’s what the AI agent does: 1. 🤔 Receives a user question via chat. 2. 🧠Understands the request and generates the correct SQL query. 3. ✅ Executes the SQL query using a BigQuery node. 4. 💬 Responds to the user in plain English. !Example of Interactions 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. !Tutorial Screenshot 🎥 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