Automate Singapore COE price analysis & purchase timing with GLM-4.5 AI predictions

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Important notice

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

1. Workflow Overview

Introduction Automates Singapore COE price tracking, predicts trends using AI, and recommends optimal car purchase timing. Scrapes LTA data biweekly, analyzes historical trends, forecasts next 6 bi...

Best for

Market Research automation workflows
AI Summarization automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.scheduletrigger, n8n-nodes-base.httprequest, n8n-nodes-base.code, n8n-nodes-base.googlesheets, n8n-nodes-base.set, @n8n/n8n-nodes-langchain.agent, n8n-nodes-base.emailsend, n8n-nodes-base.if

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Cheng Siong Chin.

Original n8n.io source

1.1 Workflow description

Title: Automate Singapore COE price analysis & purchase timing with GLM-4.5 AI predictions
Workflow name: Automate Singapore COE price analysis & purchase timing with GLM-4.5 AI predictions

Introduction

Automates Singapore COE price tracking, predicts trends using AI, and recommends optimal car purchase timing. Scrapes LTA data biweekly, analyzes historical trends, forecasts next 6 bidding rounds, and sends alerts when buying windows appear—saving time and identifying cost-saving opportunities.

How it Works

Biweekly trigger scrapes LTA COE data → processes historical trends → AI predicts 6-month prices → compares current vs forecast → generates buy/wait recommendations → alerts sent via Gmail or Telegram.

Setup Steps

Add NVIDIA/OpenAI API credentials in n8n
Connect Google Sheets for data storage
Authenticate Gmail/Telegram for notifications
Schedule trigger for Wednesdays 8PM SGT
Configure alert thresholds in conditional nodes

Workflow

Schedule Trigger → HTTP Request (Scrape LTA) → Data Processing → Google Sheets (Store) → AI Prediction → Analysis Engine → Conditional Logic → Gmail/Telegram Notification

Workflow Steps

Scraping: Extract COE prices from OneMotoring
Processing: Calculate moving averages, volatility, seasonal trends
Storage: Save to Google Sheets with timestamps
Prediction: AI forecasts next 6 bidding rounds
Analysis: Compare current vs predicted prices, generate recommendation
Notification: Alerts via email/Telegram

Prerequisites

NVIDIA/OpenAI API key, Google account (Sheets), Gmail/Telegram for notifications, basic COE category knowledge

Use Cases

First-time buyers monitoring price dips, fleet managers timing bulk purchases

Customization

Add economic indicators, integrate car loan calculators, track parallel imported car prices

Benefits

Saves hours of manual monitoring, captures 10–15% price dips, provides data-driven purchase timing (potential $5K–$15K savings)

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 - Schedule Trigger - Bi-Weekly COE Scraping

Type / Role: n8n-nodes-base.scheduleTrigger - scheduleTrigger
Config choices: Version 1.2

Block 2 - Scrape COE Data from OneMotoring

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 3 - Extract COE Price Data

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

Block 4 - Store in Google Sheets

Type / Role: n8n-nodes-base.googleSheets - googleSheets
Config choices: Version 4.5

Block 5 - Retrieve Historical COE Data

Type / Role: n8n-nodes-base.googleSheets - googleSheets
Config choices: Version 4.5

Block 6 - Calculate Technical Indicators

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

Block 7 - Prepare AI Prediction Prompt

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 8 - AI Agent - COE Analysis

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.7

Block 9 - Generate Buy Recommendations

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

Block 10 - Format HTML Report

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

Block 11 - Send Email Report

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

Block 12 - Check for Buy Opportunities

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

Block 13 - Send Telegram Alert

Type / Role: n8n-nodes-base.telegram - telegram
Config choices: Version 1.2

Block 14 - Generate Dashboard Summary

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 15 - Sticky Note

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

Block 16 - Sticky Note1

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

Block 17 - Sticky Note2

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

Block 18 - Sticky Note3

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

Block 19 - OpenRouter Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenRouter - lmChatOpenRouter
Config choices: Version 1

Block 20 - Sticky Note4

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

3. Summary Table

Workflow	Automate Singapore COE price analysis & purchase timing with GLM-4.5 AI predictions
Complexity	advanced
Nodes	20
Categories	Market Research, AI Summarization
Author	Cheng Siong Chin
Published	08 Nov 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/10624/10624.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 Market Research workflows AI Summarization workflows

Frequently asked questions

What does Automate Singapore COE price analysis & purchase timing with GLM-4.5 AI predictions do?

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 Market Research, AI Summarization use case.

Cheng Siong Chin

203 workflows

Nodes

n8n-nodes-base.scheduletrigger n8n-nodes-base.httprequest n8n-nodes-base.code n8n-nodes-base.googlesheets n8n-nodes-base.set @n8n/n8n-nodes-langchain.agent n8n-nodes-base.emailsend n8n-nodes-base.if

Complexity

advanced

Published 08 Nov 2025

Likes 0

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Install path: /data/workflows/10624/10624.json

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Automate Singapore COE price analysis & purchase timing with GLM-4.5 AI predictions

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Introduction

How it Works

Setup Steps

Workflow

Workflow Steps

Prerequisites

Use Cases

Customization

Benefits

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Schedule Trigger - Bi-Weekly COE Scraping

Block 2 - Scrape COE Data from OneMotoring

Block 3 - Extract COE Price Data

Block 4 - Store in Google Sheets

Block 5 - Retrieve Historical COE Data

Block 6 - Calculate Technical Indicators

Block 7 - Prepare AI Prediction Prompt

Block 8 - AI Agent - COE Analysis

Block 9 - Generate Buy Recommendations

Block 10 - Format HTML Report

Block 11 - Send Email Report

Block 12 - Check for Buy Opportunities

Block 13 - Send Telegram Alert

Block 14 - Generate Dashboard Summary

Block 15 - Sticky Note

Block 16 - Sticky Note1

Block 17 - Sticky Note2

Block 18 - Sticky Note3

Block 19 - OpenRouter Chat Model

Block 20 - Sticky Note4

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