Block 1 - Weekly Maintenance Analysis
- Type / Role
- n8n-nodes-base.scheduleTrigger - scheduleTrigger
- Config choices
- Version 1.3
How It Works This workflow automates weekly capital expenditure (CAPEX) forecasting for property portfolios using a multi agent AI architecture. It targets property managers, asset managers, and fa...
n8n-nodes-base.scheduletrigger, n8n-nodes-base.googlesheets, n8n-nodes-base.merge, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.splitout, @n8n/n8n-nodes-langchain.agenttool
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Cheng Siong Chin.
Original n8n.io sourceThis workflow automates weekly capital expenditure (CAPEX) forecasting for property portfolios using a multi-agent AI architecture. It targets property managers, asset managers, and facilities finance teams who need data-driven maintenance budgeting without manual spreadsheet analysis. Three Google Sheets sources, namely: maintenance records, property data, and tenant feedback, are merged into a unified dataset. A Main Prediction Agent orchestrates three specialist sub-agents: a CAPEX Prioritizer that ranks spending needs, an ROI Simulator that models return scenarios, and a Quote Requester that fetches vendor estimates. Each agent is backed by dedicated AI models, memory, and tools including a Calculator and Financial Modeling Tool. Structured predictions are parsed, split by category, formatted, saved back to Google Sheets, and pushed to an external budgeting system via POST, delivering a fully automated, auditable CAPEX planning pipeline every week.
Add more data sources (e.g., IoT sensors, ERP exports).
Eliminates manual CAPEX spreadsheet work with autonomous AI forecasting.
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.
Showing the first 24 of 26 workflow blocks. Download the JSON for the full node graph.
| Workflow | Forecast property CAPEX and ROI weekly using Google Sheets and GPT-4o |
|---|---|
| Complexity | advanced |
| Nodes | 26 |
| Categories | Engineering, AI RAG |
| Author | Cheng Siong Chin |
| Published | 13 Apr 2026 |
Use the JSON export at /data/workflows/15027/15027.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
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.
How It Works This workflow automates weekly capital expenditure (CAPEX) forecasting for property portfolios using a multi agent AI architecture. It targets property managers, asset managers, and fa...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
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 Engineering, AI RAG use case.