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Just wrapped up testing an automated VM monitoring setup using n8n on my local machine.
It SSHs into all 5 local servers every morning at 9 AM PKT and sends a color coded health report (CPU, RAM, Disk, Uptime, Services) to the team via email.
Everything's been verified against live terminal output, Data is accurate.
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Problem: Apps need a secure, organized backend to handle users, orders, products and AI features.
Solution: Built a centralized API Gateway (BFF) in n8n Cloud. One webhook handles validation, API key security and rate limiting, then routes to sub-workflows: Users (register/login), Orders (stock check, totals, status), Products (search), and AI (OpenAI chat, recommendations, review summaries). Supabase is the database.
Tools: n8n, Supabase, OpenAI API, Webhooks
Self-initiated demo project.
I'd test authorization separately for each sub-workflow, especially Orders. Does the gateway pass a verified user identity through, or does the Orders workflow check that the caller can access each order?
Managing product orders and inventory manually takes hours of tedious, repetitive work. Every time a customer inquires or places an order, you have to manually check stock availability, update Google Sheets line by line, send out custom approval emails, and track down confirmation status.
Which one is faster, saves more time, and prevents mistakes?
1 voted
33%
2 voted
67%
3 votes
Closed
Automated Workflow feels more understandable and practical and I like how the design feels modern minimalistic great job 🎉🎉🔥🔥
AI-Powered Email Classification Workflow | n8n Automation
Built an intelligent email automation system using n8n that automatically reads incoming emails, classifies them by department using AI, and forwards them to the right team without any human input.
The workflow connects directly to Gmail and triggers the moment a new email arrives. A JavaScript node extracts the key email details, including sender, subject, body, and date, before passing them to an AI Agent powered by GPT-4o-mini. The AI reads the email content and classifies it into one of six departments: Sales, Customer Service, HR, Finance, Operations, or Other.
A Switch node then routes the email down the correct branch, and a Gmail node automatically forwards it to the right department inbox with a clear label in the subject line.
What it does:
Monitors a Gmail inbox in real time
Extracts and cleans email data automatically
Uses AI to classify emails by department
Routes and forwards emails to the correct team
Fully automated with zero manual sorting required
Result:
Emails that would normally sit unread or require manual sorting now reach the right department within seconds of arriving.
Nice implementation. The production question is what happens to ambiguous emails. I usually add a confidence threshold, an “unclassified” review queue, and retention of the original message so a routing mistake can be corrected without losing context.