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Developed an AI-powered email support workflow that automatically monitors an inbox, classifies incoming emails by intent, generates context-aware responses, and routes messages based on priority.
The automation reduces manual email handling by identifying support requests, sales inquiries, spam, and general questions while maintaining a structured workflow for customer support teams.
The network for creativity
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Connect with clients, get discovered, and run your business 100% commission-free
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Obviously automated
Built an AI agent that handles access requests end-to-end inside Slack — reviewing, approving, and notifying automatically.
Manually tracking who requested access to what (and following up over email) was slow and easy to lose track of. I built a Make.com scenario that:
Watches Slack for new access request messages
Shows a typing indicator while the AI Agent processes the request
The AI Agent (Access Request Agent) evaluates the request and decides the next action
Depending on the decision, it logs the request in Google Sheets, sends an email via Gmail, or replies in Slack
Sends a confirmation message back to the requester in Slack
Result: Access requests are now reviewed and routed automatically — no manual follow-up, and every request is logged and answered consistently.
Tools: Slack, Make AI Agents, Google Sheets, Gmail (built on Make.com)
Lost 2 days building a complex n8n workflow. Here's what I learned.✌️
The project: A 12-node AI Receptionist automation for a luxury resort in Bangladesh. Multi-channel (WhatsApp, Telegram, Voice), 9 Google Sheets, Gemini API, payment automation, customer CRM.
What went wrong: Added a new voice integration node. Accidentally deleted the entire workflow.
Why it happened:
No JSON exports after milestones
No version control (Git)
Testing changes LIVE on production workflow
No documentation
Building locally with zero redundancy
The fix (now implemented):
✅ JSON backups after every 2-3 nodes
✅ GitHub versioning
✅ Clone workflows for testing
✅ Modular design
✅ Complete documentation
For automation professionals: You're not just builders—you're engineers.
Treat workflows like software:
Documentation
Version control
Backup strategy
Modular testing
Client delays = lost revenue + credibility damage.
Make the systems bulletproof.
How do you prevent data loss in your automation builds? 👇
#n8n #Automation #WorkflowAutomation #NoCode #LessonsLearned #make #AIAutomation #DataAnalyst #MachineLearning
I'd try restoring one of those JSON backups into a cloned workflow before the next handoff. That way you know it can actually get you running again.