2h • General Discussion 💬
🚀 Build in Public – Day 3
Yesterday I shared my first end-to-end AI automation for the luxury real estate platform.
Today I focused on making the system even smarter by building two new n8n workflows.
🏡 1. AI Property Recommendation Engine
When a new inquiry comes in, the workflow now:
✅ Identifies whether the lead is a buyer
✅ Normalizes buyer preferences
✅ Searches matching properties from Airtable
✅ Uses AI to rank and evaluate the best matches
✅ Returns personalized property recommendations
✅ Saves the recommendation history for future follow-ups
Instead of sending random listings, the AI recommends properties based on what the buyer is actually looking for.
📧 2. AI Recommendation Email Automation
Once recommendations are generated, another workflow automatically:
✅ Retrieves the selected properties
✅ Enriches the property data
✅ Generates a personalized email using AI
✅ Sends the recommendation email through Gmail
✅ Logs every success or failure
✅ Notifies the team in Slack for monitoring
The entire recommendation process is now fully automated—from buyer inquiry to personalized email.
💡 What I learned today
Breaking one large automation into multiple specialized workflows makes everything much easier to maintain, debug, and scale.
Instead of creating one massive workflow, I'm building a system where each workflow has a single responsibility.
This approach is already making development much cleaner.
Still running everything locally with Docker + ngrok, but the next milestone is deploying everything to a VPS so it can run 24/7.
Every day this project gets a little closer to becoming a production-ready AI-powered real estate platform.
I'd love to hear how you structure larger n8n projects. Do you prefer one large workflow or multiple smaller workflows?
#BuildInPublic #AIAutomation #n8n #OpenAI #Automation #RealEstate #AIAgents #WorkflowAutomation #NoCode #DeveloperJourney
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🚀 Build in Public – Day 3
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