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

Yesterday I shared the luxury real estate website I've been building. Today I completed the first end-to-end AI automation for the platform. Now, whenever someone submits the inquiry form, the system automatically: ✅ Receives the lead from the website ✅ Uses AI to qualify the lead ✅ Determines whether the inquiry is from a Buyer or Seller ✅ Generates AI insights and recommendations ✅ Stores everything in an Airtable CRM ✅ Continues the automation workflow for follow-ups One thing I learned today is about deployment. Right now, my n8n instance is running locally inside Docker Desktop and exposed using ngrok. It works perfectly for development, but if I shut down my laptop, the workflow stops because the webhook is no longer available. My next step is deploying n8n to a VPS or n8n Cloud so the automation can run 24/7 with a permanent webhook URL. You can explore the website here: https://gilded-horizon-properties.lovable.app I'd love your feedback on both the website and the automation architecture. If you've deployed n8n in production, what hosting setup has worked best for you? #AI #AIAutomation #n8n #OpenAI #Docker #BuildInPublic #RealEstate #CRM #Automation #AIAgents

Today I completed a modern real estate website as part of my journey in building AI-powered business solutions. My focus was on creating a clean, premium user experience with intuitive navigation, smooth interactions, and a responsive design that feels polished across devices. What I focused on: 🏡 Modern and premium UI/UX ✨ Smooth animations and interactions 📱 Responsive design 🔍 Property browsing experience 🎨 Clean and minimal interface ⚡ Performance-focused layout This project reminded me that a great website is more than just good design—it's the first impression a business makes. A well-designed user experience builds trust before a conversation even begins. This is just the first step. My goal is to continue building projects that combine modern web experiences with AI and automation to solve real business problems. 🌐 Live Demo: https://gilded-horizon-properties.lovable.app I'd genuinely appreciate your feedback. 💬 If you were reviewing this website, what would you improve first—UI, UX, performance, or features? #BuildInPublic #WebDevelopment #UIDesign #UXDesign #FrontendDevelopment #RealEstate #AIAutomation #ArtificialIntelligence #LearningInPublic #ForgewireAI

Hey everyone! I'm Zain, based in Birmingham UK. I run an AI receptionist service called Never Miss The Call. I've just built an AI receptionist called Lexi using Vapi for a sports therapy clinic — she's fully live and taking calls through Vonage. The one thing I'm stuck on is the Make.com SMS automation. When a call ends, I want Make.com to send the business owner a clean summary SMS with the caller's name, service requested, preferred day and time, and contact number. Has anyone done this before or does anyone have any video suggestions that show how to set this up? Any help would be massively appreciated! 🙏

Today I finished building an AI-powered real estate lead management system using n8n + OpenAI + Airtable. The goal was to automate the journey from a website inquiry to a qualified lead with minimal manual work. Current features: ✅ Website lead capture ✅ AI-powered lead analysis & summaries ✅ Buyer/Seller classification ✅ Lead scoring & quality (Hot / Warm / Cold) ✅ Automated email follow-ups ✅ AI-generated SMS follow-ups ✅ Consultation booking ✅ Airtable CRM for lead, appointment & follow-up management ✅ Google Sheets integration ✅ Error handling throughout the workflow I've attached a few screenshots of the CRM to show how the data is organized after the automation runs. Still improving the system, but it's been a great project for learning how to combine AI with real business workflows. 💬 If you were building this, what feature would you add next? I'd genuinely appreciate any feedback or suggestions. #BuildInPublic #n8n #OpenAI #Automation #AIAgents #Airtable #CRM #WorkflowAutomation #RealEstate #ArtificialIntelligence