Most clinics still depend on phone calls and spreadsheets to manage appointments. The result? - Missed slots whenever patients cancel last minute - Staff burning time chasing reminders - No automation for FAQs or patient queries To push the limits of **n8n + Supabase**, I built a **Dental Clinic Appointment Booking AI ChatBot** that runs the entire scheduling pipeline: 👤 Patient verification & registration 📅 Booking, rescheduling, and cancellations 🔔 Automated daily reminders + instant staff alerts 💬 FAQ handling via a RAG-powered knowledge base 💾 Calendar + database synchronization The best part: this workflow isn’t locked to dental clinics. Its modular design makes it adaptable to other industries: - 💇 **Salons** – stylist selection for hair, nail, or makeup appointments - 💆 **Spas** – wellness packages and therapist scheduling - 🐾 **Veterinary Clinics** – pet profiles + vaccination reminders - 🧘 **Fitness Studios** – class scheduling + attendance tracking - 🚗 **Auto Service Centers** – service bookings + maintenance reminders 🎥 I’ve documented the full workflow with screenshots and demo recordings so you can see it in action: 👉 Repo + Demos

Want to dive deeper into this build and discuss how to enhance it? Join AIS+ In this video, I build the ultimate AI personal assistant using a team of AI agents! A centralized assistant manages four specialized sub-agents, each handling a specific area—making the system more efficient and scalable. This approach ensures that no single agent gets overwhelmed with tasks and tools, leading to better automation and smarter decision-making. All of this is built in n8n using no code! Watch to see how it works. IMPORTANT: Import the workflows by opening up a new workflow, click the three dots in the top right, and select "Import from file". You must make sure when you are setting up the workflows as a tool for the main agent that you are choosing the correct workflow within your n8n environment.

Hello everyone! Just finished building a modular resume screening workflow using n8n. It’s designed to help recruiters automate the first layer of candidate evaluation—efficiently and intelligently. 🧩 How It Works (Step-by-Step) 1. 📥 Form Submission Trigger Candidates submit their name, email, and resume file (PDF or DOCX) via a form. 2. 📄 Resume Text Extraction The uploaded file is processed to extract clean, structured text—regardless of format. 3. 🧠 AI-Powered Analysis The resume is passed to an AI agent that evaluates the candidate against the job description. The agent performs a structured review: - Strengths - Weaknesses - Risk Factor (e.g. skill gaps, experience mismatch) - Reward Factor (e.g. unique value, standout traits) - Overall Fit Rating 4.✅ Decision Logic Based on the analysis: 🎯 Use Cases - Recruiters: Automate initial resume screening with consistent, explainable logic - Startups: Save time on hiring without compromising quality - HR Teams: Build scalable, agent-driven screening systems - AI Builders: Explore multi-agent orchestration in real-world workflows 🛠️ Built With: - n8n - Google Gemini (LLM for analysis) - Gmail (email notifications) - Telegram Bot (real-time alerts) - Sheet/database storage (for passed candidates) My end goal is to get hired as an AI automation specialist, so I’ll be sharing more of the workflows I’ve built until that happens. Huge thanks to Nate for sparking these ideas, his insights have been a game-changer in how I approach automation.

In today’s video, I sit down once again with Brett, the winner of our September AIS+ Hackathon, who took home the $5,000 first-place prize for his incredible sales automation system. We dive deep into a live demo of his system in action, showing how it streamlines lead management, follow-ups, and conversions, and then break down the n8n workflow that powers the entire build behind the scenes. You’ll get a front-row seat to see how Brett engineered this system from scratch, how each component works together, and how you can apply the same principles to your own automations. If you want to participate in future hackathons, win cash prizes, and even get featured on this channel, then join AIS+, our private community for builders who want to go deeper into AI agents and automation systems. As a Plus member, you’ll also be able to download Brett’s full template and explore his workflow for yourself.

This project started with a client’s request for short videos, and it pushed me to explore deeper, turning it into a full UGC‑style content pipeline: 💬 One Telegram message → kicks off the workflow ✍️ AI generates 7 influencer scripts (one per day) 🖼️ Images prepped + converted for video 🎬 Videos generated via API with captions + hashtags 📁 Everything stored in Drive + logged in Sheets 🧠 Error handling + spam protection baked in What surprised me most was how much quality matters here, pacing, captions, and reliability are just as important as the automation itself. This kind of setup feels super relevant for: - Agencies managing multiple influencer accounts - Solo creators who want consistent content without editing - Brands running automated campaigns - Marketing teams testing messaging at scale - Anyone experimenting with UGC‑style content at scale I’ve documented the workflow in my GitHub repository, feel free to visit: https://github.com/Orekidesu/n8n-workflow-project-lists/tree/d0ef7a8043ce2b4e9d11d34c6667d06616c20128/AI%20Influencer%20Video%20Generator 👉 Has anyone else here been experimenting with influencer/UGC pipelines? Would love to swap notes and see how you’re approaching it.