If you want to learn how to integrate a chatbot into your website, this tutorial is for you. 🚀If you’ve already developed an n8n workflow that reads data from any vector database, this video will guide you through the steps to embed that chatbot into your website. In my example, I’m using WordPress for the integration. 🖥️Please follow along with the video and you’ll have your chatbot running in no time. 🤖✨ 👉 Watch the tutorial here: https://youtu.be/9TulXEDSH3w

🔥 Screening resumes manually is painful. So I built a workflow that: 1️⃣ Reads a candidate’s resume → extracts all skills. 2️⃣ Compares those skills with the job requirements. 3️⃣ Generates a skill gap report → highlighting what’s missing. 4️⃣ Saves everything in Google Sheets. 5️⃣ Instantly emails the recruiter with the results. ⚡ In seconds, you know whether the candidate fits—or what they’re lacking. 👉 Engagement questions for Skool: Would you prefer this to run for every resume automatically, or only for shortlisted candidates? If you had this report, would you share it with candidates too (to help them upskill)? Should I drop the step-by-step workflow build here for the community? Anyone used JSON?

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🌍 The world is moving fast, and the ERA of AI is already here!Your website shouldn’t just exist — it should talk, guide, and convert. 💡 That’s why I’ve added a chatbot(created via N8N) to my own portfolio website — now visitors instantly get all the info they need about my services, without waiting ⏳ Imagine this on your business or portfolio website: 🤖 Instantly answering visitor questions 📈 Highlighting your services 24/7 💼 Driving more leads & sales effortlessly If you’re ready to bring your website to life and keep your business moving forward, I can help set this up for you — whether it’s a portfolio, business, or any other website. ✨ It’s time to level up — because the future belongs to those who automate!

In this video I show a new, faster way to build RAG agents in n8n using the Pinecone Assistant to handle the heavy lifting, no preprocessing pipeline, no manual chunking, no custom embedding flow. You simply drop your documents in and Pinecone takes care of ingestion, splitting, and indexing on the back end. Then we wire it up in n8n to get accurate answers with trustworthy, page-level citations and exact text quotes pulled straight from your knowledge base. If you’re a beginner, this is the easiest path I’ve found to stand up a production-ready RAG agent; if you’re more advanced, it’s a huge time-saver for rapid prototyping. Follow along step-by-step as I connect n8n to Pinecone Assistant, load docs, test grounded responses, and return clean sources you can show to clients or stakeholders, all with a simple, no-code build that you can replicate in minutes.