It pleases me to be able to announce that I have officially signed my first n8n client as of last Friday! The project is a workflow that will read ticket PDFs from my client's outlook account, extract information from the attachments, organize them by Order number, add a human in the loop to confirm it has been correctly generated, and then automatically create a QuickBooks invoice to my client's account. For this I am charging a project fee as well as a monthly retainer fee, one step closer to financial independence! I got this customer by using my networks and LinkedIn posts to promote my business. I already have 2 other potential customers interested in getting some automations done for them! Couldn't have done it without the advice and guidance of @Ryan Nolan, thank you for pushing me to get started! I will be posting the image of the final workflow! Should be a great one to upload to my Upwork account!

𝗕𝘂𝗶𝗹𝘁 𝗮 𝗥𝗲𝗮𝗹-𝗧𝗶𝗺𝗲 𝗩𝗼𝗶𝗰𝗲 𝗔𝗜 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗔𝗴𝗲𝗻𝘁 𝘂𝘀𝗶𝗻𝗴 𝗻𝟴𝗻 + 𝗢𝗽𝗲𝗻𝗔𝗜 🎙️🧠 I recently built a real-time voice-enabled AI agent that can research any question you ask and respond back in voice, almost instantly. The goal was to move beyond text-only chatbots and build an AI system that feels natural, conversational, and research-driven. 🔹 𝗪𝗵𝗮𝘁 𝘁𝗵𝗶𝘀 𝘃𝗼𝗶𝗰𝗲 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁 𝗱𝗼𝗲𝘀 🎙️ Accepts real-time voice or text input from the frontend 🌐 Sends queries to an n8n Webhook for processing 🤖 Uses an AI Agent to research and understand the question 🧠 Generates a concise, high-quality summary 🔊 Converts the response into voice output ⚡ Returns the answer back to the user in real time 🔹 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 Frontend sends user input → n8n Webhook OpenAI model processes the research query AI Agent refines the output into a short, clear explanation Response is sent back instantly via webhook Voice layer delivers the final answer audibly 🔹 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 Most AI assistants still rely heavily on text. This workflow shows how: Voice-first AI experiences can be built with automation Research-based answers can be delivered instantly AI agents can feel more human, accessible, and interactive Real-time AI systems don’t need heavy backend infrastructure 🔹 𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸 n8n (Webhooks & Workflow Automation) OpenAI (LLM for research & reasoning) LangChain AI Agent Voice Input & Voice Output Layer This project helped me learn more about: Real-time AI workflows Voice-based AI interactions AI agent prompting & summarization Building practical AI assistants with n8n Still learning. Still building. Sharing the journey 🚀 If you’re interested in: ✅ Voice AI Agents ✅ AI Research Assistants ✅ n8n Automation ✅ Real-time AI Systems Let’s connect and learn together 👋 Hire Me:sarfrazdeveloper7@gmail.comand watsnumber 03112817660

🚀 𝗕𝘂𝗶𝗹𝘁 𝗮 𝗥𝗲𝗮𝗹-𝗧𝗶𝗺𝗲 𝗔𝗜 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝘂𝘀𝗶𝗻𝗴 𝗟𝗼𝘃𝗮𝗯𝗹𝗲 + 𝗻𝟴𝗻 Today I built a simple but powerful real-time AI workflow that connects frontend user input directly to an AI agent and returns responses instantly. 🔹 𝗪𝗵𝗮𝘁 𝘁𝗵𝗶𝘀 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝗱𝗼𝗲𝘀: 🌐 Accepts real-time data from the frontend via Webhooks 🤖 Sends user input to an AI Agent for processing ⚡ Generates instant AI-powered responses 🔁 Returns the response back to the frontend in real time 🔹 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 Many applications need fast, live interactions — not delayed responses. This workflow shows how AI + automation can work together seamlessly to power real-time user experiences with minimal backend complexity. 🔹 𝗧𝗲𝗰𝗵 𝘀𝘁𝗮𝗰𝗸 • Lovable (Frontend integration) • n8n (Webhook + AI Agent workflow) • OpenAI (LLM via LangChain) This project helped me understand how accessible AI-driven systems have become — even small experiments can turn into real, usable products. Still learning. Still building. Sharing the journey 🚀 If you’re exploring: ✅ AI agents ✅ Real-time automation ✅ n8n workflows ✅ Building AI-powered products Let’s connect and learn together 👋 Hire Me: sarfrazdeveloper7@gmail.com and 03112817660 hashtag#AI hashtag#n8n hashtag#Automation hashtag#AIWorkflows hashtag#NoCode hashtag#LowCode hashtag#Lovable hashtag#BuildInPublic hashtag#TechJourney

I recently built an AI-powered automation workflow in n8n that acts like a real assistant — not just a chatbot. 🔹 𝗪𝗵𝗮𝘁 𝘁𝗵𝗶𝘀 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁 𝗰𝗮𝗻 𝗱𝗼: 💬 Respond to chat messages intelligently 📇 Check a Google Sheets contact database before taking any action ✉️ Send emails via Gmail only if a valid contact exists 📅 Create Google Calendar events with proper validation 🧠 Maintain short-term context using memory buffering 🤖 Powered by OpenRouter (GPT-4o-mini) via LangChain 🔹 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 Most automations fail because they don’t follow real-world rules. This agent is context-aware, permission-aware, and data-driven — it won’t email or schedule anything unless the contact is verified first. 🔹 𝗧𝗲𝗰𝗵 𝘀𝘁𝗮𝗰𝗸 • n8n (AI Agent + LangChain nodes) • OpenRouter (LLM) • Google Sheets (Contact DB) • Gmail API • Google Calendar API This is a great example of how AI agents can safely automate real business workflows — not just generate text. If you’re exploring: ✅ AI agents ✅ Workflow automation ✅ n8n + LangChain ✅ Business-ready AI systems Let’s connect and share ideas 👋 hashtag#AI hashtag#n8n hashtag#Automation hashtag#LangChain hashtag#OpenRouter hashtag#NoCode hashtag#WorkflowAutomation hashtag#AIEngineering Hire Me: sarfrazdeveloper7@gmal.com and 03112817660

I’ve built an automated LinkedIn content creation workflow that takes an idea all the way to a post-ready draft—seamlessly. ⚙️✨ Using n8n, Google Sheets, AI, and real-time web research, the system now: 🔹 Pulls content ideas automatically 🔹 Researches topics from multiple sources 🔹 Synthesizes insights into a concise LinkedIn post 🔹 Updates content status without manual effort The result? Less time on research and formatting. More time on strategy and building. 🚀 This is what happens when automation meets AI—content creation becomes scalable, consistent, and intentional. If you’re an entrepreneur focused on building systems that work for you, not because of you, this approach is worth exploring. #Automation #AIWorkflows #ContentCreation #n8n #Entrepreneurship