✨🤖Automate Multi-Platform Social Media Content Creation with AI
Automate Multi-Platform Social Media Content Creation with AI Who is this for? Social Media Managers and Digital Marketers seeking to streamline content production across 7+ platforms (X/Twitter, Instagram, LinkedIn, Facebook, TikTok, Threads, YouTube Shorts) using AI-powered automation. What problem does this solve? Creating platform-optimized content at scale while maintaining brand consistency across multiple channels, reducing manual work by 80% through AI generation and automated publishing. What this workflow does AI Content Generation: Uses GPT-4/Gemini to create platform-specific posts Automatically generates hashtags, CTAs, and emoji placement Supports image/video suggestions and image creation using OpenAI or Pollinations.ai Uses SERP api to search for relavent content Approval Workflow: Sends formatted HTML emails for human review Implements double-approval system with Gmail integration Cross-Platform Publishing: One-click deployment to: Instagram/Facebook (via Graph API) X/Twitter (Official API) LinkedIn (Sales Navigator integration) Setup Credentials: OpenAI API key Google Gemini API Social media platform tokens (X, LinkedIn, Facebook) ImgBB for image hosting Gmail SERP API Telegram Configuration: Update all "your-unique-id" placeholders in API nodes Set email recipients in Gmail nodes Customize AI prompts Customization: Adjust character limits per platform Modify approval thresholds Add/remove social platforms as needed How to customize Content Style: Edit prompt templates in the "Social Media Content Factory" agent node Approval Process: Modify email templates Analytics: Connect to Google Sheets for performance tracking Image Generation: Switch between Pollinations.ai/DALL-E/Midjourney
By Joseph LePage🤖 Build an interactive AI agent with chat interface and multiple tools
How it works This template is a complete, hands-on tutorial that lets you build and interact with your very first AI Agent. Think of an AI Agent as a standard AI chatbot with superpowers. The agent doesn't just talk; it can use tools to perform actions and find information in real-time. This workflow is designed to show you exactly how that works. The Chat Interface (Chat Trigger): This is your window to the agent. It's a fully styled, public-facing chat window where you can have a conversation. The Brain (AI Agent Node): This is the core of the operation. It takes your message, understands your intent, and intelligently decides which "superpower" (or tool) it needs to use to answer your request. The agent's personality and instructions are defined in its extensive system prompt. The Tools (Tool Nodes): These are the agent's superpowers. We've included a variety of useful and fun tools to showcase its capabilities: Get a random joke. Search Wikipedia for a summary of any topic. Calculate a future date. Generate a secure password. Calculate a monthly loan payment. Fetch the latest articles from the n8n blog. The Memory (Memory Node): This gives the agent a short-term memory, allowing it to remember the last few messages in your conversation for better context. When you send a message, the agent's brain analyzes it, picks the right tool for the job, executes it, and then formulates a helpful response based on the tool's output. Set up steps Setup time: ~3 minutes This template is nearly ready to go out of the box. You just need to provide the AI's "brain." Configure Credentials: This workflow requires an API key for an AI model. Make sure you have credentials set up in your n8n instance for either Google AI (Gemini) or OpenAI. Choose Your AI Brain (LLM): By default, the workflow uses the Google Gemini node. If you have Google AI credentials, you're all set! If you prefer to use OpenAI, simply disable the Gemini node and enable the OpenAI node. You only need one active LLM node. Make sure it is connected to the Agent parent node. Explore the Tools: Take a moment to look at the different tool nodes connected to the Your First AI Agent node. This is where the agent gets its abilities! You can add, remove, or modify these to create your own custom agent. Activate and Test! Activate the workflow. Open the public URL for the Example Chat Window node (you can copy it from the node's panel). Start chatting! Try asking it things like: "Tell me a joke." "What is n8n?" "Generate a 16-character password for me." "What are the latest posts on the n8n blog?" "What is the monthly payment for a $300,000 loan at 5% interest over 30 years?"
By Lucas PeyrinInvoice processor & validator with OCR, AI & Google Sheets
📝 Say goodbye to manual invoice checking! This smart workflow automates your entire invoice processing pipeline using AI, OCR, and Google Sheets. --- ⚙️ What This Workflow Does: 📥 1. Reads an invoice PDF — Select a local PDF invoice from your machine. 🔍 2. Extracts raw text using OCR — Converts scanned or digital PDFs into readable text. 🧠 3. AI Agent processes the text — Transforms messy raw text into clean JSON using natural language understanding. 🧱 4. Structures and refines the JSON — Converts AI output into a structured, usable format. 🔄 5. Splits item-wise data — Extracts individual invoice line items with all details. 🆔 6. Generates unique keys — Creates a unique identifier for each item for tracking. 📊 7. Updates Google Sheet — Adds extracted items to your designated sheet automatically. 📂 8. Fetches master item data — Loads your internal product master to validate against. ✅ 9. Validates item name & cost — Compares extracted items with your official records to verify accuracy. 📌 10. Updates results per item — Marks each item as Valid or Invalid in the sheet based on matching. --- 💼 Use Case: Perfect for businesses, freelancers, or operations teams who receive invoices and want to automate validation, detect billing errors, and log everything seamlessly in Google Sheets — all using the power of AI + n8n. > 🔁 Fast. Accurate. Zero manual work. --- OCR AI Invoices Automation.
By Dhrumil PatelScrape every URL on the web without getting blocked by Anti-Bot technologies with Scrappey
Purpose of the workflow Most scraping workflows get blocked by anti-bot technologies. To avoid this, you can use Scrappey to scrape every website you want. How it works: We use Test Data and make a API Call to the Scrappey service. We get the scraped website data back as a result. Setup Steps: Replace YOURAPIKEY in the "Scrappey API Call" node with your Scrappey API Key (Register For Free) Replace the test data with your production data. You can plug in any type of data connector at this point of your workflow.
By BelaAutomate blog creation in brand voice with AI
This n8n template demonstrates a simple approach to using AI to automate the generation of blog content which aligns to your organisation's brand voice and style by using examples of previously published articles. In a way, it's quick and dirty "training" which can get your automated content generation strategy up and running for very little effort and cost whilst you evaluate our AI content pipeline. How it works In this demonstration, the n8n.io blog is used as the source of existing published content and 5 of the latest articles are imported via the HTTP node. The HTML node is extract the article bodies which are then converted to markdown for our LLMs. We use LLM nodes to (1) understand the article structure and writing style and (2) identify the brand voice characteristics used in the posts. These are then used as guidelines in our final LLM node when generating new articles. Finally, a draft is saved to Wordpress for human editors to review or use as starting point for their own articles. How to use Update Step 1 to fetch data from your desired blog or change to fetch existing content in a different way. Update Step 5 to provide your new article instruction. For optimal output, theme topics relevant to your brand. Requirements A source of text-heavy content is required to accurately breakdown the brand voice and article style. Don't have your own? Maybe try your competitors? OpenAI for LLM - though I recommend exploring other models which may give subjectively better results. Wordpress for blog but feel free to use other preferred publishing platforms. Customising this workflow Ideally, you'd want to "train" your agent on material which is similar to your output ie. your social media post may not get the best results from your blog content due to differing formats. Typically, this brand voice extraction exercise should run once and then be cached somewhere for reuse later. This would save on generation time and overall cost of the workflow.
By JimleukAutomate lead qualification with RetellAI Phone Agent, OpenAI GPT & Google Sheet
👉 Build a Phone Agent to qualify outbound leads and schedule inbound calls Who is this for? This workflow is designed for sales teams, call centers, and businesses handling both outbound and inbound lead calls who want to automate their qualification, follow-up, and call documentation process without manual intervention. It’s ideal for teams using Google Sheets, RetellAI, OpenAI, and Gmail as part of their tech stack. --- Real-World Use Cases 🛍 E-commerce – Instantly handle product FAQs and order status checks, 24/7. 🏬 Retail Stores – Share store hours, directions, and return policies without lifting a finger. 🍽 Restaurants – Take reservations or answer menu questions automatically. 💼 Service Providers – Book appointments or consultations while you focus on your craft. 📞 Any Local Business – Deliver friendly, consistent phone support — no live agent required. --- What problem is this workflow solving? Managing lead calls at scale can be chaotic—between scheduling outbound qualification calls, handling inbound appointment requests, and making sure every call is documented and followed up. This workflow automates the entire process, reducing human error and saving time by: ✅ Sending reminders to reps for outbound calls ✅ Automatically placing calls with RetellAI ✅ Handling inbound calls and checking caller details ✅ Generating and emailing call summaries automatically --- What this workflow does This n8n template connects Google Sheets, RetellAI, OpenAI, and Gmail into a seamless workflow: Outbound Lead Qualification Workflow Triggers when a new lead is added to Google Sheets Sends an SMS notification to remind the rep to call in 5 minutes (Optional) Waits 5 minutes Initiates an automated call to the lead via RetellAI Inbound Call Appointment Scheduler Receives inbound calls from RetellAI (via webhook) Checks if the caller’s number exists in Google Sheets Responds to RetellAI with a success or error message Post-Call Workflow Receives post-call data from RetellAI Filters only analyzed calls Updates the lead’s record in Google Sheets Uses OpenAI to generate a call summary Emails the summary to a team inbox or rep --- Setup ✅ You need an active RetellAI API key Sign up for RetellAI, create an agent, and set the webhook URLs (n8n_call for call events). Purchase a Twilio phone number and link it to the agent. ✅ Your Google Sheet must have a column for phone numbers (e.g., "Phone") ✅ Gmail account connected and authorized in n8n ✅ OpenAI API key added to your environment variables or credentials Configure your Google Sheets node with the correct spreadsheet ID and range Add your RetellAI API key to the HTTP request nodes Connect your Gmail account in the Gmail node Add your OpenAI key in the OpenAI node 👉 See full setup guide here: Notion Documentation --- How to customize this workflow to your needs Change SMS content: Edit the text in the “Send SMS reminder” node to match your team’s tone Modify call wait time: Enable and adjust the “Wait 5 minutes” node to any delay you prefer Add CRM integration: Replace or extend the Google Sheets node to update your CRM instead of a spreadsheet Customize call summary prompts: Edit the prompt sent to OpenAI to change the summary style or add extra insights Send email to different recipients: Change the recipient address in the Gmail node or make it dynamic from the lead record --- Need help customizing? Contact me for consulting and support : Linkedin
By Dr. FirasReddit AI digest
This workflow digests mentions of n8n on Reddit that can be sent as an single email or Slack summary each week. We use OpenAI to classify if a specific Reddit post is really about n8n or not, and then the summarise it into a bullet point sentence. How it works Get posts from Reddit that might be about n8n; Filter for the most relevant posts (posted in last 7 days and more than 5 upvotes and is original content); Check if the post is actually about n8n; If it is, categorise with OpenAI. Bear in mind: Workflow only considers first 500 characters of each reddit post. So if n8n is mentioned after this amount, it won't register as being a post about n8n.io. Next steps Improve OpenAI Summary node prompt to return cleaner summaries; Extend to more platforms/sources - e.g. it would be really cool to monitor larger Slack communities in this way; Do some classification on type of user to highlight users likely to be in our ICP; Separate a list of data sources (reddit, twitter, slack, discord etc.), extract messages from there and have them go to a sub workflow for classification and summarisation.
By n8n TeamTurn emails into AI-enhanced tasks in Notion (multi-user support) with Gmail, Airtable and Softr
Purpose This workflow automatically creates Tasks from forwarded Emails, similar to Asana, but better. Emails are processed by AI and converted to rather actionable task. In addition this workflow is build in a way, that multiple users can share this single process by setting up their individual configuration through a user friendly portal (internal tool) instead of the need to manage their own workflows. Demo [](https://youtu.be/7cIvSqJAY0E) How it works One Gmail account is used to process inbound mails from different users. A custom web portal enables users to define “routes”. Thats where the mapping between an automatically generated Gmail Alias and a Notion Database URL, including the personal API Token, happens. Using a Gmail Trigger, new entries are split by the Email Alias, so the corresponding route can be retrieved from the Database connected to the portal. Every Email then gets processed by AI to get generate an actionable task and get a short summary of the original Email as well as some metadata. Based on a predefined structure a new Page is created in the corresponding Notion Database. Finally the Email is marked as “processed” in Gmail. If an error happens, the route gets paused for a possible overflow and the user gets notified by Email. Setup Create a new Google account (alternatively you can use an existing one and set up rules to keep your inbox organized) Create two Labels in Gmail: “Processed” and “Error” Clone this Softr template including the Airtable dataset and publish the application Clone this workflow and choose credentials (Gmail, Airtable) Follow the additional instructions provided within the workflow notes Enable the workflow, so it runs automatically in the background How to use Open published Softr application Register as a new user Create a new route containing the Notion API key and the Notion Database URL Expand the new entry to copy the Email address Save the address as a new contact in your Email provider of choice Forward an Email to it and watch how it gets converted to an actionable task Disclamer Airtable was chosen, so you can setup this template fairly quickly. It is advised to replace the persistence by something you own, like a self hosted SQL server, since we are dealing with sensitive information of multiple users This solution is only meant for building internal tools, unless you own an embed license for n8n.
By MarioRecipe recommendations with Qdrant and Mistral
This n8n workflow demonstrates creating a recipe recommendation chatbot using the Qdrant vector store recommendation API. Use this example to build recommendation features in your AI Agents for your users. How it works For our recipes, we'll use HelloFresh's weekly course and recipes for data. We'll scrape the website for this data. Each recipe is split, vectorised and inserted into a Qdrant Collection using Mistral Embeddings Additionally the whole recipe is stored in a SQLite database for later retrieval. Our AI Agent is setup to recommend recipes from our Qdrant vector store. However, instead of the default similarity search, we'll use the Recommendation API instead. Qdrant's Recommendation API allows you to provide a negative prompt; in our case, the user can specify recipes or ingredients to avoid. The AI Agent is now able to suggest a recipe recommendation better suited for the user and increase customer satisfaction. Requirements Qdrant vector store instance to save the recipes Mistral.ai account for embeddings and LLM agent Customising the workflow This workflow can work for a variety of different audiences. Try different sets of data such as clothes, sports shoes, vehicles or even holidays.
By JimleukStore Notion's Pages as Vector Documents into Supabase with OpenAI
*Workflow updated on 17/06/2024: Added 'Summarize' node to avoid creating a row for each Notion content block in the Supabase table.* Store Notion's Pages as Vector Documents into Supabase This workflow assumes you have a Supabase project with a table that has a vector column. If you don't have it, follow the instructions here: Supabase Langchain Guide Workflow Description This workflow automates the process of storing Notion pages as vector documents in a Supabase database with a vector column. The steps are as follows: Notion Page Added Trigger: Monitors a specified Notion database for newly added pages. You can create a specific Notion database where you copy the pages you want to store in Supabase. Node: Page Added in Notion Database Retrieve Page Content: Fetches all block content from the newly added Notion page. Node: Get Blocks Content Filter Non-Text Content: Excludes blocks of type "image" and "video" to focus on textual content. Node: Filter - Exclude Media Content Summarize Content: Concatenates the Notion blocks content to create a single text for embedding. Node: Summarize - Concatenate Notion's blocks content Store in Supabase: Stores the processed documents and their embeddings into a Supabase table with a vector column. Node: Store Documents in Supabase Generate Embeddings: Utilizes OpenAI's API to generate embeddings for the textual content. Node: Generate Text Embeddings Create Metadata and Load Content: Loads the block content and creates associated metadata, such as page ID and block ID. Node: Load Block Content & Create Metadata Split Content into Chunks: Divides the text into smaller chunks for easier processing and embedding generation. Node: Token Splitter
By DatakiCreate multilingual voice calling bot with GPT-4o, ElevenLabs & Twilio
AI Voice Calling Bot - OpenAI GPT-4o + ElevenLabs + Twilio Integration for Multilingual Appointment Booking & Service Orders Overview Transform your business with an intelligent voice calling bot that handles customer calls automatically in 25+ languages. This N8n workflow integrates OpenAI GPT-4o, ElevenLabs text-to-speech, and Twilio for seamless appointment scheduling, pizza orders, and service bookings. Key Features Multilingual Support: Conversations in English, Spanish, French, German, Italian, Portuguese, Chinese, Japanese, Arabic, and 20+ more languages Natural AI Conversations: GPT-4o powered responses with ElevenLabs realistic voice synthesis Multi-Service Handling: Appointments, orders, and service requests with automatic logging Real-time Processing: Instant speech-to-text and audio response generation Prerequisites N8n instance (self-hosted or cloud) Twilio account with phone number OpenAI API key (GPT-4o access) ElevenLabs API credentials Google Sheets access Cloud storage for audio files Setup Instructions Step 1: Configure Credentials Add API keys for OpenAI, ElevenLabs, Twilio, and Google Sheets in N8n credentials manager. Step 2: Prepare Data Storage Create Google Sheets for call logs and appointments with columns: timestamp, callerid, speechinput, airesponse, language, callsid. Step 3: Configure Twilio Set webhook URL to your N8n endpoint: https://your-n8n-instance.com/webhook/voice-webhook Step 4: Update Sheet IDs Replace placeholder Google Sheet IDs in workflow nodes with your actual sheet IDs. Customization Options Voice Settings: Adjust ElevenLabs multilingual voice models and parameters AI Behavior: Modify system prompts for specific business needs and languages Service Types: Add custom service handling logic Business Hours: Implement language-specific operating hours Monitoring Track call analytics, language preferences, conversion rates, and customer satisfaction across all supported languages through automated Google Sheets logging. Ready for production use with comprehensive error handling and scalability for global businesses.
By ShivaCreate a task in ClickUp
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By tanaypant