Workflow Templates

Who is this for? This workflow is perfect for marketers, SEO specialists, product teams, and competitive analysts who want to monitor and summarize public reviews of their competitors. It’s especially helpful for small teams who want fast insights from Google reviews without spending hours manually reading and sorting them. What problem is this workflow solving? Manually going through competitor reviews is time-consuming and repetitive. You risk missing patterns or insights, and it’s hard to share summaries with your team quickly. This workflow automatically scrapes reviews from Google and generates a structured summary of pain points and positive feedback. That way, you can focus on strategy instead of sorting through dozens of reviews. What this workflow does This automation watches for new competitor entries in a Google Sheet, then: Uses Dumpling AI to scrape the latest Google reviews (up to 20) for each business. Splits and cleans the reviews for analysis. Sends them to GPT-4o, which summarizes the most common complaints and praises. Saves the structured result back to the same Google Sheet. You’ll instantly get an overview of what people are saying about any competitor. Setup Google Sheet Setup Create a Google Sheet with at least one column: Business Add names or search queries for the competitors you want to analyze Optional: Add columns for Summary of Reviews and Pain Points Connect Dumpling AI Sign up at Dumpling AI Create an agent using the get-google-reviews endpoint Copy your agent key Use it in the HTTP Request node in this workflow OpenAI Setup Use your API key with GPT-4o access The prompt is already structured to generate grouped summaries from reviews Run the Workflow Trigger it manually or schedule it Make sure your Google Sheets, OpenAI, and Dumpling AI connections are active How to customize this workflow to your needs You can expand the number of reviews retrieved by changing the Dumpling AI agent config Replace Google Sheets with Airtable if you want more robust data views Add more fields like star ratings or review dates in your agent for richer analysis Change the GPT prompt to highlight emotional tone, urgency, or feature mentions 🧠 Node Details Google Sheets Trigger**: Watches for new competitor names HTTP Request (Dumpling AI)**: Scrapes 20 recent reviews from Google SplitOut Node**: Breaks review array into individual items Code Node**: Extracts and combines review text Edit Fields Node**: Structures the review content before GPT GPT-4o Node**: Analyzes and summarizes top pain points and praise Google Sheets Output**: Saves the summary back to the same sheet Dependencies Dumpling AI account and review scraping agent setup OpenAI API key with GPT-4o access Google Sheets OAuth2 credentials

Template for Kids' Story in Arabic The n8n template for creating kids' stories in Arabic offers a versatile platform for storytellers to captivate young audiences with educational and interactive tales. It allows for customization to suit various use cases and can be set up effortlessly. Check this example: https://t.me/st0ries95 Use Cases Educational Platforms: Educational platforms can automate the creation and distribution of educational stories in Arabic for children using this template. By incorporating visual and auditory elements into the storytelling process, educational platforms can enhance learning experiences and engage young learners effectively. Children's Libraries: Children's libraries can utilize this template to curate and share a diverse collection of Arabic stories with young readers. The automated generation of visual content and audio files enhances the storytelling experience, encouraging children to immerse themselves in new worlds and characters through captivating narratives. Language Learning Apps: Language learning apps focused on Arabic can integrate this template to offer culturally rich storytelling experiences for children learning the language. By translating stories into Arabic and supplementing them with visual and auditory components, these apps can facilitate language acquisition in an enjoyable and interactive manner. Configuration Guide for Nodes OpenAI Chat Model Nodes: Functionality**: Allows interaction with the OpenAI GPT-4 Turbo model. Purpose**: Enables communication with advanced chat capabilities. Create a Prompt for DALL-E Node: Customization**: Tailor prompts for generating relevant visual content. Summarization**: Define prompts for visual content generation without text. Generate an Image for the Story Node: Resource Type**: Specifies image as the resource. Prompt Setup**: Configures prompt for textless image creation within the visual content. Generate Audio for the Story Node: Resource Type**: Chooses audio as the resource. Input Definition**: Sets input text for audio file generation. Translate the Story to Arabic Node: Chunking Mode Selection**: Allows advanced chunking mode choice. Summarization Configuration**: Sets method and prompts for story translation into Arabic. Send the Story To Channel Node: Channel ID**: Specifies the channel ID for sending the story text. Text Configuration**: Sets up the text to be sent to the channel. By following these node descriptions, users can effectively configure the n8n template for kids' stories in Arabic, tailoring it to specific use cases for a seamless and engaging storytelling experience for young audiences.

This n8n workflow template allows you to upload a photo to a SharePoint folder using the Microsoft Graph API. The workflow includes steps for authentication, retrieving a photo for testing purposes, setting the destination folder and file name, and uploading the photo. Who is this for? This workflow is ideal for users who need to automate the process of uploading images to SharePoint. It is particularly useful for developers, IT administrators, and anyone managing digital assets within a SharePoint environment. What problem is this workflow solving? / Use Case This workflow addresses the need to automate the uploading of photos to a specific SharePoint folder. By using the Microsoft Graph API, it ensures secure and efficient file management, reducing manual effort and potential errors. What this workflow does Trigger the Workflow: The workflow starts when the user clicks the 'Test workflow' button. Set Configuration: Sensitive data such as TENANT_ID, CLIENT_ID, and CLIENT_SECRET are set. Authentication: Obtains an access token from Microsoft Graph API using the provided credentials. Get Photo: Retrieves a sample photo from a URL for testing purposes. Set Destination: Sets the target folder and file name for the photo upload. Upload Photo: Uploads the photo to the specified SharePoint folder using the Microsoft Graph API. Setup Prerequisites Create an Application User: Follow this guide to create an application user. Set Permissions: Ensure the following permissions are set: Sites.ReadWrite.All: For SharePoint site access. Files.ReadWrite.All: For file upload operations. Authentication For successful authentication, provide the following: TENANT_ID CLIENT_ID CLIENT_SECRET Note: For demonstration purposes, these values are stored in a 'Set' node. In a production environment, ensure the safety of such data using credentials, secure vaults, or other safe methods. Set Destination The destination is defined by two parameters: TARGET_FOLDER: The folder path in SharePoint where the photo will be uploaded. FILE_NAME: The name of the file to be uploaded. Example: Desired file location: https://contoso.sharepoint.com/uploads/pictures from n8n/example.jpg Set the following: TARGET_FOLDER = /uploads/pictures from n8n FILE_NAME = example.jpg How to Customize This Workflow to Your Needs Update Sensitive Data: Replace the placeholder values for TENANT_ID, CLIENT_ID, and CLIENT_SECRET with your actual credentials. Change Destination: Modify the TARGET_FOLDER and FILE_NAME parameters to match your desired upload location and file name. Test with Different Photos: Update the URL in the 'Get Photo' node to test with different images. Sticky Notes Workflow Overview This sticky note explains the overall purpose and dependencies of the workflow. Authentication Details This sticky note provides details on the authentication process and the importance of securing sensitive data. Set Destination Details This sticky note explains how to set the destination folder and file name for the photo upload. By following these guidelines, you can easily customize and use this workflow to automate photo uploads to SharePoint using the Microsoft Graph API.

This workflow template, "Daily Gratitude Reminder Bot for LINE," is designed to help users cultivate a habit of gratitude by sending personalized, AI-generated reminders every evening at 9:00 PM. Using Azure OpenAI , the bot generates varied and engaging messages to prompt users to reflect on the positive aspects of their day. The reminders are then sent directly to users via the LINE messaging platform , ensuring a seamless and impactful experience. Whether you're a developer, counselor, or business owner, this template offers a customizable and scalable solution for promoting mental wellness and fostering a culture of gratitude. profile Qwen2.5-Max 2:56 pm Here’s a polished and detailed description for your "Daily Gratitude Reminder Bot for LINE" template, following the submission guidelines provided. This description is structured to meet all the requirements, including SEO optimization, clarity, and user convenience. Daily Gratitude Reminder Bot for LINE This workflow template, "Daily Gratitude Reminder Bot for LINE," is designed to help users cultivate a habit of gratitude by sending personalized, AI-generated reminders every evening at 9:00 PM. Using Azure OpenAI , the bot generates varied and engaging messages to prompt users to reflect on the positive aspects of their day. The reminders are then sent directly to users via the LINE messaging platform , ensuring a seamless and impactful experience. Whether you're a developer, counselor, or business owner, this template offers a customizable and scalable solution for promoting mental wellness and fostering a culture of gratitude. Who Is This Template For? Developers who want to integrate AI-powered workflows into messaging platforms like LINE. Counselors & Therapists looking to encourage mindfulness and emotional well-being among their clients. Businesses & Organizations focused on employee wellness or customer engagement through positive reinforcement. Educators & Nonprofits seeking tools to promote mental health awareness and self-care practices. What Problem Does This Workflow Solve? Gratitude journaling has been proven to improve mental health, reduce stress, and increase overall happiness. However, many people struggle to maintain the habit due to busy schedules or forgetfulness. This workflow solves that problem by automating daily reminders to reflect on positive experiences, making it easier for users to build and sustain a gratitude practice. What This Workflow Does Scheduled Trigger: The workflow is triggered every evening at 9:00 PM using a schedule node. AI-Powered Message Generation: An Azure OpenAI Chat Model generates a unique and engaging reminder message with a temperature setting of 0.9 to ensure variety and creativity. Message Formatting: The generated message is reformatted to comply with the LINE Push API requirements, ensuring smooth delivery. Push Notification via LINE: The formatted message is sent to the user via the LINE Push API , delivering the reminder directly to their chat. Setup Guide Pre-Requisites Access to an Azure OpenAI account with credentials. A LINE Developers Console account with access to the Push API. Basic knowledge of n8n workflows and JSON formatting. How to Customize This Workflow to Your Needs Change the Time: Adjust the schedule trigger to send reminders at a different time. Modify the Prompt: Edit the AI model's input prompt to generate messages tailored to your audience (e.g., focus on work achievements or personal growth). Expand Recipients: Update the LINE Push API node to send reminders to multiple users or groups. Integrate Additional Features: Add nodes to log user responses or track engagement metrics. Why Use This Template? Promotes Mental Wellness: Encourages users to reflect on positive experiences, improving emotional well-being. Highly Customizable: Easily adapt the workflow to suit different audiences and use cases. Scalable: Send reminders to one user or thousands, making it suitable for both personal and organizational use. AI-Powered Creativity: Avoid repetitive messages by leveraging AI to generate fresh and engaging content.

Convert PDF documents to AI-generated podcasts with Google Gemini and Text-to-Speech Transform any PDF document into an engaging, natural-sounding podcast using Google's Gemini AI and advanced Text-to-Speech technology. This automated workflow extracts text content, generates conversational scripts, and produces high-quality audio files. Who is this for? This workflow template is perfect for content creators, educators, researchers, and marketing professionals who want to repurpose written content into audio format. Ideal for creating podcast episodes, educational content, or making documents more accessible. What problem does this solve? Converting written documents to engaging audio content manually is time-consuming and requires scriptwriting skills. This workflow automates the entire process, turning static PDFs into dynamic, conversational podcasts that sound natural and engaging. What this workflow does Extracts text from uploaded PDF documents Generates podcast script using Google Gemini AI with conversational tone Converts script to speech using Google's advanced TTS with customizable voices Processes audio into properly formatted WAV files Saves final podcast ready for distribution Setup Obtain API credentials: Get Google Gemini API key from AI Studio Configure credentials in n8n as "Google Gemini(PaLM) Api account" Configure voice settings: Choose from available voices: Kore (professional), Aoede (conversational), Laomedeia (energetic) Customize script generation prompts if needed Test the workflow: Upload a sample PDF file Verify audio output quality Adjust voice settings as preferred How to customize this workflow Modify script style:** Edit the prompt in the "Generate Podcast Script" node to change tone, length, or format Change voice:** Update the voice name in "Prepare TTS Request" node Add preprocessing:** Insert text cleaning nodes before script generation Integrate with storage:** Connect to Google Drive, Dropbox, or other storage services Add notifications:** Include Slack or email notifications when podcasts are ready Note: This template requires Google Gemini API access and works best with text-based PDF files under 10MB.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How it works This workflow is a simple AI Agent that connects to Langfuse so send tracing data to help monitor LLM interactions. The main idea is to create a custom LLM model that allows the configuration of callbacks, which are used by langchain to connect applications such Langfuse. This is achieves by using the "langchain code" node: Connects a LLM model sub-node to obtain the model variables (model name, temp and provider) - Creates a generic langchain initChatModel with the model parameters. Return the LLM to be used by the AI Agent node. 📋 Prerequisites Langfuse instance (cloud or self-hosted) with API credentials LLM API key (Gemini, OpenAI, Anthropic, etc.) n8n >= 1.98.0 (required for LangChain code node support in AI Agent) ⚙️ Setup Add these to your n8n instance: Langfuse configuration LANGFUSE_SECRET_KEY=your_secret_key LANGFUSE_PUBLIC_KEY=your_public_key LANGFUSE_BASEURL=https://cloud.langfuse.com # or your self-hosted URL LLM API key (example for Gemini) GOOGLE_API_KEY=your_api_key Alternative: Configure these directly in the LangChain code node if you prefer not to use environment variables Import the workflow JSON Connect your preferred LLM model node Send a test message to verify tracing appears in Langfuse

AI-Powered Product Assistant for E-commerce Transform your online store customer service with an intelligent AI assistant that automatically processes customer inquiries, searches your product database, and provides personalized responses about product availability, pricing, and specifications. Perfect for shoe stores, fashion retailers, and any business with extensive product catalogs - this workflow eliminates manual customer service while increasing response speed and accuracy. How it works Customer sends product inquiry via webhook (Instagram DM, website chat, or messaging app) AI extracts key product details (brand, model, size, color) from natural language text System searches your Google Sheets product database with smart filtering AI generates friendly, personalized response with availability, pricing, and stock information Automatic response sent back to customer with product details or alternatives Screenshots: Customer inquiry: "Do you have Nike Air Max 40 size?" AI response: "Nike Air Max 90, size 40 - in stock 3 pieces, price 120$" Set up steps Prepare your product database - Create Google Sheets with columns: Brand, Model, Size, Color, Price, Quantity Configure AI settings - Connect OpenAI API for natural language processing Set up webhook endpoint - Configure trigger for your messaging platform (Instagram, Telegram, website chat) Test with sample inquiries - Verify AI correctly parses requests and finds products Deploy and monitor - Launch your automated assistant and track performance Time investment: 30-45 minutes setup, works immediately with any product catalog up to 1000+ items.

Built this for a dedicated Slack outage-notifications channel — works well on both desktop and mobile. This is for: IT Administrators & small MSPs looking to streamline M365 alerts from one or multiple mailboxes into a single or specific Slack channels IT Admins who prefer ChatOps over management-by-email What does it do Scans for M365 outage alerts emails (every 1 min) Checks if it impacts a specific user region (if the alert calls it out, countries have to be manually set) Summarizes the incident using OpenAI o4-mini (cheap model - or you can swap for local Ollama) Sends a Slack Block to your outage channel with incident link (can be extended) Deletes the original alert email after successful delivery Credentials Outlook: Create an Outlook credential (OAuth2.0) to point to the mailbox (regular or shared) where M365 service alerts will be received Slack: Create a Slack bot credential with access to the slack channel you want updates posted to OpenAI: Create a OpenAI credential that has access to the GPT-4O-MINI model. Recommend you use projects in OpenAI so that you may set a per-project-budget and not impact other projects. Review this OpenAI documentation for more info on managing Projects in the API portal. Expect this to consume no more than 1-2 cents per month on average. Setup Download & import the workflow Modify the first Outlook block (Check for 365 Service Alert) to use the Outlook credential Modify the OpenAI block's system prompt to call out the countries your users reside in ie. "- Assume the organization has users primarily in the U.S. and Australia. If those regions are affected, state: "Your users may have been affected." Otherwise, add: "No impact expected for your user base."" ← swap U.S. & Australia for desired countries Modify the Slack block (Post outage to Slack) to specify the channel updates will be posted to Sample Slack Output Workflow Diagram

🤖 AI Customer Support Agent with Google Docs Knowledge (Telegram + OpenAI) This no-code workflow turns your Telegram bot into an intelligent, always-on AI support agent that references your business documentation in Google Docs to respond to customer queries—instantly and accurately. Watch full step-by-step video tutorial of the build here: https://youtu.be/Mlv7CjGO7wI 🔧 How it works: Telegram Trigger – Captures incoming messages from users on your Telegram bot Langchain AI Agent (OpenAI GPT) – Interprets the message and uses RAG (retrieval-augmented generation) techniques to craft an answer Google Docs Tool – Connects to and retrieves context from your specified Google Doc (e.g. FAQ, SOPs, policies) Memory Buffer – Keeps track of recent chat history for more human-like conversations Telegram Reply Node – Sends the AI-generated response back to the user 💡 Use Cases: E-commerce customer service SaaS product onboarding Internal helpdesk bot for teams WhatsApp-style support for digital businesses 🧠 What makes this powerful: Supports complex questions by referencing a live Google Doc knowledge base Works in plain conversational language (no buttons or forms needed) Runs 24/7 with zero code Easily extendable to Slack, WhatsApp, or email support 🛠️ Tools used: Telegram Node (trigger + send) Langchain Agent with OpenAI GPT Google Docs Tool Memory Buffer Sticky Notes for easy understanding

This workflow syncs Outlook Calendar events to a Notion database. The Outlook Calendar event must be within a specific time frame (default of within next year) for the workflow to pick up the event. The event subject will be the title of the Notion page, and the event link will be added to the Notion page as a property. Prerequisites Notion account and Notion credentials. Microsoft account and Microsoft credentials. How it works On scheduled intervals, find all Outlook Calendar events within a specific time frame. For each event, check if the event already exists in the Notion database. If it does not exist, create a new page in the Notion database, otherwise update the existing page. Setup This workflow requires that you set up a Notion database or use an existing one with at least the following fields: Title (title) Date (date) Event ID (text) Link (URL)

This workflow creates/updates/deletes a Notion database page when an issue is created/updated/deleted in Jira. Subsequent updates to the issue's title or status in Jira are updated in the Notion database. If you require more fields to send to Notion, this template is easily extendible which will be described in setup. The Notion database will require setup before the workflow can be used. Prerequisites Notion account and Notion credentials. Jira account and Jira credentials. How it works When a new issue is created in Jira, the workflow creates a new page in the Notion database will all the required fields. When the issue's title or status is updated in Jira, the workflow updates the specific Notion database page identified by the "Issue Key" field in Notion. If the status in Jira is set to "Done", the workflow will mark the Notion database page "Done" field as true. When the issue is deleted in Jira, the workflow archives the Notion database page. Setup This workflow requires that you set up a Notion database. To do so, follow the steps below: In Notion, create a new database. Add the following columns to the database: Done (with type "Checkbox") Title (renamed from "Name") Status (with the following options: "To Do", "In Progress", "Done") Link (with type "URL") Issue ID (with type "Number") Issue Key (with type "Text") Add any other fields you require to the database. Your database should look something like this Share the database to n8n. By default, the workflow will fill all the fields provided above, except for any other additional fields you add.

Monitor X for Relevant Posts Use Case This automation monitors X (formerly Twitter) search pages in real time and extracts high-signal posts that match your categories of interest. It’s ideal for community engagement, lead discovery, thought leadership tracking, or competitive analysis. What This Automation Does Given a search URL and a list of categories, it: Logs into X using Airtop Opens the specified search URL Scrolls through the results Extracts up to 10 valid, English-language posts Filters and classifies each post by category (or marks as [NA] if unrelated) Returns the structured results as JSON Input parameters: airtop_profile** — An Airtop browser profile authenticated on X x_url** — X search URL (e.g., https://x.com/search?q=ai agents&f=live) relevant_categories** — Text-based list of categories to classify posts (e.g., "Web automation use cases", "Thought leadership") Output: A JSON array of posts, each with: writer time text url category How It Works Trigger: This workflow is triggered by another workflow (e.g., a community engagement pipeline). Input Setup: Accepts the Airtop profile, search URL, and categories to use for classification. Session: Starts a browser session using the Airtop profile. Window Navigation: Opens the provided X search URL. Extraction: Scrapes up to 10 posts with /status/ in the URL and text in English. Classification: Each post is labeled with a category if relevant, or [NA] otherwise. Filtering: Discards [NA] posts. Output: Returns the list of classified posts. Setup Requirements Airtop profile with an active X login. Airtop API key connected in n8n. List of category definitions to guide post classification (used in prompt). Next Steps Feed into Engagement Workflows**: Pass the results to workflows that reply, retweet, or track posts. Use in Slack Alerts**: Push classified posts into Slack channels for review and reaction. Customize Classifier**: Refine the categorization logic to include sentiment or company mentions. Read more about Monitoring X for Relevant Posts