Workflow Templates

Send structured logs to BetterStack from any workflow using HTTP Request Who is this for? This workflow is perfect for automation builders, developers, and DevOps teams using n8n who want to send structured log messages to BetterStack Logs. Whether you're monitoring mission-critical workflows or simply want centralized visibility into process execution, this reusable log template makes integration easy. What problem is this workflow solving? Logging failures or events across multiple workflows typically requires duplicated logic. This workflow solves that by acting as a shared log sender, letting you forward consistent log entries from any other workflow using the Execute Workflow node. What this workflow does Accepts level (e.g., "info", "warn", "error") and message fields via Execute Workflow Trigger Sends the structured log to your BetterStack ingestion endpoint via HTTP Request Uses HTTP Header Auth for secure delivery Includes a manual trigger for testing and a sample call to demonstrate usage Comes with clear sticky notes to help you get started Setup Copy your BetterStack Logs ingestion URL. Create a Header Auth credential in n8n with your Authorization: Bearer YOUR_API_KEY. Replace the URL in the HTTP Request node with your BetterStack endpoint. Optionally modify the test data or log levels for custom scenarios. Use Execute Workflow in any of your workflows to send logs here.

AI-Powered Proposal Generator - Sales Automation Workflow Overview This n8n workflow automates the entire proposal generation process using AI, transforming client requirements into professional, customized proposals delivered via email in seconds. Use Case Perfect for agencies, consultants, and sales teams who need to generate high-quality proposals quickly. Instead of spending hours writing proposals manually, this workflow captures client information through a web form and uses GPT-4 to generate contextually relevant, professional proposals. How It Works Form Trigger - Captures client information through a customizable web form OpenAI Integration - Processes form data and generates structured proposal content Google Drive - Creates a copy of your proposal template Google Slides - Populates the template with AI-generated content Gmail - Automatically sends the completed proposal to the client Key Features AI Content Generation**: Uses GPT-4 to create personalized proposal content Professional Templates**: Integrates with Google Slides for polished presentations Automated Delivery**: Sends proposals directly to clients via email Form Integration**: Captures all necessary client data through web forms Customizable Output**: Generates structured proposals with multiple sections Template Sections Generated Proposal title and description Problem summary analysis Three-part solution breakdown Project scope details Milestone timeline with dates Cost integration Requirements n8n instance** (cloud or self-hosted) OpenAI API key** for content generation Google Workspace account** for Slides and Gmail Basic n8n knowledge** for setup and customization Setup Complexity Intermediate - Requires API credentials setup and basic workflow customization Benefits Time Savings**: Reduces proposal creation from hours to minutes Consistency**: Ensures all proposals follow the same professional structure Personalization**: AI analyzes client needs for relevant content Automation**: Eliminates manual copy-paste and formatting work Scalability**: Handle multiple proposal requests simultaneously Customization Options Modify AI prompts for different industries or services Customize Google Slides template design Adjust form fields for specific information needs Personalize email templates and signatures Configure milestone templates for different project types Error Handling Includes basic error handling for API failures and form validation to ensure reliable operation. Security Notes All credentials have been removed from this template. Users must configure their own: OpenAI API credentials Google OAuth2 connections for Slides, Drive, and Gmail Form webhook configuration This workflow demonstrates practical AI integration in business processes and showcases n8n's capabilities for complex automation scenarios.

Who is this for? Content creators, social media managers, digital marketers, and researchers who need to download original TikTok videos without watermarks for analysis, repurposing, or archiving purposes. What problem does this workflow solve? Downloading TikTok videos without watermarks typically requires using questionable third-party websites that may have limitations, ads, or privacy concerns. This workflow provides a clean, automated solution that can be integrated into your own systems and processes. What this workflow does This workflow automates the process of downloading TikTok videos without watermarks in three simple steps: Fetch the TikTok video page by providing the video URL Extract the raw video URL from the page's HTML data Download the original video file without watermark (Optional) Upload to Google Drive with public sharing link generation The workflow uses web scraping techniques to extract the original video source directly from TikTok's own servers, maintaining the highest possible quality without any added watermarks or branding. Setup (Est. time: 5-10 minutes) Before getting started, you'll need: n8n installation The URL of a TikTok you want to download (Optional) Google Drive API enabled in Google Cloud Console with OAuth Client ID and Client Secret credentials if you want to use the upload feature How to customize this workflow to your needs Replace the example TikTok URL with your desired video links Modify the file naming convention for downloaded videos Integrate with other nodes to process videos after downloading Create a webhook to trigger the workflow from external applications Set up a schedule to regularly download videos from specific accounts This workflow can be extended to support various use cases like trending content analysis, competitor research, creating compilation videos, or building a content library for inspiration. It provides a foundation that can be customized to fit into larger automated workflows for content creation and social media management.

Description This template provides a simple and powerful backend for adding speech-to-text capabilities to any application. It creates a dedicated webhook that receives an audio file, transcribes it using OpenAI's gpt-4o-mini model, and returns the clean text. To help you get started immediately, you'll find a complete, ready-to-use HTML code example right inside the workflow in a sticky note. This code creates a functional recording interface you can use for testing or as a foundation for your own design. Who is this for? Developers:** Quickly add a transcription feature to your application by calling this webhook from your existing frontend or backend code. No-code/Low-code builders:** Embed a functional audio recorder and transcription service into your projects by using the example code found inside the workflow. API enthusiasts:** A lean, practical example of how to use n8n to wrap a service like OpenAI into your own secure and scalable API endpoint. What problem does this solve? Provides a ready-made API:** Instantly gives you a secure webhook to handle audio file uploads and transcription processing without any server setup. Decouples frontend from backend:** Your application only needs to know about one simple webhook URL, allowing you to change the backend logic in n8n without touching your app's code. Offers a clear implementation pattern:** The included example code provides a working demonstration of how to send an audio file from a browser and handle the response—a pattern you can replicate in any framework. How it works This solution works by defining a clear API contract between your application (the client) and the n8n workflow (the backend). The client-side technique: Your application's interface records or selects an audio file. It then makes a POST request to the n8n webhook URL, sending the audio file as multipart/form-data. It waits for the response from the webhook, parses the JSON body, and extracts the value of the Transcript key. You can see this exact pattern in action in the example code provided in the workflow's sticky note. The n8n workflow (backend): The Webhook node catches the incoming POST request and grabs the audio file. The HTTP Request node sends this file to the OpenAI API. The Set node isolates the transcript text from the API's response. The Respond to Webhook node sends a clean JSON object ({"Transcript": "your text here..."}) back to your application. Setup Configure the n8n workflow: In the Transcribe with OpenAI node, add your OpenAI API credentials. Activate the workflow to enable the endpoint. Click the "Copy" button on the Webhook node to get your unique Production Webhook URL. Integrate with the frontend: Inside the workflow, find the sticky note labeled "Example Frontend Code Below". Copy the complete HTML from the note below it. ⚠️ Important: In the code you just copied, find the line const WEBHOOK_URL = 'YOUR WEBHOOK URL'; and replace the placeholder with the Production Webhook URL from n8n. Save the code as an HTML file and open it in your browser to test. Taking it further Save transcripts:* Add an *Airtable* or *Google Sheets** node to log every transcript that comes through the workflow. Error handling:** Enhance the workflow to catch potential errors from the OpenAI API and respond with a clear error message. Analyze the transcript:* Add a *Language Model** node after the transcription step to summarize the text, classify its sentiment, or extract key entities before sending the response.

Automating LinkedIn Company URL Verification Use Case This automation verifies that a given LinkedIn URL actually belongs to a company by comparing the website listed on their LinkedIn page against the expected company domain. It is essential for ensuring data accuracy in lead qualification, enrichment, and CRM updates. What This Automation Does Input Parameters Company LinkedIn**: The LinkedIn URL to be verified. Company Domain**: The expected domain (e.g., example.com) for validation. Airtop Profile (connected to LinkedIn)**: Airtop Profile with LinkedIn authentication. Output Confirmation whether the LinkedIn page corresponds to the provided domain. Returns the verified LinkedIn URL if the match is confirmed. How It Works Extracts the website URL from the specified LinkedIn company profile. Compares the extracted URL with the provided company domain. If the domain is contained in the extracted website, the LinkedIn profile is confirmed as valid. Returns the original LinkedIn URL if the match is successful. Setup Requirements Airtop API Key LinkedIn-authenticated Airtop Profile Next Steps Use for LinkedIn Discovery Validation**: Ensure correctness after automated LinkedIn page discovery. Combine with CRM Updates**: Prevent incorrect LinkedIn links from being stored in CRM. Automate in Data Pipelines**: Use this as a validation gate before enrichment or scoring steps.

Who Is This For? This workflow is perfect for content creators, marketers, and business professionals who receive regular newsletters and want to effortlessly convert them into engaging LinkedIn posts. By automating the extraction and repurposing process, you can save time and consistently share thoughtful updates with your network. What Problem Does This Workflow Solve? Manually reading newsletters, extracting the key points, and then formatting that content into professional, engaging LinkedIn posts can be time-consuming and error-prone. This workflow automates those steps by: Filtering Emails:** Uses the Gmail node to process only those emails from a specific sender (e.g., newsletter@example.com). Extracting Content:** Leverages OpenAI to identify and summarize the top news items in your newsletter. Generating Posts:** Crafts concise, insightful LinkedIn posts in a smart, deadpan style with a touch of subtle humor. Publishing:** Posts the generated content directly to LinkedIn. What This Workflow Does Filter Newsletters:** The Gmail node is set up to only handle emails from your chosen sender, ensuring that only relevant newsletters are processed. Extract Key Content:** An OpenAI node analyzes the newsletter text to pull out the most important news items, including headlines and summaries. Split Content:** A Split Out node divides the extracted content so each news item is processed on its own. Generate LinkedIn Posts:** Another OpenAI node takes each news item's details and produces a well-structured LinkedIn post that delivers practical insights and ends with a reflective observation or question. Publish to LinkedIn:** The LinkedIn node publishes the crafted posts directly to your account. Setup Gmail Node: Rename it to “Filter Gmail Newsletter” and configure it to filter emails by your newsletter sender. OpenAI Nodes: Ensure your OpenAI API credentials are set up correctly. Customize the prompt if needed to match your desired tone. LinkedIn Node: Rename it to “Post to LinkedIn” and confirm that your LinkedIn OAuth2 credentials are properly configured. How to Customize OpenAI Prompts:** Adjust the prompts in the OpenAI nodes to fine-tune the post tone and output formatting. Email Filter:** Change the Gmail filter to match the sender of your newsletters. Post Processing:** Optionally, add extra formatting (using Function nodes) to further enhance the readability of the generated LinkedIn posts. This template offers an automated, hands-off solution to transform your newsletter content into engaging LinkedIn updates, keeping your audience informed and inspired with minimal effort.

What it is: In version 1.78, n8n introduced a dedicated node to use the OpenRouter service, which lets you to use a lot of different LLM models and providers and change models on the fly in an agentic workflow. For prior n8n versions, there's a workaround to make OpenRouter accessible, by using the OpenAI node with a OpenRouter-specific BaseURL. This trivial workflow demonstrates this for version before 1.78, so that you can use different LLM model dynamically with the available n8n nodes for OpenAI LLM and OpenAI credentials. What you can do: Use any of the OpenRouter models Have the model even dynamically configured or changing (by some external config, some rule, or some specific chat message) Setup steps: Import the workflow Ensure you have registered and account, purchased some credits and created and API key for OpenRouter.ai Configure the "OpenRouter" credentials with your own credentials, using an OpenAI type credential, but making sure in the credential's config form its "Base URL" is set to https://openrouter.ai/api/v1 so OpenRouter is used instead of OpenAI. Open the "Settings" node and change the model value to any valid model id from the OpenRouter models list or even have the model property set dynamically

This workflow demonstrates how to use the workflowStaticData() function to set any type of variable that will persist within workflow executions. https://docs.n8n.io/code/cookbook/builtin/get-workflow-static-data/ This can be useful for example when working with access tokens that expire after a certain time period. Using staticData we can keep a record of that access token and the expiry time and build our workflow logic around it. Important Static Data only persists across production executions, i.e. triggered by Webhooks or Schedule Triggers (not manual executions!) For this the workflow will have to be activated. Setup configure HTTP Request node to fetch access token from your API (optional) activate workflow test the workflow with the webhook production link you can check the population of the static data in the single executions Feedback If you found this useful or want to report some missing information - I'd be happy to hear from you at ria@n8n.io

What this workflow does This workflow automatically turns new technical video uploads into short, engaging Facebook post drafts—complete with a suggested image—and saves the results to Google Sheets for quick review or publishing. It’s designed to help you repurpose tutorial or demo videos into ready-to-use social content without any manual writing or design effort. What problem is this workflow solving? Manually writing Facebook posts for every new tutorial or product video takes time, especially when you want them to be engaging and consistent. This workflow solves that by using AI to watch for new videos, extract meaningful insights, and write posts and create visuals automatically—saving hours of work. Who is this for? This workflow is ideal for: Content creators uploading tutorial videos Marketing teams working with how-to or product videos Agencies and automation pros building scalable social workflows for clients How it works Trigger: Starts when a new video is uploaded to a specific Google Drive folder. Download & Convert: Downloads the video and converts it to base64. Extract Insights: Dumpling AI analyzes the video and extracts structured insights such as topic, tools mentioned, and key steps. Generate Post: GPT-4o creates a short, friendly Facebook post using those insights, along with an image prompt. Create Visual: Dumpling AI generates an image using the prompt. Save to Sheet: The Facebook post and image URL are saved to a Google Sheet. Setup Create a Google Sheet to store the posts and images. Connect your Google Drive, Google Sheets, Dumpling AI, and OpenAI credentials in n8n. Update the workflow with: Your Google Drive folder ID Your target Google Sheet ID (Optional) Edit the prompt used in the GPT node if you want a different tone, style, or structure for the post. How to customize the workflow Change the platform**: Replace “Facebook” in the prompt with LinkedIn, Instagram, or another platform. Use a different image tool**: You can swap Dumpling AI for any other image generation API (e.g. DALL·E, Midjourney via webhook). Add auto-publishing**: Add a Facebook or social media module to publish the generated post directly instead of just saving to Google Sheets. Tag videos by content type**: Use AI to classify videos into categories and store them in separate tabs or sheets.

This n8n workflow automates the process of saving web articles or links shared in a chat conversation directly into a Notion database, using Google's Gemini AI and Browserless for web scraping. Who is this AI automation template for? It's useful for anyone wanting to reduce manual copy-pasting and organize web findings seamlessly within Notion. A smarter web clipping tool! What this AI automation workflow does Starts when a message is received Uses a Google Gemini AI Agent node to understand the context and manage the subsequent steps. It identifies if a message contains a request to save an article/link. If a URL is detected, it utilizes a tool configured with the Browserless API (via the HTTP Request node) to scrape the content of the web page. Creates a new page in a specified Notion database, populating it with thea summary scraped content, in a specific format, never leaving out any important details. It also saves the original URL, smart tags, publication date, and other metadata extracted by the AI. Posts a confirmation message (e.g., to a Discord channel) indicating whether the article was saved successfully or if an error occurred. Setup Import Workflow: Import this template into your n8n instance. Configure Credentials & Notion Database: Notion Database: Create or designate a Notion database (like the example "Knowledge Database") where articles will be saved. Ensure this database has the following properties (fields): Name (Type: Text) - This will store the article title. URL (Type: URL) - This will store the original article link. Description (Type: Text) - This can store the AI-generated summary. Tags (Type: Multi-select) - Optional, for categorization. Publication Date (Type: Date) - *Optional, store the date the article was published. Ensure the n8n integration has access to this specific database. If you require a different format to the Notion Database, not that you will have to update the Notion tool configuration in this n8n workflow accordingly. Notion Credential: Obtain your Notion API key and add it as a Notion credential in n8n. Select this credential in the save_to_notion tool node. Configure save_to_notion Tool: In the save_to_notion tool node within the workflow, set the 'Database ID' field to the ID of the Notion database you prepared above. Map the workflow data (URL, AI summary, etc.) to the corresponding database properties (URL, Description, etc.). In the blocks section of the notion tool, you can define a custom format for the research page, allowing the AI to fill in the exact details you want extracted from any web page! Google Gemini AI: Obtain your API key from Google AI Studio or Google Cloud Console (if using Vertex AI) and add it as a credential. Select this credential in the "Tools Agent" node. Discord (or other notification service): If using Discord notifications, create a Webhook URL (instructions) or set up a Bot Token. Add the credential in n8n and select it in the discord_notification tool node. Configure the target Channel ID. Browserless/HTTP Request: Cloud: Obtain your API key from Browserless and configure the website_scraper HTTP Request tool node with the correct API endpoint and authentication header. Self-Hosted: Ensure your Browserless Docker container is running and accessible by n8n. Configure the website_scraper HTTP Request tool node with your self-hosted Browserless instance URL. Activate Workflow: Save test and activate the workflow. How to customize this workflow to your needs Change AI Model:** Experiment with different AI models supported by n8n (like OpenAI GPT models or Anthropic Claude) in the Agent node if Gemini 2.5 Pro doesn't fit your needs or budget, keeping in mind potential differences in context window size and processing capabilities for large content. Modify Notion Saving:** Adjust the save_to_notion tool node to map different data fields (e.g., change the summary style by modifying the AI prompt, add specific tags, or alter the page content structure) to your Notion database properties. Adjust Scraping:** Modify the prompt/instructions for the website_scraper tool or change the parameters sent to the Browserless API if you need different data extracted from the web pages. You could also swap Browserless for another scraping service/API accessible via the HTTP Request node.

Use Case In most companies, employees have a lot of great ideas. That was the same for us at n8n. We wanted to make it as easy as possible to allow everyone to add their ideas to some formatted database - it should be somewhere where everyone is all the time and could add a new idea without much extra effort. Since we're using Slack, this seemed to be the perfect place to easily add ideas and collect them in Notion. What this workflow does This workflow waits for a webhook call within Slack, that gets fired when users use the /idea command on a bot that you will create as part of this template. It then checks the command, adds the idea to Notion, and notifies the user about the newly added idea as you can see below: Creating your Slack bot Visit https://api.slack.com/apps, click on New App and choose a name and workspace. Click on OAuth & Permissions and scroll down to Scopes -> Bot token Scopes Add the chat:write scope Head over to Slash Commands and click on Create New Command Use /idea as the command Copy the test URL from the Webhook node into Request URL Add whatever feels best to the description and usage hint Go to Install app and click install Setup Add a Database in Notion with the columns Name and Creator Add your Notion credentials and add the integration to your Notion page. Fill the setup node below Create your Slack app (see other sticky) Click Test workflow and use the /idea comment in Slack Activate the workflow and exchange the Request URL with the production URL from the webhook How to adjust it to your needs You can adjust the table in Notion and for example, add different types of ideas or areas that they impact You might wanna add different templates in Notion to make it easier for users to fill their ideas with details Rename the Slack command as it works best for you How to enhance this workflow At n8n we use this workflow in combination with some others. E.g. we have the following things on top: We additionally have a /bug Slack command that adds a new bug to Linear. Here we're using AI to classify the bugs and move it to the right team. (see this template and this template) We also added other types, like /pain to be less solution-driven To make it easier for everyone to give input, we added a Votes column that allows everyone to vote on ideas/pain points in the list We're also running a workflow once a week that highlights the most popular new ideas and the most active voters (see here)

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow automates the process of scraping product data from e-commerce websites and using it to fine-tune a custom OpenAI GPT model for generating high-quality marketing copy and product descriptions. Main Use Cases Fine-tune OpenAI models with real product data from hundreds of supported e-commerce websites for marketing content generation. Create custom AI models specialized in writing compelling product descriptions across different industries and platforms. Automate the entire pipeline from data collection to model training using Bright Data's extensive scraper library. Generate marketing copy using your custom-trained model via an interactive chat interface. How it works The workflow operates in two main phases: model training and model usage, organized into these stages: Data Collection & Processing Manually triggered to start the fine-tuning process. Uses Bright Data's web scraper to extract product information from any supported e-commerce platform (Amazon, eBay, Shopify stores, Walmart, Target, and hundreds of other websites). Collects product titles, brands, features, descriptions, ratings, and availability status from your chosen platform. Easily customizable to scrape from different websites by simply changing the dataset configuration and product URLs. Training Data Preparation A Code node processes the scraped product data to create training examples in OpenAI's required JSONL format. For each product, generates a complete training example with: System message defining the AI's role as a marketing assistant. User prompt containing specific product details (title, brand, features, original description snippet). Assistant response providing an ideal marketing description template. Compiles all training examples into a single JSONL file ready for OpenAI fine-tuning. Model Fine-Tuning Uploads the training file to OpenAI using the OpenAI File Upload node. Initiates a fine-tuning job via HTTP Request to OpenAI's fine-tuning API using the GPT-4o-mini model as the base. The fine-tuning process runs on OpenAI's servers to create your custom model. Interactive Chat Interface Provides a chat trigger that allows real-time interaction with your fine-tuned model. An AI Agent node connects to your custom-trained OpenAI model. Users can chat with the model to generate product descriptions, marketing copy, or other content based on the training. Custom Model Integration The OpenAI Chat Model node is configured to use your specific fine-tuned model ID. Delivers responses trained on your product data for consistent, high-quality marketing content. Summary Flow: Manual Trigger → Scrape E-commerce Products (Bright Data) → Process & Format Training Data (Code) → Upload Training File (OpenAI) → Start Fine-Tuning Job (HTTP Request) | Parallel: Chat Trigger → AI Agent → Custom Fine-Tuned Model Response Benefits: Fully automated pipeline from raw product data to trained AI model. Works with hundreds of different e-commerce websites through Bright Data's extensive scraper library. Creates specialized models trained on real e-commerce data for authentic marketing copy across various industries. Scalable solution that can be adapted to different product categories, niches, or websites. Interactive chat interface for immediate access to your custom-trained model. Cost-effective fine-tuning using OpenAI's most efficient model (GPT-4o-mini). Easily customizable with different websites, product URLs, training prompts, and model configurations. Setup Requirements: Bright Data API credentials for web scraping (supports hundreds of e-commerce websites). OpenAI API key with fine-tuning access. Replace placeholder credential IDs and model IDs with your actual values. Customize the product URLs list and Bright Data dataset for your specific website and use case. The workflow can be adapted for any e-commerce platform supported by Bright Data's scraping infrastructure.