Workflow Templates

Auto-generate product comparison pages that help users buy faster This workflow creates detailed "X vs Y" product comparison pages designed to help readers make faster, more confident purchase decisions — all with zero manual writing. How it works Triggered manually or via Google Sheets row Takes two product names as input (e.g. “Notion vs Evernote”) Uses AI to generate: ✅ A compelling title and meta description 📝 Clear feature-by-feature comparison 🤝 Use-case-based recommendations 💬 FAQ section tailored to user pain points Saves each section into a Google Sheet for review or publishing Final output can be exported to your CMS or website builder (like Dorik, Webflow, etc.) Set up steps You’ll need OpenAI and Google Sheets credentials Takes 10–15 minutes to plug in your keys and connect the sheet Adjust prompts to match your brand tone or SEO goals 📝 You can easily expand this to generate pricing tables, testimonials, or even localized versions using the same structure. Ideal for SaaS companies, affiliate marketers, or content teams who want to scale up comparison content — without spending hours writing.

Overview Transform your Bitrix24 Open Line channels with an intelligent chatbot that leverages Retrieval-Augmented Generation (RAG) technology to provide accurate, document-based responses to customer inquiries in real-time. Use Case This workflow is designed for organizations that want to enhance their customer support capabilities in Bitrix24 by providing automated, knowledge-based responses to customer inquiries. It's particularly useful for: Customer service teams handling repetitive questions Support departments with extensive documentation Sales teams needing quick access to product information Organizations looking to provide 24/7 customer support What This Workflow Does Smart Document Processing Automatically processes uploaded PDF documents Splits documents into manageable chunks Generates vector embeddings for semantic understanding Indexes content for efficient retrieval AI-Powered Responses Utilizes Google Gemini AI to generate natural language responses Constructs answers based on relevant document content Maintains conversation context for coherent interactions Provides fallback responses when information is not available Vector Database Integration Stores document embeddings in Qdrant vector database Enables semantic search beyond simple keyword matching Retrieves the most relevant information for each query Maintains a persistent knowledge base that grows over time Webhook Handler Processes incoming messages from Bitrix24 Open Line channels Handles authentication and security validation Routes different types of events to appropriate handlers Manages session and conversation state Event Routing Intelligently routes different event types: ONIMBOTMESSAGEADD: Processes new user messages ONIMBOTJOINCHAT: Handles bot joining a conversation ONAPPINSTALL: Manages application installation ONIMBOTDELETE: Handles bot deletion Document Management Organizes processed documents in designated folders Tracks document processing status Moves indexed documents to appropriate locations Maintains document metadata for reference Interactive Menu Provides menu-based options for common user requests Customizable menu items and responses Easy navigation for users seeking specific information Fallback to operator option when needed Technical Architecture Components Webhook Handler: Receives and validates incoming requests from Bitrix24 Credential Manager: Securely manages authentication tokens and API keys Event Router: Directs events to appropriate processing functions Document Processor: Handles document loading, chunking, and embedding Vector Store: Qdrant database for storing and retrieving document embeddings Retrieval System: Searches for relevant document chunks based on user queries LLM Integration: Google Gemini model for generating natural language responses Response Manager: Formats and sends responses back to Bitrix24 Integration Points Bitrix24 API**: For bot registration, message handling, and user interaction Ollama API**: For generating document embeddings Qdrant API**: For vector storage and retrieval Google Gemini API**: For AI-powered response generation Setup Instructions Prerequisites Active Bitrix24 account with Open Line channels enabled Access to n8n workflow system Ollama API credentials Qdrant vector database access Google Gemini API key Configuration Steps Initial Setup Import the workflow into your n8n instance Configure credentials for all services Set up webhook endpoints Bitrix24 Configuration Create a new Bitrix24 application Configure webhook URLs Set appropriate permissions Install the application to your Bitrix24 account Document Storage Create a designated folder in Bitrix24 for knowledge base documents Configure folder paths in the workflow settings Upload initial documents to be processed Bot Configuration Customize bot name, avatar, and description Configure welcome messages and menu options Set up fallback responses Testing Verify successful installation Test document processing pipeline Send test queries to evaluate response qu

Automate Audio Transcription, AI Summarization, and Google Drive Storage Who is this for? Content Teams, Researchers, and Administrators who need to automatically process voice memos, meeting recordings, or interview audio into structured, searchable documents. What problem does this solve? Eliminates manual transcription work by automatically converting audio files into organized text documents with AI analysis, while maintaining human oversight through approval workflows. What this workflow does Smart Audio Processing: Triggers when new .m4a files appear in Google Drive Uses OpenAI's Whisper for accurate transcription Implements dual-format reporting (JSON + Markdown) Human Oversight (optional): Requires email approval before processing 45-minute response window with escalation options AI-Powered Analysis: Generates structured JSON reports with: Key points & action items Sentiment analysis Technical terminology glossary Creates Markdown versions for easy reading Document Management: Stores raw transcripts + reports in Google Drive Automatic file naming with timestamps Sends completion alerts via Email/Telegram Workflow visualization showing audio file processing path Setup Credentials Needed: Google Drive API access OpenAI API key (GPT-4o-mini) Gmail & Telegram integrations Configuration: Set your Google Drive folder ID in 3 nodes Update email addresses in Gmail nodes Customize approval timeout in "Gmail User for Approval" Customization Points: File extension filters (.m4a) AI report templates and prompts Notification channels (Email/Telegram) How to customize Approval Process**: Add SMS/Teams notifications via additional nodes File Types**: Modify filter node for .mp3/.wav support Analysis Depth**: Adjust GPT-4 prompts in "Summarize to JSON" nodes Storage**: Connect to Notion/Airtable instead of Google Drive

🎥 Analyze YouTube Video for Summaries, Transcripts & Content + Google Gemini Who is this for? This workflow is ideal for content creators, video marketers, and research professionals who need to extract actionable insights, detailed transcripts, or metadata from YouTube videos efficiently. It is particularly useful for those leveraging AI tools to analyze video content and optimize audience engagement. What problem does this workflow solve? / Use case Analyzing video content manually can be time-consuming and prone to errors. This workflow automates the process by extracting key metadata, generating summaries, and providing structured transcripts tailored to specific use cases. It helps users save time and ensures accurate data extraction for content optimization. What this workflow does Extracts audience-specific metadata (e.g., video type, tone, key topics, engagement drivers). Generates customized outputs based on six prompt types: Default: Actionable insights and strategies. Transcribe: Verbatim transcription. Timestamps: Timestamped dialogue. Summary: Concise bullet-point summary. Scene: Visual descriptions of settings and techniques. Clips: High-engagement video segments with timestamps. Saves extracted data as a text file in Google Drive. Sends analyzed outputs via Gmail or provides them in a completion form. Setup Configure API keys: Add your Google API key as an environment variable. Input requirements: Provide the YouTube video ID (e.g., wBuULAoJxok). Select a prompt type from the dropdown menu. Connect credentials: Set up Google Drive and Gmail integrations in n8n. How to customize this workflow to your needs Modify the metadata prompt to extract additional fields relevant to your use case. Adjust the output format for summaries or transcripts based on your preferences (e.g., structured bullets or plain text). Add nodes to integrate with other platforms like Slack or Notion for further collaboration. Example Usage Input: YouTube video ID (wBuULAoJxok) and prompt type (summary). Output: A concise summary highlighting actionable insights, tools, and resources mentioned in the video.

🎨 AI Graphic Design Team - Generate and Review AI Images with Ideogram and OpenAI Description Who is this for? This workflow is perfect for graphic designers, creative agencies, marketing teams, or freelancers who regularly use AI-generated images in their projects. It's specifically beneficial for teams that want to automate the generation, review, and management of AI-created graphics efficiently. What problem does this workflow solve? Design teams often face time-consuming manual reviews and inconsistent quality checks for AI-generated images. This workflow addresses these challenges by automating image generation and introducing a systematic, AI-driven vetting process. This ensures only high-quality, relevant images reach your team's assets, saving valuable time and enhancing workflow efficiency. What this workflow does AI Image Generation:** Integrates Ideogram via HTTP Request to automatically create AI-generated images based on creative briefs. Automated Image Review:** Uses OpenAI to automatically evaluate and approve images, ensuring they meet your predefined quality standards. Efficient Asset Management:** Automatically creates structured Google Drive folders and compiles key metadata (including creation dates, prompts, and image links) into a CSV file and Google Sheet. Immediate Email Notifications:** Delivers a setup confirmation and provides easy access to Google Drive folders and assets via automated email notifications. Final Approved Images:** Outputs vetted, ready-to-use images for your creative projects, removing the burden of manual reviews. Setup Initial Email Configuration Update your email details in both the "Setup Gmail" node and the "Gmail" notification node. Run the initial setup workflow to automatically create the Google Drive folders "Graphic_Design_Team" and "Image_Generations," and upload your CSV file (n8n-Graphic_Design_Team.csv). Review Email & Set Up Google Sheets Check your inbox for an automated email containing folder IDs and direct links. Create and set up a Google Sheet by importing the provided CSV data from your email. Update Workflow Nodes Select your newly created Google Sheet in both Google Sheets nodes. Update your Creative Brief node with the Google Drive folder IDs provided in the email. Run Workflow for AI Image Generation & Review Execute the workflow. Your generated images will be automatically vetted, organized, and ready for creative use. How to Customize This Workflow Tailor Image Generation Prompts:** Adjust prompts and settings in the Ideogram HTTP Request node to better fit your project's creative requirements. Set Quality Standards:** Modify the criteria used by the OpenAI node to reflect your specific standards and preferences for image approval. Customize Asset Organization:** Adapt Google Drive folder structures, CSV headers, or Google Sheets integrations to match your team's organizational preferences. Dependencies & Requirements Nodes Used:** HTTP Request (Ideogram API integration) OpenAI (Image review and quality assessment) Gmail (Automated notifications) Google Drive (File and asset management) Google Sheets (Metadata organization) Credentials:** Ensure Gmail, Google Drive, Google Sheets, and OpenAI credentials are properly configured in your n8n account. No custom or community nodes are needed. Final Outcome Upon completion, your workflow efficiently provides vetted, high-quality AI-generated images, organized in Google Drive and accessible via easy-to-use metadata in Google Sheets, drastically reducing manual intervention and accelerating your creative processes.

✨ Overview This workflow allows candidates to schedule interviews through a conversational AI assistant. It integrates with your Google Calendar to check for existing events and generates a list of available 30-minute weekday slots between 9 AM and 5 PM Eastern Time. Once the candidate selects a suitable time and provides their contact information, the AI bot automatically books the meeting on your calendar and confirms the appointment. ⚡ Prerequisites To use this workflow, you need an OpenAI account with access to the GPT-4o model, a Google account with a calendar that can be accessed through the Google Calendar API, and an active instance of n8n—either self-hosted or via n8n cloud. Within n8n, you must have two credential configurations ready: one for Google Calendar using OAuth2 authentication, and another for your OpenAI API key. 🔐 API Credentials Setup For Google Calendar, go to the Google Cloud Console and create a new project. Enable the Google Calendar API, then create OAuth2 credentials by selecting “Web Application” as the application type. Add http://localhost:5678/rest/oauth2-credential/callback as the redirect URI if using local n8n. After that, go to n8n, navigate to the Credentials section, and create a new Google Calendar OAuth2 credential using your account. For OpenAI, visit platform.openai.com to retrieve your API key. Then go to the n8n Credentials page, create a new credential for OpenAI, paste your key, and name it for reference. 🔧 How to Make This Workflow Yours To customize the workflow for your use, start by replacing all instances of the calendar email rbreen.ynteractive@gmail.com with your own Google Calendar email. This email is referenced in multiple places, including Google Calendar nodes and the ToolWorkflow JSON for the node named "Run Get Availability." Also update any instances where the Google Calendar credential is labeled as Google Calendar account to match your own credential name within n8n. Do the same for the OpenAI credential label, replacing OpenAi account with the name of your own credential. Next, go to the node labeled Candidate Chat and copy the webhook URL. This is the public chat interface where candidates will engage with the bot—share this URL with them through email, your website, or anywhere you want to allow access. Optionally, you can also tweak the system message in the Interview Scheduler node to modify the tone, language, or logic used during conversations. If you want to add branding, update the title, subtitle, and inputPlaceholder in the Candidate Chat node, and consider modifying the final confirmation message in Final Response to User to reflect your brand voice. You can also update the business rules such as time zone, working hours, or default duration by editing the logic in the Generate 30 Minute Timeslots code node. 🧩 Workflow Explanation This workflow begins with the Candidate Chat node, which triggers when a user visits the public chat URL. The Interview Scheduler node acts as an AI agent, guiding the user through providing their email, phone number, and preferred interview time. It checks availability using the Run Get Availability tool, which in turn reads your calendar and compares it with generated free time slots from the Generate 30 Minute Timeslots node. The check day names tool helps the AI interpret natural language date expressions like “next Tuesday.” The schedule is only populated with 30-minute weekday slots from 9 AM to 5 PM Eastern Time, and no events are scheduled if they overlap with existing ones. When a suitable time is confirmed, the AI formats the result into structured JSON, creates an event on your Google Calendar, and sends a confirmation back to the user with all relevant meeting details. 🚀 Deployment Steps To deploy the interview scheduler, import the provided workflow JSON into your n8n instance. Update the Google Calendar email, OpenAI and Google credential labels, system prompts, and branding as needed. Test the connections to ensure the API credentials are working correctly. Once everything is configured, copy and share the public chat URL from the Candidate Chat node. When candidates engage with the chat, the workflow will walk them through the interview booking process, check your availability, and finalize the booking automatically. 💡 Additional Tips By default, the workflow avoids scheduling interviews on weekends and outside of 9–5 EST. Each interview lasts exactly 30 minutes, and overlapping with existing events is prevented. The assistant does not reveal details about other meetings. You can customize every part of this workflow to fit your use case, including subworkflows like Get Availability and check day names, or even white-label it for client use. This workflow is ready to become your AI-powered interview scheduling assistant. 🤝 Connect with Me Description I’m Robert Breen, founder of Ynteractive — a consulting firm that helps businesses automate operations using n8n, AI agents, and custom workflows. I’ve helped clients build everything from intelligent chatbots to complex sales automations, and I’m always excited to collaborate or support new projects. If you found this workflow helpful or want to talk through an idea, I’d love to hear from you. Links 🌐 Website: https://www.ynteractive.com 📺 YouTube: @ynteractivetraining 💼 LinkedIn: https://www.linkedin.com/in/robert-breen 📬 Email: rbreen@ynteractive.com

⚠️ DISCLAIMER: This workflow uses the HDW LinkedIn community node, which is only available on self-hosted n8n instances. It will not work on n8n.cloud. Overview This workflow automates the entire LinkedIn lead generation process from finding prospects that match your Ideal Customer Profile (ICP) to sending personalized messages. It uses AI to analyze lead data, score potential clients, and prioritize your outreach efforts. Key Features AI-Driven Lead Generation**: Convert ICP descriptions into LinkedIn search parameters Comprehensive Data Enrichment**: Analyze company websites, LinkedIn posts, and news Intelligent Lead Scoring**: Prioritize leads based on AI analysis of intent signals Automated Outreach**: Connect with prospects and send personalized messages Requirements Self-hosted n8n instance with the HDW LinkedIn community node installed OpenAI API access (for GPT-4o) Google Sheets access HDW API key (available at app.horizondatawave.ai) LinkedIn account Setup Instructions 1. Install Required Nodes Ensure the HDW LinkedIn community node is installed on your n8n instance Command: npm install n8n-nodes-hdw (or use this instruction) 2. Configure Credentials OpenAI**: Add your OpenAI API key Google Sheets**: Set up Google account access HDW LinkedIn**: Configure your API key from horizondatawave.ai 3. Set Up Google Sheet Create a new Google Sheet with the following columns (or copy template): Name, URN, URL, Headline, Location, Current company, Industry, etc. The workflow will populate these columns automatically 4. Customize Your ICP Use chat to provide the AI Agent with your Ideal Customer Profile Example: "Target marketing directors at SaaS companies with 50-200 employees" 5. Adjust Scoring Criteria Modify the lead scoring prompt in the "Company Score Analysis" node to match your specific product/service Tune the evaluation criteria based on your unique business needs 6. Configure Message Templates Update the HDW LinkedIn Send Message node with your custom message How It Works ICP Translation: AI converts your ICP description into LinkedIn search parameters Lead Discovery: Workflow searches LinkedIn using these parameters Data Collection: Results are saved to Google Sheets Enrichment: System collects additional data about each lead: Company website analysis Lead's LinkedIn posts Company's LinkedIn posts Recent company news Intent Analysis: AI analyzes all data to identify buying signals Lead Scoring: Leads are scored on a 1-10 scale based on likelihood of interest Connection Requests: Top-scoring leads receive connection requests Follow-Up: When connections are accepted, automated messages are sent Customization Search Parameters**: Adjust the AI Agent prompt to refine your target audience Scoring Criteria**: Modify scoring prompts to highlight indicators relevant to your product Message Content**: Update message templates for personalized outreach Schedule**: Configure when connection requests and messages are sent Rate Limits & Best Practices LinkedIn has connection request limits (approximately 100-200 per week) The workflow includes safeguards to avoid exceeding these limits Consider spacing your outreach for better response rates Note: Always use automation tools responsibly and in accordance with LinkedIn's terms of service.

This n8n template builds a simple automation to ensure no JIRA issues go unassigned for more than a week to prevent them falling through the cracks. It uses AI to perform searching tasks against a Supabase Vector Store. This can be one way to help reduce the amount of manual work in managing the issue backlog for busy teams with little effort. How it works This template contains 2 separate flows which run continuously via schedule triggers. The first populates our Supabase vector store with resolved issues within the last day. This helps keep our vector store up-to-date and relevant for the purpose of finding similar issues. It does this by pulling the latest resolved issues from JIRA and populating the Supabase vectorstore with carefully chosen metadata. This will come in handy later. The second flow watches for stale, unassigned issues for the purpose of aut-assigning to a relevant team member. It does this by comparing the stale issue against our vector store of resolved issues with the goal of identifying which team member would have best context regarding the issue. In a busy team, this may net a few team members as possible candidates to assign. Therefore, we can introduce additional logic to count each team member's assigned, in-progress issues. This is intended to not overload our busiest members. The team member with the least assigned issues is pressumed to have the most capacity and therefore is assigned. A comennt is left in the issue to notify the team member that they've been auto-assigned due to age of issue. How to use Modify the project and interval parameters to match those of your use-case and team members. Add additional criteria before assigning to a team member eg. department, as required. Requirements OpenAI for LLM JIRA for Issue Management Supabase for Vector Store Customising this workflow Not using JIRA or Supabase? The beauty of these AI templates are these components are entirely interchangeable with competing services. Try Linear and Qdrant instead! Auto-assigning logic is simplified in this template. Expand criteria as required for your team and organisation. eg. Might be a good idea to pull in annual leave information from HR system to prevent assigning to someone who is on currently on holiday!

This n8n template builds a newsletter ("daily digest") delivery service which pulls and summarises the latest n8n.io template in select categories defined by subscribers. It's scheduled to run once a day and sends the newsletter directly to subscriber via a nicely formatted email. If you've had trouble keeping up with the latest and greatest templates beign published daily, this workflow can save you a lot of time! How it works A scheduled trigger pulls a list of subscribers (email and category preferences) from an Excel workbook. We work out unique categories amongst all subscribers and only fetch the latest n8n website templates from these categories to save on resources and optimise the number of API calls we make. The fetched templates are summarised via AI to produce a short description which is more suitable for our email format. For each subscriber, we filter and collect only the templates relevant to their category preferences (as defined in the Excel) and ensure that duplicate templates or those which have been "seen before" are omitted. A HTML node is then used to generate the email newsletter. HTML emails are the perfect format since we can add links back to the template. Finally, we use the Outlook node to send the email digest to the subscriber. How to use Populate your Excel sheet with 3 columns: name, email and categories. Categories is a comma-delimited list of categories which match the n8n template website. The available categories are AI, SecOps, Sales, IT Ops, Marketing, Engineering, DevOps, Building Blocks, Design, Finance, HR, Other, Product and Support. To subscribe a new user, simply add their email to the Excel sheet with at least one category. To unsubscribe a user, remove them from the sheet. If you're not interested in paid templates, you may want to filter them out after fetching. Requirements Microsoft Excel for subscriber list Microsoft Outlook for delivering emails OpenAI for AI-generated descriptions Customising the workflow Use AI to summarise the week's trend of templates types and use-cases This template can be the basis for other similar newsletters - just pull in a list of things from anywhere!

This workflow template, "Personal Assistant to Note Messages and Extract Namecard Information" is designed to streamline the processing of incoming messages on the LINE messaging platform. It integrates with powerful tools like Microsoft Teams , Microsoft To Do , OneDrive , and OpenRouter.ai to handle tasks such as saving notes, extracting namecard information, and organizing images. Whether you’re managing personal productivity or automating workflows for teams, this template offers a versatile and customizable solution. By leveraging this workflow, you can automate repetitive tasks, improve collaboration, and enhance efficiency in handling LINE messages. Who Is This Template For? This template is ideal for: Professionals: Who want to save important messages, extract data from namecards, or organize images automatically. Teams: Looking to integrate LINE messages into tools like Microsoft Teams and Microsoft To Do for better collaboration. Developers: Seeking to build intelligent workflows that process text, images, and other inputs from LINE. Business Owners: Who need to manage customer interactions, follow-ups, and task tracking efficiently. What Problem Does This Workflow Solve? Managing incoming messages on LINE can be time-consuming, especially when dealing with diverse input types like text, images, and namecards. This workflow solves that problem by: Automatically identifying and routing different message types (text, images, namecards) to appropriate actions. Extracting structured data from namecards and saving it for follow-up tasks. Uploading images to OneDrive and saving text messages to Microsoft Teams or Microsoft To Do for easy access. Sending real-time feedback to users via LINE to confirm that their messages have been processed. What This Workflow Does Receive Messages via LINE Webhook: The workflow is triggered whenever a user sends a message (text, image, or other types) to the LINE bot. Display Loading Animation: A loading animation is displayed to reassure the user that their request is being processed. Route Input Types: The workflow uses a Switch node to determine the type of input: Text Starting with "T": Adds the message as a task in Microsoft To Do. Plain Text: Saves the message in Microsoft Teams under a designated channel (e.g., "Notes"). Images: Identifies whether the image is a namecard, handwritten note, or other content, then processes accordingly. Unsupported formats trigger a polite response indicating the limitation. Process Namecards: *Images * If the image is identified as a namecard, the workflow extracts structured data (e.g., name, email, phone number) using OpenRouter.ai and saves it to Microsoft To Do for follow-up tasks. Save Images to OneDrive: Images are uploaded to OneDrive, renamed based on their unique message ID, and linked in Microsoft Teams for reference. Send Feedback via LINE: The workflow replies to the user with confirmation messages, such as "[ Task Created ]" or "[ Message Saved ]." Setup Guide Pre-Requisites Access to the LINE Developers Console to configure your webhook and bot. Accounts for Microsoft Teams , Microsoft To Do, and OneDrive with API access. An OpenRouter.ai account with credentials to access models like GPT-4o. Basic knowledge of APIs, webhooks, and JSON formatting. Step-by-Step Setup 1) Configure the LINE Webhook: Go to the LINE Developers Console and set up a webhook to receive incoming messages. Copy the Webhook URL from the Line Webhook node and paste it into the LINE Console. Remove any "test" configurations when moving to production. 2) Set Up Microsoft Integrations: Connect your Microsoft Teams, Microsoft To Do, and OneDrive accounts to the respective nodes in the workflow. 3) Set Up OpenRouter.ai: Create an account on OpenRouter.ai and obtain your API credentials. Connect your credentials to the OpenRouter nodes in the workflow. Test the Workflow: Simulate sending text, images, and namecards to the LINE bot to verify that all actions are processed correctly. How to Customize This Workflow to Your Needs Add More Actions: Extend the workflow to handle additional input types or integrate with other tools. Enhance Image Processing: Use advanced OCR tools to improve text extraction from complex images. Customize Feedback Messages: Modify the reply format to include emojis, links, or other formatting options. Expand Use Cases: Adapt the workflow for specific industries, such as sales or customer support, by tailoring the actions to relevant tasks. Why Use This Template? Versatile Automation: Handles multiple input types (text, images, namecards) with ease. Seamless Integration: Connects LINE messages to popular productivity tools like Microsoft Teams and To Do. Structured Data Extraction: Extracts and organizes data from namecards, saving time and effort. Real-Time Feedback: Keeps users informed about the status of their requests with instant notifications.

Introduction The "Automatic Weekly Digital PR Stories Suggestions" workflow is a sophisticated automated system designed to identify trending news stories on Reddit, analyze public sentiment through comment analysis, extract key information from source articles, and generate strategic angles for potential digital PR campaigns. This workflow leverages the power of social media trends, natural language processing, and AI-driven analysis to deliver curated, sentiment-analyzed news opportunities for PR professionals. Operating on a weekly schedule, the workflow searches Reddit for posts related to specified topics, filters them based on engagement metrics, and performs a deep analysis of both the content and public reaction. It then generates comprehensive reports that include story opportunities, audience insights, and strategic recommendations. These reports are automatically compiled, stored in Google Drive, and shared with team members via Mattermost for immediate collaboration. This workflow solves the time-consuming process of manually monitoring social media for trending stories, analyzing public sentiment, and identifying PR opportunities. By automating these tasks, PR professionals can focus on strategy development and execution rather than spending hours on research and analysis. Who is this for? This workflow is designed for digital PR professionals, content marketers, communications teams, and media relations specialists who need to stay on top of trending stories and public sentiment to develop timely and effective PR campaigns. It's particularly valuable for: PR agencies managing multiple clients across different industries In-house PR teams needing to identify media opportunities quickly Content marketers looking for trending topics to create timely content Communications professionals monitoring public perception of industry news Users should have basic familiarity with n8n workflows and the PR strategy development process. While technical knowledge of the integrated APIs is not required to use the workflow, some understanding of Reddit, sentiment analysis, and PR campaign development would be beneficial for interpreting and acting on the generated reports. What problem is this workflow solving? Digital PR professionals face several challenges that this workflow addresses: Information Overload: Manually monitoring social media platforms for trending stories is time-consuming and often results in missed opportunities. Sentiment Analysis Complexity: Understanding public perception of news stories requires reading through hundreds of comments and identifying patterns, which is labor-intensive and subjective. Content Extraction: Visiting multiple news sources to read and analyze articles takes significant time. Strategic Angle Development: Identifying unique PR angles that leverage trending stories and public sentiment requires synthesizing large amounts of information. Team Collaboration: Sharing findings and insights with team members in a structured format can be cumbersome. By automating these processes, the workflow enables PR professionals to quickly identify trending stories with PR potential, understand public sentiment, and develop strategic angles based on comprehensive analysis, all while maintaining a structured approach to team collaboration. What this workflow does Overview The workflow automatically identifies trending posts on Reddit related to specified topics, analyzes both the content of linked articles and public sentiment from comments, and generates comprehensive PR strategy reports. These reports include story opportunities, audience insights, and strategic recommendations based on the analysis. The final reports are compiled, stored in Google Drive, and shared with team members via Mattermost. Process Topic Selection and Reddit Search: The workflow starts with a list of topics specified in the "Set Data" node It searches Reddit for posts related to these topics Posts are filtered based on upvotes and other criteria to focus on trending content Comment Analysis: For each post, the workflow retrieves comments It extracts the top 30 comments based on score Using Claude AI, it analyzes the comments to understand: Overall sentiment Dominant narratives Audience insights PR implications Content Analysis: The workflow extracts the content of the linked article using Jina AI It analyzes the content to identify: Core story elements Technical aspects Narrative opportunities Viral elements PR Strategy Development: Based on the combined analysis of comments and content, the workflow generates: First-mover story opportunities Trend-amplifier story ideas Priority rankings Execution roadmap Strategic recommendations Report Generation and Distribution: The workflow compiles comprehensive reports for each post Reports are converted to text files All files are compressed into a ZIP archive The archive is uploaded to Google Drive A link to the archive is shared with team members via Mattermost Setup To set up this workflow, follow these steps: Import the Workflow: Download the workflow JSON file Import it into your n8n instance Configure API Credentials: Reddit: Add a new credential "Reddit OAuth2 API" by following the guide at https://docs.n8n.io/integrations/builtin/credentials/reddit/ Anthropic: Add a new credential "Anthropic Account" by following the guide at https://docs.n8n.io/integrations/builtin/credentials/anthropic/ Google Drive: Add a new credential "Google Drive OAuth2 API" by following the guide at https://docs.n8n.io/integrations/builtin/credentials/google/oauth-single-service/ Configure the "Set Data" Node: Set your interested topics (one per line) Add your Jina API key (obtain from https://jina.ai/api-dashboard/key-manager) Configure the Mattermost Node: Update your Mattermost instance URL Set your Webhook ID and Channel Follow the guide at https://developers.mattermost.com/integrate/webhooks/incoming/ for webhook setup Adjust the Schedule (Optional): The workflow is set to run every Monday at 6am Modify the "Schedule Trigger" node if you need a different schedule Test the Workflow: Run the workflow manually to ensure all connections are working properly Check the output to verify the reports are being generated correctly How to customize this workflow to your needs This workflow can be customized in several ways to better suit your specific requirements: Topic Selection: Modify the topics in the "Set Data" node to focus on industries or subjects relevant to your PR strategy Add multiple topics to cover different client interests or market segments Filtering Criteria: Adjust the "Upvotes Requirement Filtering" node to change the minimum upvotes threshold Modify the filtering conditions to include or exclude certain types of posts Analysis Parameters: Customize the prompts in the "Comments Analysis," "News Analysis," and "Stories Report" nodes to focus on specific aspects of the content or comments Adjust the temperature settings in the Anthropic Chat Model nodes to control the creativity of the AI responses Report Format: Modify the "Set Final Report" node to change the structure or content of the final reports Add or remove sections based on your specific reporting needs Distribution Method: Replace or supplement the Mattermost notification with email notifications, Slack messages, or other communication channels Add additional storage options beyond Google Drive Schedule Frequency: Change the "Schedule Trigger" node to run the workflow more or less frequently Set up multiple triggers for different topics or clients Integration with Other Systems: Add nodes to integrate with your CRM, content management system, or project management tools Create connections to automatically populate content calendars or task management systems

This workflow with AI agent is designed to navigate through the page to retrieve specific type of information (in this example: social media profile links). The agent is equipped with 2 tools: text tool:** to retrieve all the text from the page, URLs tool:** to extract all possible links from the page. 💡 You can edit prompt and JSON schema connected to the agent in order to return other data then social media profile links. 👉 This workflow uses Supabase as storage (input/output). Feel free to change it to any other database of your choice. 🎬 See this workflow in action in my YouTube video. How it works? The workflow uses the input URL (website) as a starting point to retrieve the data (e.g. example.com). Using the "URLs tool", the agent is able to retrieve all links from the page and navigate to them. For example, if you want to retrieve contact information, agent will try to find a subpage that might contain this information (e.g. example.com/contact) and extract the information using the text tool. Set up steps Connect database with input data (website addresses) or pin sample data to trigger node. Configure the crawling agent to retrieve the desired data (e.g. modify prompt and/or parsing schema). Set credentials for OpenAI. Optionally: split agent tools to separate workflows. If you like this workflow, please subscribe to my YouTube channel and/or my newsletter.