Workflow Templates

Video Guide I prepared a detailed guide explaining how to build an AI-powered meeting assistant that provides real-time transcription and insights during virtual meetings. Youtube Link Who is this for? This workflow is ideal for business professionals, project managers, and team leaders who require effective transcription of meetings for improved documentation and note-taking. It's particularly beneficial for those who conduct frequent virtual meetings across various platforms like Zoom and Google Meet. What problem does this workflow solve? Transcribing meetings manually can be tedious and prone to error. This workflow automates the transcription process in real-time, ensuring that key discussions and decisions are accurately captured and easily accessible for later review, thus enhancing productivity and clarity in communications. What this workflow does The workflow employs an AI-powered assistant to join virtual meetings and capture discussions through real-time transcription. Key functionalities include: Automatic joining of meetings on platforms like Zoom, Google Meet, and others with the ability to provide real-time transcription. Integration with transcription APIs (e.g., AssemblyAI) to deliver seamless and accurate capture of dialogue. Structuring and storing transcriptions efficiently in a database for easy retrieval and analysis. Real-Time Transcription: The assistant captures audio during meetings and transcribes it in real-time, allowing participants to focus on discussions. Keyword Recognition: Key phrases can trigger specific actions, such as noting important points or making prompts to the assistant. Structured Data Management: The assistant maintains a database of transcriptions linked to meeting details for organized storage and quick access later. Setup Preparation Create Recall.ai API key Setup Supabase account and table create table public.data ( id uuid not null default gen_random_uuid (), date_created timestamp with time zone not null default (now() at time zone 'utc'::text), input jsonb null, output jsonb null, constraint data_pkey primary key (id), ) tablespace pg_default; Create OpenAI API key Development Bot Creation: Use a node to create the bot that will join meetings. Provide the meeting URL and set transcription options within the API request. Authentication: Configure authentication settings via a Bearer token for interacting with your transcription service. Webhook Setup: Create a webhook to receive real-time transcription updates, ensuring timely data capture during meetings. Join Meeting: Set the bot to join the specified meeting and actively listen to capture conversations. Transcription Handling: Combine transcription fragments into cohesive sentences and manage dialog arrays for coherence. Trigger Actions on Keywords: Set up keyword recognition that can initiate requests to the OpenAI API for additional interactions based on captured dialogue. Output and Summary Generation: Produce insights and summary notes from the transcriptions that can be stored back into the database for future reference.

🎯 Universal Meeting Transcript to LinkedIn Content Automatically transform your meeting insights into engaging LinkedIn content with AI Perfect for coaches, consultants, sales professionals, and content creators who want to share valuable insights from their meetings without the manual effort of content creation. How it works Calendar trigger detects when your coaching/meeting ends Waits for meeting completion, then sends you a form via email You provide the meeting transcript and specify post preferences AI analyzes the transcript using your personal brand guidelines Generates professional LinkedIn content based on real insights Creates organized Google Docs with both transcript and final post Sends you links to review and publish your content How to use Connect your Google Calendar and Gmail accounts Update the calendar filter to match your meeting types Customize the AI prompts with your brand voice and style Replace email addresses with your own Test with a sample meeting transcript Requirements Google Calendar (for meeting detection) Gmail (for form delivery and notifications) Google Drive & Docs (for content storage) LangChain AI nodes (for content generation) Good to know AI processing may incur costs based on your LangChain provider Works with any meeting platform - just copy/paste transcripts Can be adapted to use webhooks from recording tools like Fireflies.ai Memory nodes store your brand guidelines for consistent output Happy Content Creating!

🎯 Automated TikTok Influencer Discovery & Analysis A complete n8n automation that discovers TikTok influencers using Bright Data, evaluates their fit using Claude AI, and sends personalized outreach emails. Designed for marketing teams and brands that need a scalable, intelligent way to find and connect with relevant creators. 📋 Overview This workflow provides a full-service influencer discovery pipeline: it finds TikTok profiles using search keywords, uses AI to assess alignment with your brand, and initiates contact with qualified influencers. Ideal for influencer marketing, brand partnerships, and campaign planning. ✨ Key Features 🔍 Keyword-Based Discovery** Locate TikTok influencers by specific niche-related keywords. 📊 Bright Data Integration** Access accurate TikTok profile data from Bright Data’s datasets. 🤖 AI-Powered Analysis** Claude AI evaluates each profile's fit with your brand based on bio, content, and more. 📧 Smart Email Notifications** Sends tailored outreach emails to creators deemed highly relevant. 📈 Data Storage** Google Sheets stores profile details, AI evaluation results, and outreach status. 🎯 Intelligent Filtering** Processes only influencers who meet your criteria (e.g., 5000+ followers, industry match). ⚡ Fast & Reliable** Uses professional scraping with robust error handling. 🔄 Batch Processing** Supports bulk influencer processing through a single automated flow. 🎯 What This Workflow Does Input Search Keywords** – TikTok terms for finding niche creators Business Info** – Brand description and industry Collaboration Criteria** – Follower count minimum, niche alignment Processing Steps Form Submission TikTok Discovery via Bright Data Data Extraction and Normalization Save to Google Sheets Relevance Scoring via Claude AI Filtering Based on AI Score + Follower Count Personalized Email Outreach Output Data Points | Field | Description | Example | |---------------|------------------------------------|----------------------------------| | Profile ID | TikTok profile identifier | tiktoker123456 | | Username | TikTok handle | @creativecreator | | URL | Profile link | https://tiktok.com/@creativecreator | | Description | Creator bio | "Fashion & lifestyle content..." | | Followers | Total follower count | 50,000 | | Collaboration | AI assessment of brand fit | "Highly Relevant" | | Analysis | 50-word Claude AI relevance summary| "Strong alignment with fashion..."| 🚀 Setup Instructions Prerequisites n8n (cloud or self-hosted) Bright Data account with TikTok access Google Sheets + Gmail Anthropic Claude API key 10–15 minutes setup time Step-by-Step Setup Import Workflow via JSON in n8n Configure Bright Data – Add API credentials and dataset ID Google Sheets – Setup credentials and map columns Claude AI – Insert API key and select desired model Gmail – Authenticate Gmail and update mail node settings Update Variables – Replace placeholders with business info Test & Launch – Submit a sample form and verify all outputs 📖 Usage Guide Adding Search Keywords Submit the form with search terms, business description, and industry category to trigger the workflow. Understanding AI Analysis Emails are sent only if: Collaboration status = Highly Relevant Follower count ≥ 5000 Industry alignment confirmed Claude AI returns a 50-word analysis justifying the match Customizing Filters Edit the "Find the Collaborator" prompt to adjust: Follower thresholds Industry relevance Additional metrics (e.g., engagement rate) Viewing Results Google Sheets log includes: Influencer metadata AI scores and rationale Collaboration status Email delivery timestamp 🔧 Customization Options Add More Fields:** Engagement rate, contact email, content themes Email Personalization:** Customize message templates or integrate other mail services Enhanced Filtering:** Use engagement rates, region, content frequency 🚨 Troubleshooting | Issue | Fix | |-------|-----| | Bright Data fails | Recheck API and dataset ID | | No influencer data | Adjust keywords or dataset scope | | Sheets permission error | Re-authenticate and check sharing | | Claude fails | Validate API key and prompt | | Emails not sent | Re-auth Gmail or update recipient field | | Form not triggering | Reconfirm webhook URL and permissions | Advanced Debugging Check n8n execution logs Run individual nodes for pinpointing failures Confirm all data formats Handle API rate limits Add error-catch nodes for retries 📊 Use Cases & Examples Brand Discovery:** Fashion, tech, fitness creators Competitor Insights:** Find influencers used by rival brands Campaign Planning:** Build targeted influencer lists Market Research:** Identify creator trends across regions ⚙️ Advanced Configuration Batch Execution:** Process multiple keywords with delay logic Engagement Metrics:** Scrape and calculate likes-to-follower ratios CRM Integration:** Sync qualified profiles to HubSpot, Salesforce, or Slack 📈 Performance & Limits Processing Time:** 3–5 minutes per keyword Concurrency:** 3–5 simultaneous fetches (depends on plan) Accuracy:** >95% influencer data reliability Success Rate:** 90%+ for outreach and processing

Who is this template for? This workflow template is designed for Marketing and pre-Sales to get prospects from a form like Tally, decline data in the famous opensource CRM (SuiteCRM), synchronize contact in Brevo with linking the id from CRM, and then notify in NextCloud. Bonus : validate email with ++CaptainVerify++ and notify in NextCloud depending on response How it works For each submission in the form, a webhook is triggered. A check of the email is done with CaptainVerify. Depending on the response, and if it is ok, then a Lead is created in SuiteCRM. Else, a message in your selected discussion is sent. As the lead has been created, we can create a contact in Brevo (for future campain), ank link this contact with the lead_id from the CRM in a dedicated field. Finaly, a message in your selected discussion in NextCloud informs you about the lead. Set up instructions Complete the Set up credentials step when you first open the workflow. You'll need a CaptainVerify account (Api Key), a dedicated SuiteCRM user with Oauth, a Brevo account (Api Key) and a Nextcloud account. Set up the Webhook in the form's tool of your choice (why not Tally ?). Set each node with the explanations in sticky Notes. Enjoy ! Template was created in n8n v1.44.1

Notice Community nodes can only be installed on self-hosted instances of n8n. Who this is for The DNB Company Search & Extract workflow is designed for professionals who need to gather structured business intelligence from Dun & Bradstreet (DNB). It is ideal for: Market Researchers B2B Sales & Lead Generation Experts Business Analysts Investment Analysts AI Developers Building Financial Knowledge Graphs What problem is this workflow solving? Gathering business information from the DNB website usually involves manual browsing, copying company details, and organizing them in spreadsheets. This workflow automates the entire data collection pipeline — from searching DNB via Google, scraping relevant pages, to structuring the data and saving it in usable formats. What this workflow does This workflow performs automated search, scraping, and structured extraction of DNB company profiles using Bright Data’s MCP search agents and OpenAI’s 4o mini model. Here's what it includes: Set Input Fields: Provide search_query and webhook_notification_url. Bright Data MCP Client (Search): Performs Google search for the DNB company URL. Markdown Scrape from DNB: Scrapes the company page using Bright Data and returns it as markdown. OpenAI LLM Extraction: Transforms markdown into clean structured data. Extracts business information (company name, size, address, industry, etc.) Webhook Notification: Sends structured response to your provided webhook. Save to Disk: Persists the structured data locally for logging or auditing. Pre-conditions Knowledge of Model Context Protocol (MCP) is highly essential. Please read this blog post - model-context-protocol You need to have the Bright Data account and do the necessary setup as mentioned in the Setup section below. You need to have the Google Gemini API Key. Visit Google AI Studio You need to install the Bright Data MCP Server @brightdata/mcp You need to install the n8n-nodes-mcp Setup Please make sure to setup n8n locally with MCP Servers by navigating to n8n-nodes-mcp Please make sure to install the Bright Data MCP Server @brightdata/mcp on your local machine. Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. Create a Web Unlocker proxy zone called mcp_unlocker on Bright Data control panel. In n8n, configure the OpenAi account credentials. In n8n, configure the credentials to connect with MCP Client (STDIO) account with the Bright Data MCP Server as shown below. Make sure to copy the Bright Data API_TOKEN within the Environments textbox above as API_TOKEN=<your-token>. Update the Set input fields for search_query and webhook_notification_url. Update the file name and path to persist on disk. How to customize this workflow to your needs Search Engine**: Default is Google, but you can change the MCP client engine to Bing, or Yandex if needed. Company Scope**: Modify search query logic for niche filtering, e.g., "biotech startups site:dnb.com". Structured Fields**: Customize the LLM prompt to extract additional fields like CEO name, revenue, or ratings. Integrations**: Push output to Notion, Airtable, or CRMs like HubSpot using additional n8n nodes. Formatting**: Convert output to PDF or CSV using built-in File and Spreadsheet nodes.

🛠️ Philips Hue Tool MCP Server Complete MCP server exposing all Philips Hue Tool operations to AI agents. Zero configuration needed - all 4 operations pre-built. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works • MCP Trigger: Serves as your server endpoint for AI agent requests • Tool Nodes: Pre-configured for every Philips Hue Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Philips Hue Tool tool with full error handling 📋 Available Operations (4 total) Every possible Philips Hue Tool operation is included: 🔧 Light (4 operations) • Delete a light • Get a light • Get many lights • Update a light 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Resource IDs and identifiers • Search queries and filters • Content and data payloads • Configuration options Response Format: Native Philips Hue Tool API responses with full data structure Error Handling: Built-in n8n error management and retry logic 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • Other n8n Workflows: Call MCP tools from any workflow • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Complete Coverage: Every Philips Hue Tool operation available • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n error handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

📊 Real-Time Flight Data Analytics Bot with Dynamic Chart Generation via Telegram 🚀 Template Overview This advanced n8n workflow creates an intelligent Telegram bot that transforms raw CSV flight data into stunning, interactive visualizations. Users can generate professional charts on-demand through a conversational interface, making data analytics accessible to anyone via messaging. Key Innovation: Combines real-time data processing, Chart.js visualization engine, and Telegram's messaging platform to deliver instant business intelligence insights. 🎯 What This Template Does Transform your flight booking data into actionable insights with four powerful visualization types: 📈 Bar Charts**: Top 10 busiest airlines by flight volume 🥧 Pie Charts**: Flight duration distribution (Short/Medium/Long-haul) 🍩 Doughnut Charts**: Price range segmentation with average pricing 📊 Line Charts**: Price trend analysis across flight durations Each chart includes auto-generated insights, percentages, and key business metrics delivered instantly to users' phones. 🏗️ Technical Architecture Core Components Telegram Webhook Trigger: Captures user interactions and button clicks Smart Routing Engine: Conditional logic for command detection and chart selection CSV Data Pipeline: File reading → parsing → JSON transformation Chart Generation Engine: JavaScript-powered data processing with Chart.js Image Rendering Service: QuickChart API for high-quality PNG generation Response Delivery: Binary image transmission back to Telegram Data Flow Architecture User Input → Command Detection → CSV Processing → Data Aggregation → Chart Configuration → Image Generation → Telegram Delivery 🛠️ Setup Requirements Prerequisites n8n instance** (self-hosted or cloud) Telegram Bot Token** from @BotFather CSV dataset** with flight information Internet connectivity** for QuickChart API Dataset Source This template uses the Airlines Flights Data dataset from GitHub: 🔗 Dataset: Airlines Flights Data by Rohit Grewal Required Data Schema Your CSV file should contain these columns: airline,flight,source_city,departure_time,arrival_time,duration,price,class,destination_city,stops File Structure /data/ └── flights.csv (download from GitHub dataset above) ⚙️ Configuration Steps 1. Telegram Bot Setup Create a new bot via @BotFather on Telegram Copy your bot token Configure the Telegram Trigger node with your token Set webhook URL in your n8n instance 2. Data Preparation Download the dataset from Airlines Flights Data Upload the CSV file to /data/flights.csv in your n8n instance Ensure UTF-8 encoding Verify column headers match the dataset schema Test file accessibility from n8n 3. Workflow Activation Import the workflow JSON Configure all Telegram nodes with your bot token Test the /start command Activate the workflow 🔧 Technical Implementation Details Chart Generation Process Bar Chart Logic: // Aggregate airline counts const airlineCounts = {}; flights.forEach(flight => { const airline = flight.airline || 'Unknown'; airlineCounts[airline] = (airlineCounts[airline] || 0) + 1; }); // Generate Chart.js configuration const chartConfig = { type: 'bar', data: { labels, datasets }, options: { responsive: true, plugins: {...} } }; Dynamic Color Schemes: Bar Charts: Professional blue gradient palette Pie Charts: Duration-based color coding (light→dark blue) Doughnut Charts: Price-tier specific colors (green→purple) Line Charts: Trend-focused red gradient with smooth curves Performance Optimizations Efficient Data Processing: Single-pass aggregations with O(n) complexity Smart Caching: QuickChart handles image caching automatically Minimal Memory Usage: Stream processing for large datasets Error Handling: Graceful fallbacks for missing data fields Advanced Features Auto-Generated Insights: Statistical calculations (percentages, averages, totals) Trend analysis and pattern detection Business intelligence summaries Contextual recommendations User Experience Enhancements: Reply keyboards for easy navigation Visual progress indicators Error recovery mechanisms Mobile-optimized chart dimensions (800x600px) 📈 Use Cases & Business Applications Airlines & Travel Companies Fleet Analysis**: Monitor airline performance and market share Pricing Strategy**: Analyze competitor pricing across routes Operational Insights**: Track duration patterns and efficiency Data Analytics Teams Self-Service BI**: Enable non-technical users to generate reports Mobile Dashboards**: Access insights anywhere via Telegram Rapid Prototyping**: Quick data exploration without complex tools Business Intelligence Executive Reporting**: Instant charts for presentations Market Research**: Compare industry trends and benchmarks Performance Monitoring**: Track KPIs in real-time 🎨 Customization Options Adding New Chart Types Create new Switch condition Add corresponding data processing node Configure Chart.js options Update user interface menu Data Source Extensions Replace CSV with database connections Add real-time API integrations Implement data refresh mechanisms Support multiple file formats Visual Customizations // Custom color palette backgroundColor: ['#your-colors'], // Advanced styling borderRadius: 8, borderSkipped: false, // Animation effects animation: { duration: 2000, easing: 'easeInOutQuart' } 🔒 Security & Best Practices Data Protection Validate CSV input format Sanitize user inputs Implement rate limiting Secure file access permissions Error Handling Graceful degradation for API failures User-friendly error messages Automatic retry mechanisms Comprehensive logging 📊 Expected Outputs Sample Generated Insights "✈️ Vistara leads with 350+ flights, capturing 23.4% market share" "📈 Long-haul flights dominate at 61.1% of total bookings" "💰 Budget category (₹0-10K) represents 47.5% of all bookings" "📊 Average prices peak at ₹14K for 6-8 hour duration flights" Performance Metrics Response Time**: <3 seconds for chart generation Image Quality**: 800x600px high-resolution PNG Data Capacity**: Handles 10K+ records efficiently Concurrent Users**: Scales with n8n instance capacity 🚀 Getting Started Download the workflow JSON Import into your n8n instance Configure Telegram bot credentials Upload your flight data CSV Test with /start command Deploy and share with your team 💡 Pro Tips Data Quality**: Clean data produces better insights Mobile First**: Charts are optimized for mobile viewing Batch Processing**: Handles large datasets efficiently Extensible Design**: Easy to add new visualization types Ready to transform your data into actionable insights? Import this template and start generating professional charts in minutes! 🚀

Who is this template for? This workflow template is designed for teams involved in training management and feedback analysis. It is particularly useful for: HR Departments**: Automating the collection and response to training feedback. Training Managers**: Streamlining the process of handling feedback and ensuring timely follow-up. Corporate Trainers**: Receiving direct feedback and taking actions to improve training sessions. This workflow offers a comprehensive solution for automating feedback management, ensuring timely responses, and improving the quality of training programs. How it works This workflow operates with an Airtable trigger but can be easily adapted to work with other triggers like webhooks from external applications. Once feedback data is captured, the workflow evaluates the feedback and directs it to the appropriate channel for action. Tasks are created in Usertask based on the feedback rating, and notifications are sent to relevant parties. Here’s a brief overview of this n8n workflow template: Airtable Trigger**: Captures new or updated feedback entries from Airtable. Switch Node**: Evaluates the feedback rating and directs the workflow based on the rating. Webhook**: Retrieves the result of a Usertask task. Task Creation**: Creates tasks in Usertask for poor feedback. Creates follow-up tasks for fair to good feedback. Documents positive feedback and posts recognition on LinkedIn for very good to excellent ratings. Notifications**: Sends email notifications to responsible parties for urgent actions. Sends congratulatory emails and posts on LinkedIn for positive feedback. To summarize Flexible Integration**: This workflow can be triggered by various methods like Airtable updates or webhooks from other applications. Automated Task Management**: It creates tasks in Usertask based on feedback ratings to ensure timely follow-up. Multichannel Notifications**: Sends notifications via email and LinkedIn to keep stakeholders informed and recognize successes. Comprehensive Feedback Handling**: Automates the evaluation and response to training feedback, improving efficiency and response time. Instructions: Set Up Airtable: Create a table in Airtable to capture training feedback. Configure n8n: Set up the Airtable trigger in n8n to capture new or updated feedback entries. Set Up Usertask: Configure the Usertask nodes in n8n to create and manage tasks based on feedback ratings. Configure Email and LinkedIn Nodes: Set up the email and LinkedIn nodes to send notifications and post updates. Test the Workflow: Run tests to ensure the workflow captures feedback, creates tasks, and sends notifications correctly. Video : https://youtu.be/U14MhTcpqeY Remember, this template was created in n8n v1.38.2.

Who is this template for? This workflow template is designed for accounting, human resources, and IT project management teams looking to automate the generation of PDF and Word documents. It can be particularly useful for: The accounting department: for generating invoices in PDF format, thus streamlining the invoicing process and payment tracking. The human resources department: for creating employment contracts in PDF, simplifying the administrative management of employees. IT project management teams: for producing Word documents, such as project specifications, to clearly define project requirements and objectives. Example result in mail This PDF and Word document generation workflow offers a practical and efficient solution for automating administrative and document-related tasks, allowing teams to focus on higher-value activities. How it works This workflow currently operates with an n8n form, but you can easily replace this form with a webhook triggered by an external application such as AirTable, SharePoint, DocuWare, etc. Once the configuration information is retrieved, we fill the API request body of JSReport. The body is defined at the time of template creation in JSReport (Example of JSReport usage). Then, in a straightforward manner, we fetch the PDF and send it via email. Here's a brief overview of this n8n workflow template: Link to n8n workflow template presentation To summarize This workflow integrates with an n8n form, but it's flexible to work with various triggering methods like webhooks from other applications such as AirTable, SharePoint, or DocuWare. After configuring the necessary information, it populates the API request body of JSReport, which defines the template in JSReport. Once the template is populated, it retrieves the PDF and sends it via email. In essence, it streamlines the process of generating PDF documents based on user input and distributing them via email. Instructions: Create a JSReport Account: Sign up for a JSReport account to create your PDF template model. Define PDF Template in JSReport: Use JSON data from your system to set up the content of your PDF template in JSReport. Configure HTTP Request in n8n: Use the HTTP Request node in n8n to send a request to JSReport. Set the node's body to the JSON data defining your PDF template. Watch the Video: For detailed setup guidance, watch the setup video. Remember, this template was created in n8n v1.38.2.

Who this is for The Crunchbase B2B Lead Discovery Pipeline is designed for sales teams, B2B marketers, business analysts, and data operations teams who need a reliable way to extract, structure, and summarize company information from Crunchbase to fuel lead generation and market intelligence. This workflow is ideal for: Sales Development Reps (SDRs) - Needing structured leads from Crunchbase Marketing Analysts - Generating segmented outreach lists Growth Teams - Identifying trending B2B startups RevOps Teams - Automating company research pipelines Data Teams - Consolidating insights into Google Sheets for dashboards What problem is this workflow solving? Manual extraction of company data from Crunchbase is time-consuming, inconsistent, and often lacks the contextual summary required for sales enablement or growth targeting. This workflow automates the extraction, transformation, summarization, and delivery of Crunchbase company data into structured formats, making it instantly usable for B2B targeting and analysis. It solves: The difficulty of scaling lead discovery from Crunchbase The need to summarize raw textual content for quick insights The lack of integration between web scraping, LLM processing, and storage What this workflow does Markdown to Textual Data Extractor**: Takes raw scraped markdown from Crunchbase and converts it into readable plain text using a basic LLM chain Structured Data Extraction**: Applies a parsing model (OpenAI) to extract structured fields such as company name, funding rounds, industry tags, location, and founding year Summarization Chain**: Generates an executive summary from the raw Crunchbase text using a summarization prompt template Send to Google Sheets**: Adds the structured data and summary into a Google Sheet for team access and further processing Persist to Disk**: Saves both raw and structured data files locally for archiving or further use Webhook Notification**: Sends a structured payload to a webhook endpoint (e.g., Slack, CRM, internal tools) with lead insights Pre-conditions You need to have a Bright Data account and do the necessary setup as mentioned in the "Setup" section below. You need to have an OpenAI Account. Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. In n8n, Configure the Google Sheet Credentials with your own account. Follow this documentation - Set Google Sheet Credential In n8n, configure the OpenAi account credentials. Ensure the URL and Bright Data zone name are correctly set in the Set URL, Filename and Bright Data Zone node. Set the desired local path in the Write a file to disk node to save the responses. How to customize this workflow to your needs LLM Prompt Customization : Modify the extraction prompt to include additional fields like revenue, social links, leadership team Adjust summarization tone (e.g., executive summary, sales-focused snapshot or marketing digest) File Persistence Store raw markdown, extracted JSON, and summary text separately for audit/debug Webhook Notification Connect to CRM (e.g., HubSpot, Salesforce) via webhook to automatically create leads Send Slack notifications to alert sales reps when a new high-potential company is discovered

SEO Blog Generator with GPT-4o, Perplexity, and Telegram Integration This workflow helps you automatically generate SEO-optimized blog posts using Perplexity.ai, OpenAI GPT-4o, and optionally Telegram for interaction. 🚀 Features 🧠 Topic research via Perplexity sub-workflow ✍️ AI-written blog post generated with GPT-4o 📊 Structured output with metadata: title, slug, meta description 📩 Integration with Telegram to trigger workflows or receive outputs (optional) ⚙️ Requirements ✅ OpenAI API Key (GPT-4o or GPT-3.5) ✅ Perplexity API Key (with access to /chat/completions) ✅ (Optional) Telegram Bot Token and webhook setup 🛠 Setup Instructions Credentials: Add your OpenAI credentials (openAiApi) Add your Perplexity credentials under httpHeaderAuth Optional: Setup Telegram credentials under telegramApi Inputs: Use the Form Trigger or Telegram input node to send a Research Query Subworkflow: Make sure to import and activate the subworkflow Perplexity_Searcher to fetch recent search results Customization: Edit prompt texts inside the Blog Content Generator and Metadata Generator to change writing style or target industry Add or remove output nodes like Google Sheets, Notion, etc. 📦 Output Format The final blog post includes: ✅ Blog content (1500-2000 words) ✅ Metadata: title, slug, and meta description ✅ Extracted summary in JSON ✅ Delivered to Telegram (if connected) Need help? Reach out on the n8n community forum

How it works • Extract AI Overviews from Google Search - Receives data from browser extension via webhook • Convert HTML to Markdown - Automatically processes and cleans AI Overview content • Store in Google Sheets - Archives all extracted AI Overviews with metadata and sources • Generate SEO Guidelines - AI analyzes page content vs AI Overview to suggest improvements • Automate Analysis - Batch process multiple URLs and schedule regular checks Set up steps • Import workflow - Load the JSON template into your n8n instance (2 minutes) • Configure Google Sheets - Set up OAuth connection and create spreadsheet with required columns (5 minutes) • Set up AI provider - Add OpenRouter API credentials for Gemini 2.5 Pro (3 minutes) • Install browser extension - Deploy the companion Chrome/Firefox extension for data extraction (5 minutes) • Test webhook endpoint - Verify the connection between extension and n8n workflow (2 minutes) Total setup time: ~15 minutes What you'll need: Google account for Sheets integration Google Sheet template with required columns OpenRouter API key for Gemini 2.5 Pro model access Browser extension: Chrome Extension or Firefox Add-on n8n instance (local or cloud) Use cases: SEO agencies** - Monitor AI Overview presence for client keywords Content marketers** - Analyze what content gets featured in AI Overviews E-commerce** - Track AI Overview coverage for product-related searches Research** - Build datasets of AI Overview content across different topics The workflow comes with a free browser extension (Chrome | Firefox) that automatically extracts AI Overview content from Google Search and sends it via webhook to your n8n workflow for processing and analysis. GitHub Repository: https://github.com/romek-rozen/ai-overview-extractor/ Detailed Setup Instructions - AI Overview Extractor Prerequisites n8n instance** (local or cloud) - version 1.95.3+ Google account** for Sheets integration OpenRouter API account** for Gemini 2.5 Pro access Browser** (Chrome/Firefox) for the extension Step 1: Import the Workflow Open n8n and navigate to Workflows Click "Add workflow" → "Import from JSON" Upload the AI_OVERVIES_EXTRACTOR_TEMPLATE.json file Save the workflow Step 2: Configure Google Sheets Create Google Sheets Document Create new Google Sheet with these columns: extractedAt | searchQuery | sources | markdown | myURL | task | guidelines | key Here is public google sheet template: https://docs.google.com/spreadsheets/d/15xqZ2dTiLMoyICYnnnRV-HPvXfdgVeXowr8a7kU4uHk/edit?gid=0#gid=0 Copy the Google Sheets URL (you'll need it for the workflow) Set up Google Sheets Credentials In n8n, go to Settings → Credentials Click "Add credential" → "Google Sheets OAuth2 API" Follow the OAuth setup to authorize n8n access to Google Sheets Name the credential (e.g., "Google Sheets AI Overview") Configure Google Sheets Nodes Update these nodes with your Google Sheets URL: Get URLs to Analyze Save AI Overview to Sheets Save SEO Guidelines to Sheets In each node: Set documentId to your Google Sheets URL Set sheetName to your Google Sheets URL Select your Google Sheets credential Step 3: Configure AI Provider (OpenRouter) Get OpenRouter API Key Sign up at https://openrouter.ai/ Generate API key in your account settings Add credits to your account Set up OpenRouter Credentials In n8n, go to Settings → Credentials Click "Add credential" → "OpenRouter API" Enter your API key Name the credential (e.g., "OpenRouter AI Overview") Configure OpenRouter Node Select the Gemini 2.5 Pro Model node Choose your credential from the dropdown Verify the model (default: google/gemini-2.5-pro-preview) Step 4: Install Browser Extension Install in Chrome Official Extension (Recommended) Visit: https://chromewebstore.google.com/detail/ai-overview-extractor/cbkdfibgmhicgnmmdanlhnebbgonhjje Click "Add to Chrome" Install in Firefox Official Add-on Visit: https://addons.mozilla.org/en-US/firefox/addon/ai-overview-extractor/ Click "Add to Firefox" Step 5: Configure Webhook Connection Get Webhook URL In n8n workflow, click on the Webhook node Copy the webhook URL (should be like: http://localhost:5678/webhook/ai-overview-extractor-template-123456789) Configure Extension Go to Google Search and perform any search with AI Overview Click the browser extension button (AI Overview Extractor) In webhook configuration section, paste your webhook URL Click "Test" - should show ✅ Test successful Click "Save" to store the configuration Step 6: Activate and Test Activate Workflow In n8n, toggle the workflow to "Active" (top right switch) Verify all nodes are properly configured Test End-to-End Go to Google Search Search for something that shows AI Overview Use the extension to extract AI Overview Send via webhook - check your Google Sheets for the data Verify the markdown conversion worked correctly Optional: Batch Analysis Setup For SEO Analysis Features In your Google Sheets, add URLs in the myURL column Set task column to "create guidelines" Run the workflow manually or wait for the 15-minute scheduler Check guidelines column for AI-generated SEO recommendations Troubleshooting Webhook Issues Ensure n8n is running on port 5678 Check if workflow is activated Verify webhook URL format Google Sheets Errors Confirm OAuth credentials are working Check sheet URL format Verify column names match exactly Ensure nodes Get URLs to Analyze, Save AI Overview to Sheets, and Save SEO Guidelines to Sheets are properly configured OpenRouter Issues Check API key validity Ensure sufficient account credits Try different models if Gemini 2.5 Pro fails Verify the Gemini 2.5 Pro Model node is properly connected Extension Problems Check browser console for errors Verify extension is properly installed Ensure you're on google.com/search pages Confirm webhook URL is correctly configured in extension Next Steps Customize AI prompts** in the Generate SEO Recommendations node for your specific needs Adjust scheduler frequency** (default: 15 minutes) Add more URL analysis** by populating Google Sheets Monitor usage** and API costs Support GitHub Issues**: https://github.com/romek-rozen/ai-overview-extractor/issues n8n Community**: https://community.n8n.io/ Template Documentation**: Check the included README files