Workflow Templates

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. **This n8n template automates candidate outreach, call transcription, and structured feedback capture for HR teams and recruiters. It triggers on a new candidate row added in a Google Sheet, initiates a call using Vapi.ai, processes the transcript using Google Gemini, extracts key information like CTC, experience, and notice period, and then updates the same Google Sheet with parsed insights. This is ideal for recruiters or HR teams conducting high-volume candidate outreach and wanting to scale initial data collection using automated voice bots and AI transcription analysis.** How it works Trigger: Listens for new rows added to a Google Sheet (e.g., a new candidate lead). Call Initiation: Uses Vapi.ai to make a phone call to the candidate using an assistant bot. Transcript Retrieval: After the call, fetches the conversation transcript from the Vapi API. AI Transcript Analysis: Google Gemini parses the transcript and extracts structured fields like: Work experience Current & expected CTC Notice period & negotiability Work preferences and location Data Mapping: Extracted insights are mapped to structured JSON fields. Google Sheet Update: The same row in the source Sheet is updated with the collected information. Use Cases Pre-screening calls for job applicants Collecting missing candidate information asynchronously Replacing manual HR data entry with AI-powered automation Smart CRM updates from voice interactions Requirements Before you run this workflow, ensure the following: ✅ Google account with access to Google Sheets API ✅ Vapi.ai account with: Assistant ID Phone number ID Active API key ✅ Google Gemini API (via PaLM) enabled ✅ n8n version 1.40.0 or later with relevant credentials configured How to use Import the workflow into n8n. Set up your credentials for: Google Sheets Trigger Google Sheets Vapi.ai (add Bearer token) Google Gemini Replace the placeholder values in: Assistant ID Phone number ID Google Sheet ID and tab Start the workflow and add a row to the Google Sheet. Wait for the automated call and let the AI extract and populate the data. Customising this workflow Replace Google Gemini with OpenAI or Claude if preferred. Add sentiment analysis on the transcript using an LLM. Modify the Sheet column structure to add additional fields. Add a filter node to skip candidates with incomplete phone numbers. Use a Webhook trigger instead of Google Sheets to integrate with job portals or ATS.

Use Case When building a product it's important to discover and eliminate bugs as quickly as possible. Since we're using our product at n8n a lot, we wanted to make it as easy as possible for everyone to add bugs with the needed level of detail. That's why we built this workflow that allows everyone to add bugs to our Linear account easily directly from Slack What this workflow does This workflow waits for a webhook call within Slack, that gets fired when users use the /bug command on a bot that you will create as part of this template. It then adds the bug to Linear using a pre-defined description and a defined label. It then notifies the user about the newly added bug as you can see below: How to create 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 /bug 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 Configure your Slack bot using the sticky to the left Fill the Set me up node. You can find the IDs easily using the Helper nodes section Make sure to exchange the Request URL in your Slack with the Prod URL of the Webhook node before activating this workflow How to adjust it to your needs Add zero, one, two or many labels when creating the new ticket Change the Slack message according to your needs Change the default description for a new bug ticket 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're using AI to classify the bugs and move them to the right team as soon as they get added to Linear (see this template) We also added other commands like /pain and /idea that allow us to submit other things to Notion. You can see the workflow for that here.

This workflow illustrates how to use Perplexity AI in your n8n workflow. Perplexity is a free AI-powered answer engine that provides accurate, trusted, and real-time answers to any question. Credentials Setup 1/ Go to the perplexity dashboard, purchase some credits and create an API Key https://www.perplexity.ai/settings/api 2/ In the perplexity Request node, use Generic Credentials, Header Auth. For the name, use the value "Authorization" And for the value "Bearer pplx-e4...59ea" (Your Perplexity Api Key) AI Model Sonar Pro is the current top model used by perplexity. If you want to use a different one, check this page: https://docs.perplexity.ai/guides/model-cards

Overview Transform your LLM into a powerful GitHub automation specialist with this n8n workflow template. In a world where multiple MCP servers can overwhelm LLMs with context, this streamlined solution provides a dedicated GitHub Agent that handles all GitHub API operations through a single, specialized tool. When you need GitHub operations like creating repositories, managing issues, or handling pull requests, your LLM can make one simple call to the GitHub Agent. This agent specializes exclusively in GitHub MCP server operations, offloading all contextual complexity and providing clean, efficient GitHub automation. ✨ Features Single MCP Server Trigger** - One tool and one parameter to handle all GitHub API interactions Specialized GitHub Agent** - Dedicated AI agent with direct GitHub MCP Server connection Self-Executing Workflow** - "When Executed by Another Workflow" trigger enables seamless workflow chaining Scalable Architecture** - Ready to integrate with unlimited GitHub tools and operations Context Optimization** - Reduces LLM token usage by delegating GitHub complexity to a specialized agent Flexible Request Processing** - Handles any GitHub operation through natural language requests 🎯 Use Cases Repository Management** - Create, clone, and manage repositories programmatically Issue Tracking** - Automate issue creation, updates, and management workflows Pull Request Automation - Streamline code review and merge processes GitHub Actions Integration** - Trigger and monitor CI/CD workflows Team Collaboration** - Automate notifications and team management tasks Documentation Updates** - Automatically update README files and documentation 🏗️ Workflow Architecture Node Breakdown: MCP Server Trigger - Receives requests with GitHub operation parameters Set GitHub Username - Configures GitHub user context for API calls OpenAI Chat Model - Powers the intelligent GitHub agent with contextual understanding Simple Memory - Maintains conversation context and operation history GitHub AI Agent - Specialized Tools Agent with direct GitHub MCP Server access [MCP Server Trigger] → [Set GitHub Username] → [GitHub AI Agent] ↓ [OpenAI Chat Model] ← [Simple Memory] ← [GitHub API Operations] 📋 Requirements Essential Prerequisites: ✅ OpenAI API Key - For AI Agent and Chat Model functionality ✅ GitHub Username Configuration - Edit the "Set GitHub Username" node with your GitHub username for API calls ✅ n8n Version - Compatible with n8n 2024+ releases ✅ MCP Server Setup - Existing GitHub MCP server configuration Recommended Setup: GitHub Personal Access Token with appropriate permissions Basic understanding of n8n workflow configuration Familiarity with GitHub API operations 🚀 Setup Instructions Step 1: Import and Configure Import the workflow template into your n8n instance Navigate to the Set GitHub Username node Replace the placeholder with your actual GitHub username Step 2: API Keys Setup Configure your OpenAI API key in the Chat Model node Ensure your GitHub credentials are properly configured in n8n Test the connection to verify API access Step 3: MCP Server Integration Connect your existing GitHub MCP server to the workflow Verify the MCP Server Trigger is properly configured Test with a simple GitHub operation (e.g., "List my repositories") Step 4: Deploy and Test Activate the workflow in your n8n instance Test with various GitHub operations to ensure functionality Monitor execution logs for any configuration issues 🔧 Customization Options Agent Behavior Modify the Chat Model prompt** to adjust agent personality and response style Configure memory settings** to control conversation context retention Adjust timeout settings** for long-running GitHub operations GitHub Operations Extend supported operations** by adding new GitHub API endpoints Configure repository filters** to limit scope of operations Set up notification preferences** for important GitHub events Integration Points Webhook triggers** for real-time GitHub event processing Scheduled operations** for regular repository maintenance Cross-workflow triggers** for complex automation chains 💡 Pro Tips Start Simple**: Begin with basic operations like repository listing before attempting complex workflows Monitor Token Usage**: The specialized agent approach significantly reduces OpenAI API costs Batch Operations**: Group related GitHub operations in single requests for efficiency Error Handling**: The agent provides detailed error messages for troubleshooting 🤝 Support and Community Documentation**: Official n8n Documentation Community Forum**: n8n Community Issues & Contributions**: Feel free to suggest improvements or report issues 📄 License This workflow template is provided under the MIT License. You're free to use, modify, and redistribute with attribution. Created by: William Lettieri Version: 1.0 Last Updated: May 28, 2025 Compatibility: n8n 2024+

Automatically convert documents from Google Drive into vector embeddings using OpenAI, LangChain, and PGVector — fully automated through n8n. ⚙️ What It Does This workflow monitors a Google Drive folder for new files, supports multiple file types (PDF, TXT, JSON), and processes them into vector embeddings using OpenAI’s text-embedding-3-small model. These embeddings are stored in a Postgres database using the PGVector extension, making them query-ready for semantic search or RAG-based AI agents. After successful processing, files are moved to a separate “vectorized” folder to avoid duplication. 💡 Use Cases Powering Retrieval-Augmented Generation (RAG) AI agents Semantic search across private documents AI assistant knowledge ingestion Automated document pipelines for indexing or classification 🧠 Workflow Highlights Trigger Options:** Manual or Scheduled (3 AM daily by default) Supported File Types:** PDF, TXT, JSON Embedding Stack:** LangChain Text Splitter, OpenAI Embeddings, PGVector Deduplication:** Files are moved after processing License:** CC BY-SA 4.0 Author:** AlexK1919 🛠 What You’ll Need Google Drive OAuth2** credentials (connected to Search Folder, Download File, and Move File nodes) OpenAI API Key** (used in the Embeddings OpenAI node) Postgres + PGVector** database (connected in the Postgres PGVector Store node) 🔧 Step-by-Step Setup Instructions Create Google OAuth2 credentials in n8n and connect them to all Google Drive nodes. Set your source folder ID in the Search Folder node — this is where incoming files are placed. Set your processed folder ID in the Move File node — files will be moved here after vectorization. Ensure you have a PGVector-enabled Postgres instance and input the table name and collection in the Postgres PGVector Store node. Add your OpenAI credentials to the Embeddings OpenAI node and select text-embedding-3-small. Optional: Activate the Schedule Trigger node to run daily or configure your own schedule. Run manually by triggering When clicking ‘Test workflow’ for on-demand ingestion. 🧩 Customization Tips Want to support more file types or enhance the pipeline? Add new extractors**: Use Extract from File with other formats like DOCX, Markdown, or HTML. Refine logic by file type**: The Switch node routes files to the correct extraction method based on MIME type (application/pdf, text/plain, application/json). Pre-process with OCR**: Add an OCR step before extraction to handle scanned PDFs or images. Add filters**: Enhance the Search Folder or Switch node logic to skip specific files or folders. 📄 License This workflow is available under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license. You are free to use, adapt, and share this workflow for non-commercial purposes under the terms of this license. Full license details: https://creativecommons.org/licenses/by-nc-sa/4.0/

🤖 Create a Telegram Bot with Mistral AI and Conversation Memory A sophisticated Telegram bot that provides AI-powered responses with conversation memory. This template demonstrates how to integrate any AI API service with Telegram, making it easy to swap between different AI providers like OpenAI, Anthropic, Google AI, or any other API-based AI model. 🔧 How it works The workflow creates an intelligent Telegram bot that: 💬 Maintains conversation history for each user 🧠 Provides contextual AI responses using any AI API service 📱 Handles different message types and commands 🔄 Manages chat sessions with clear functionality 🔌 Easily adaptable to any AI provider (OpenAI, Anthropic, Google AI, etc.) ⚙️ Set up steps 📋 Prerequisites 🤖 Telegram Bot Token (from @BotFather) 🔑 AI API Key (from any AI service provider) 🚀 n8n instance with webhook capability 🛠️ Configuration Steps 🤖 Create Telegram Bot Message @BotFather on Telegram Create new bot with /newbot command Save the bot token for credentials setup 🧠 Choose Your AI Provider OpenAI: Get API key from OpenAI platform Anthropic: Sign up for Claude API access Google AI: Get Gemini API key NVIDIA: Access LLaMA models Hugging Face: Use inference API Any other AI API service 🔐 Set up Credentials in n8n Add Telegram API credentials with your bot token Add Bearer Auth/API Key credentials for your chosen AI service Test both connections 🚀 Deploy Workflow Import the workflow JSON Customize the AI API call (see customization section) Activate the workflow Set webhook URL in Telegram bot settings ✨ Features 🚀 Core Functionality 📨 Smart Message Routing**: Automatically categorizes incoming messages (commands, text, non-text) 🧠 Conversation Memory**: Maintains chat history for each user (last 10 messages) 🤖 AI-Powered Responses**: Integrates with any AI API service for intelligent replies ⚡ Command Support**: Built-in /start and /clear commands 📱 Message Types Handled 💬 Text Messages**: Processed through AI model with context 🔧 Commands**: Special handling for bot commands ❌ Non-text Messages**: Polite error message for unsupported content 💾 Memory Management 👤 User-specific chat history storage 🔄 Automatic history trimming (keeps last 10 messages) 🌐 Global state management across workflow executions 🤖 Bot Commands /start 🎯 - Welcome message with bot introduction /clear 🗑️ - Clears conversation history for fresh start Regular text 💬 - Processed by AI with conversation context 🔧 Technical Details 🏗️ Workflow Structure 📡 Telegram Trigger - Receives all incoming messages 🔀 Message Filtering - Routes messages based on type/content 💾 History Management - Maintains conversation context 🧠 AI Processing - Generates intelligent responses 📤 Response Delivery - Sends formatted replies back to user 🤖 AI API Integration (Customizable) Current Example (NVIDIA): Model: mistralai/mistral-nemotron Temperature: 0.6 (balanced creativity) Max tokens: 4096 Response limit: Under 200 words 🔄 Easy to Replace with Any AI Service: OpenAI Example: { "model": "gpt-4", "messages": [...], "temperature": 0.7, "max_tokens": 1000 } Anthropic Claude Example: { "model": "claude-3-sonnet-20240229", "messages": [...], "max_tokens": 1000 } Google Gemini Example: { "contents": [...], "generationConfig": { "temperature": 0.7, "maxOutputTokens": 1000 } } 🛡️ Error Handling ❌ Non-text message detection and appropriate responses 🔧 API failure handling ⚠️ Invalid command processing 🎨 Customization Options 🤖 AI Provider Switching To use a different AI service, modify the "NVIDIA LLaMA Chat Model" node: 📝 Change the URL in HTTP Request node 🔧 Update the request body format in "Prepare API Request" node 🔐 Update authentication method if needed 📊 Adjust response parsing in "Save AI Response to History" node 🧠 AI Behavior 📝 Modify system prompt in "Prepare API Request" node 🌡️ Adjust temperature and response parameters 📏 Change response length limits 🎯 Customize model-specific parameters 💾 Memory Settings 📊 Adjust history length (currently 10 messages) 👤 Modify user identification logic 🗄️ Customize data persistence approach 🎭 Bot Personality 🎉 Update welcome message content ⚠️ Customize error messages and responses ➕ Add new command handlers 💡 Use Cases 🎧 Customer Support**: Automated first-line support with context awareness 📚 Educational Assistant**: Homework help and learning support 👥 Personal AI Companion**: General conversation and assistance 💼 Business Assistant**: FAQ handling and information retrieval 🔬 AI API Testing**: Perfect template for testing different AI services 🚀 Prototype Development**: Quick AI chatbot prototyping 📝 Notes 🌐 Requires active n8n instance for webhook handling 💰 AI API usage may have rate limits and costs (varies by provider) 💾 Bot memory persists across workflow restarts 👥 Supports multiple concurrent users with separate histories 🔄 Template is provider-agnostic - easily switch between AI services 🛠️ Perfect starting point for any AI-powered Telegram bot project 🔧 Popular AI Services You Can Use | Provider | Model Examples | API Endpoint Style | |----------|---------------|-------------------| | 🟢 OpenAI | GPT-4, GPT-3.5 | https://api.openai.com/v1/chat/completions | | 🔵 Anthropic | Claude 3 Opus, Sonnet | https://api.anthropic.com/v1/messages | | 🔴 Google | Gemini Pro, Gemini Flash | https://generativelanguage.googleapis.com/v1beta/models/ | | 🟡 NVIDIA | LLaMA, Mistral | https://integrate.api.nvidia.com/v1/chat/completions | | 🟠 Hugging Face | Various OSS models | https://api-inference.huggingface.co/models/ | | 🟣 Cohere | Command, Generate | https://api.cohere.ai/v1/generate | Simply replace the HTTP Request node configuration to switch providers!

Use Case Turn any web page into a compelling LinkedIn post — complete with an AI-generated image. This automation is ideal for sharing content like blog posts, case studies, or product updates in a polished and engaging format. What This Automation Does Given a page URL and optional user instructions, this automation: Scrapes the content of the webpage Uses AI to write a clear, educational, and LinkedIn-optimized post Sends both to Slack for review and approval Handles feedback and revisions via Slack interactions Input: Page URL** — The link to the webpage (required) Instructions** — Optional notes on tone, emphasis, or format Output: LinkedIn post text Slack message with review/approval options How It Works Form Submission: User inputs a web page and optional instructions. Web Scraping: Uses Airtop to extract page content. Post Generation: AI agent writes a post based on the page and instructions. Slack Review Flow: Post and image sent to Slack for feedback User can approve, request revisions, or decline Revisions trigger reprocessing steps automatically Final Post Delivery: Approved post is sent back to Slack, ready to publish. Setup Requirements Generate an Airtop API key completely free. Configure your OpenAI credentials for post and image prompt generation Slack OAuth credentials and a Slack channel Next Steps Post Directly**: Add LinkedIn publishing to automate the full content workflow. Template Variations**: Offer post style presets (e.g., technical, story-driven, short-form). CRM Sync**: Save approved posts and stats in Airtable or Notion for team use. Read more about generating social content using AI

Generate new keywords for SEO with the monthly Search volumes This workflow is an improvement on the workflows below. It can be used to generate new keywords that you can use for your SEO campaigns or Google ads campaigns Generate SEO Keyword Search Volume Data using Google API and Generating Keywords using Google Autosuggest Usage Send the keywords you need as an array to this workflow Pin the data and map it to the set Keywords node Map the keywords to the Google ads API with the location and Language of your choice Split the results and set them data Pass this to the next nodes as needed for storage Make a copy of this spreedsheet and update the data accordingly Having challenges with the google Ads API? Read this blog Setup Replace the trigger with your desired trigger eg a webhook or manual trigger Map the data correctly to the set Keywords node On the Generate new keywords, Update the {customer_id} on the url and login-customer-id with your actual one. Update the developer-token` also with your values. The url should be corrected as below https://googleads.googleapis.com/v18/customers/{customer-id}:generateKeywordIdeas You should send the headers as below { "name": "content-type", "value": "application/json" }, { "name": "developer-token", "value": "5j-tyzivCNmiCcoW-xkaxw" }, { "name": "login-customer-id", "value": "513554 " } and the json body should take the following format { "geoTargetConstants": ["geoTargetConstants/2840"], "includeAdultKeywords": false, "pageToken": "", "pageSize": 2, "keywordPlanNetwork": "GOOGLE_SEARCH", "language": "languageConstants/1000", "keywordSeed": { "keywords": {{ $json.Keyword }} } } Troubleshooting If you get an error with the workflow, check the credentials you are using Check the account you are using eg the right customer id and developer token Follow the guide on the blog to set up your Google ads account Made by @Imperol

Who this is for? Google SERP Tracker + Trends and Recommendations is an AI-powered n8n workflow that extracts Google search results via Bright Data, parses them into structured JSON using Google Gemini, and generates actionable recommendations and search trends. It outputs CSV reports and sends real-time Webhook notifications. This workflow is ideal for: SEO Agencies needing automated rank & trend tracking Growth Marketers seeking daily/weekly search-based insights Product Teams monitoring brand or competitor visibility Market Researchers performing search behavior analysis No-code Builders automating search intelligence workflows What problem is this workflow solving? Traditional tracking of search engine rankings and search trends is often fragmented and manual. Analyzing SERP changes and trends requires: Manual extraction or using unstable scrapers Unstructured or cluttered HTML data Lack of actionable insights or recommendations This workflow solves the problem by: Automating real-time Google SERP data extraction using Bright Data Structuring unstructured search data using Google Gemini LLM Generating actionable recommendations and trends Exporting both CSV reports automatically to disk for downstream use Notifying external systems via Webhook What this workflow does Accepts search input, zone name, and webhook notification URL Uses Bright Data to extract Google Search Results Uses Google Gemini LLM to parse the SERP data into structured JSON Loops over structured results to: Extract recommendations Extract trends Saves both as .csv files (example below): Google_SERP_Recommendations_Response_2025-06-10T23-01-50-650Z.csv Google_SERP_Trends_Response_2025-06-10T23-01-38-915Z.csv Sends a Webhook with the summary or file reference LLM Usage Google Gemini LLM handles: Parsing Google Search HTML into structured JSON Summarizing recommendation data Deriving trends from the extracted SERP metadata 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. A Google Gemini API key (or access through Vertex AI or proxy). Update the Set input fields with the search criteria, Bright Data Zone name, Webhook notification URL. How to customize this workflow to your needs Input Customization Set your target keyword/phrase in the search field Add your webhook_notification_url for external triggers or notifications SERP Source You can extend the Bright Data search logic to include other engines like Bing or DuckDuckGo. Output Format Edit the .csv structure in the Convert to File nodes if you want to include/exclude specific columns. LLM Prompt Tuning The Gemini LLM prompt inside the Recommendation or Trends extractor nodes can be fine-tuned for domain-specific insight (e.g., SEO vs eCommerce focus).

Deep Multiline Icebreaker System (AI-Powered Cold Email Personalization) Categories: Lead Generation, AI Marketing, Sales Automation This workflow creates an advanced AI-powered cold email personalization system that achieves 5-10% reply rates by generating deeply personalized multi-line icebreakers. The system scrapes comprehensive website data, analyzes multiple pages per prospect, and uses advanced AI prompting to create custom email openers that make recipients believe you've personally researched their entire business. Benefits Superior Response Rates** - Achieves 5-10% reply rates vs. 1-2% for standard cold email campaigns Deep Website Intelligence** - Scrapes and analyzes multiple pages per prospect, not just homepages Advanced AI Personalization** - Uses sophisticated prompting techniques with examples and formatting rules Complete Lead Pipeline** - From Apollo search to personalized icebreakers in Google Sheets Scalable Processing** - Handle hundreds of prospects with intelligent batching and error handling Revenue-Focused Approach** - System designed around proven $72K/month agency methodologies How It Works Apollo Lead Acquisition: Integrates directly with Apollo.io search URLs through Apify scraper Processes 500+ leads per search with comprehensive contact data Filters for prospects with both email addresses and accessible websites Multi-Page Website Scraping: Scrapes homepage to extract all internal website links Processes relative URLs and filters out external/irrelevant links Performs intelligent batching to prevent IP blocking during scraping Comprehensive Content Analysis: Converts HTML to markdown for efficient AI processing Uses GPT-4 to generate detailed abstracts of each webpage Aggregates insights from multiple pages into comprehensive prospect profiles Advanced AI Icebreaker Generation: Employs sophisticated prompting with system messages, examples, and formatting rules Uses proven icebreaker templates that reference non-obvious website details Generates personalized openers that imply deep manual research Smart Data Processing: Removes duplicate URLs and handles scraping errors gracefully Implements token limits to control AI processing costs Organizes final output in structured Google Sheets format Required Google Sheets Setup Create a Google Sheet with these exact tab and column structures: Search URLs Tab: URL - Contains Apollo.io search URLs for your target audiences Leads Tab (Output): first_name - Contact's first name last_name - Contact's last name email - Contact's email address website_url - Company website URL headline - Job title/position location - Geographic location phone_number - Contact phone (if available) multiline_icebreaker - AI-generated personalized opener Setup Instructions: Create Google Sheet with "Search URLs" and "Leads" tabs Add your Apollo search URLs to the first tab (one per row) Connect Google Sheets OAuth credentials in n8n Update the Google Sheets document ID in all sheet nodes The workflow reads from Search URLs and outputs to Leads automatically Apollo Search URL Format: Your search URLs should look like: https://app.apollo.io/#/people?personLocations[]=United%20States&personTitles[]=ceo&qKeywords=marketing%20agency&page=1 Business Use Cases AI Automation Agencies** - Generate high-converting prospect outreach for service-based businesses B2B Sales Teams** - Create personalized cold email campaigns that actually get responses Marketing Agencies** - Offer premium personalization services to clients Consultants** - Build authority through deeply researched prospect outreach SaaS Companies** - Improve demo booking rates through personalized messaging Professional Services** - Stand out from generic sales emails with custom insights Revenue Potential This system transforms cold email economics: 5-10x Higher Response Rates** than standard cold email approaches $72K/month proven methodology** - exact system used to scale successful AI agency Premium Positioning** - prospects assume you've done extensive manual research Scalable Personalization** - process hundreds of prospects daily vs. manual research Difficulty Level: Advanced Estimated Build Time: 3-4 hours Monthly Operating Cost: ~$150 (Apollo + Apify + OpenAI + Email platform APIs) Watch My Complete Live Build Want to see me build this entire deep personalization system from scratch? I walk through every component live - including the AI prompting strategies, website scraping logic, error handling, and the exact techniques that generate 5-10% reply rates. 🎥 See My Live Build Process: "I Deep-Personalized 1000+ Cold Emails Using THIS AI System (FREE TEMPLATE)" This comprehensive tutorial shows the real development process - including advanced AI prompting, multi-page scraping architecture, and the proven icebreaker templates that have generated over $72K/month in agency revenue. Set Up Steps Apollo & Apify Integration: Configure Apify account with Apollo scraper access Set up API credentials and test lead extraction Define target audience parameters and lead qualification criteria Google Sheets Database Setup: Create multi-sheet structure (Search URLs, Leads) Configure proper column mappings for lead data Set up Google Sheets API credentials and permissions Website Scraping Infrastructure: Configure HTTP request nodes with proper redirect handling Set up error handling for websites that can't be scraped Implement intelligent batching with split-in-batches nodes AI Content Processing: Set up OpenAI API credentials with appropriate rate limits Configure dual-AI approach (page summarization + icebreaker generation) Implement token limiting to control processing costs Advanced Icebreaker Generation: Configure sophisticated AI prompting with system messages Set up example-based learning with input/output pairs Implement formatting rules for natural-sounding personalization Quality Control & Testing: Test complete workflow with small prospect batches Validate AI output quality and personalization accuracy Monitor response rates and optimize messaging templates Advanced Optimizations Scale the system with: Industry-Specific Templates:** Customize icebreaker formats for different verticals A/B Testing Framework:** Test different AI prompt variations and templates CRM Integration:** Automatically add qualified responders to sales pipelines Response Tracking:** Monitor which personalization elements drive highest engagement Multi-Touch Sequences:** Create follow-up campaigns based on initial response data Important Considerations AI Token Management:** System includes intelligent token limiting to control OpenAI costs Scraping Ethics:** Built-in delays and error handling prevent website overload Data Quality:** Filtering logic ensures only high-quality prospects with accessible websites Scalability:** Batch processing prevents IP blocking during high-volume scraping Why This System Works The key to 5-10% reply rates lies in making prospects believe you've done extensive manual research: Non-obvious details from deep website analysis Natural language patterns that avoid template detection Company name abbreviation (e.g., "Love AMS" vs "Love AMS Professional Services") Multiple page insights aggregated into compelling narratives Check Out My Channel For more advanced automation systems and proven business-building strategies that generate real revenue, explore my YouTube channel where I share the exact methodologies used to build successful automation agencies.

🧩 Jamf Patch Summary to Slack Stay on top of software patch compliance by automatically posting Jamf patch summaries to Slack. This helps IT and security teams quickly identify outdated installs and take action—without logging into Jamf. ✅ Prerequisites • A Jamf Pro API key with permissions to read software titles and patch summary • A Slack app or incoming webhook URL with permission to post messages to your desired channel 🔍 How it works • Manually trigger the flow or Add a webhook • Fetch a list of software titles from Jamf Pro • Filter to select the software you're tracking (e.g. Chrome, Edge) • Retrieve the patch summary for that software (latest version, up-to-date, out-of-date counts) • Format the summary into Slack Block Kit • Post the formatted summary into a Slack channel ⚙️ Set up steps • Takes ~5–10 minutes to configure • Set your server BaseURL variable in the Set Node • Add your Jamf Pro API credentials in the HTTP Request nodes (Get & Retrieve) • Set the target software ID in the Filter node • Add your Slack webhook URL or token in the final HTTP node • Optional: Adjust Slack formatting inside the Function node

🎵 TikTok Post Scraper via Keywords | Bright Data + Sheets Integration 📝 Workflow Description Automatically scrapes TikTok posts based on keyword search using Bright Data API and stores comprehensive data in Google Sheets for analysis and monitoring. 🔄 How It Works This workflow operates through a simple, automated process: Keyword Input:** User submits search keywords through a web form Data Scraping:** Bright Data API searches TikTok for posts matching the keywords Processing Loop:** Monitors scraping progress and waits for completion Data Storage:** Automatically saves all extracted data to Google Sheets Result Delivery:** Provides comprehensive post data including metrics, user info, and media URLs ⏱️ Setup Information Estimated Setup Time: 10-15 minutes This includes importing the workflow, configuring credentials, and testing the integration. Most of the process is automated once properly configured. ✨ Key Features 📝 Keyword-Based Search Search TikTok posts using specific keywords 📊 Comprehensive Data Extraction Captures post metrics, user profiles, and media URLs 📋 Google Sheets Integration Automatically organizes data in spreadsheets 🔄 Automated Processing Handles scraping progress monitoring 🛡️ Reliable Scraping Uses Bright Data's professional infrastructure ⚡ Real-time Updates Live status monitoring and data processing 📊 Data Extracted | Field | Description | Example | |-------|-------------|---------| | url | TikTok post URL | https://www.tiktok.com/@user/video/123456 | | post_id | Unique post identifier | 7234567890123456789 | | description | Post caption/description | Check out this amazing content! #viral | | digg_count | Number of likes | 15400 | | share_count | Number of shares | 892 | | comment_count | Number of comments | 1250 | | play_count | Number of views | 125000 | | profile_username | Creator's username | @creativity_master | | profile_followers | Creator's follower count | 50000 | | hashtags | Post hashtags | #viral #trending #fyp | | create_time | Post creation timestamp | 2025-01-15T10:30:00Z | | video_url | Direct video URL | https://video.tiktok.com/tos/... | 🚀 Setup Instructions Step 1: Prerequisites n8n instance (self-hosted or cloud) Bright Data account with TikTok scraping dataset access Google account with Sheets access Basic understanding of n8n workflows Step 2: Import Workflow Copy the provided JSON workflow code In n8n: Go to Workflows → + Add workflow → Import from JSON Paste the JSON code and click Import The workflow will appear in your n8n interface Step 3: Configure Bright Data In n8n: Navigate to Credentials → + Add credential → Bright Data API Enter your Bright Data API credentials Test the connection to ensure it's working Update the workflow nodes with your dataset ID: gd_lu702nij2f790tmv9h Replace BRIGHT_DATA_API_KEY with your actual API key Step 4: Configure Google Sheets Create a new Google Sheet or use an existing one Copy the Sheet ID from the URL In n8n: Credentials → + Add credential → Google Sheets OAuth2 API Complete OAuth setup and test connection Update the Google Sheets node with your Sheet ID Ensure the sheet has a tab named "Tiktok by keyword" Step 5: Test the Workflow Activate the workflow using the toggle switch Access the form trigger URL to submit a test keyword Monitor the workflow execution in n8n Verify data appears in your Google Sheet Check that all fields are populated correctly ⚙️ Configuration Details Bright Data API Settings Dataset ID:** gd_lu702nij2f790tmv9h Discovery Type:** discover_new Search Method:** keyword Results per Input:** 2 posts per keyword Include Errors:** true Workflow Parameters Wait Time:** 1 minute between status checks Status Check:** Monitors until scraping is complete Data Format:** JSON response from Bright Data Error Handling:** Automatic retry on incomplete scraping 📋 Usage Guide Running the Workflow Access the form trigger URL provided by n8n Enter your desired keyword (e.g., "viral dance", "cooking tips") Submit the form to start the scraping process Wait for the workflow to complete (typically 2-5 minutes) Check your Google Sheet for the extracted data Best Practices Use specific, relevant keywords for better results Monitor your Bright Data usage to stay within limits Regularly backup your Google Sheets data Test with simple keywords before complex searches Review extracted data for accuracy and completeness 🔧 Troubleshooting Common Issues 🚨 Scraping Not Starting Verify Bright Data API credentials are correct Check dataset ID matches your account Ensure sufficient credits in Bright Data account 🚨 No Data in Google Sheets Confirm Google Sheets credentials are authenticated Verify sheet ID is correct Check that the "Tiktok by keyword" tab exists 🚨 Workflow Timeout Increase wait time if scraping takes longer Check Bright Data dashboard for scraping status Verify keyword produces available results 📈 Use Cases Content Research Research trending content and hashtags in your niche to inform your content strategy. Competitor Analysis Monitor competitor posts and engagement metrics to understand market trends. Influencer Discovery Find influencers and creators in specific topics or industries. Market Intelligence Gather data on trending topics, hashtags, and user engagement patterns. 🔒 Security Notes Keep your Bright Data API credentials secure Use appropriate Google Sheets sharing permissions Monitor API usage to prevent unexpected charges Regularly rotate API keys for better security Comply with TikTok's terms of service and data usage policies 🎉 Ready to Use! Your TikTok scraper is now configured and ready to extract valuable data. Start with simple keywords and gradually expand your research as you become familiar with the workflow. Need Help? Visit the n8n community forum or check the Bright Data documentation for additional support and advanced configuration options. For any questions or support, please contact: Email or fill out this form