# templates

name: Automatically Enrich Salesforce Accounts with Web Crawling, LinkedIn Data, GPT
author_name: Le Nguyen
author_username: leeseifer
categories: []
created_at: 2025-07-28T15:22:52.165Z
updated_at: 2025-07-28T15:22:52.165Z
url: https://n8n.io/workflows/6586
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Crawl the web, mine LinkedIn, think with GPT, and auto‑enrich Salesforce—all inside n8n.

  🔧 How It Works (High-Level)

  Listen – Trigger on new Salesforce Accounts.  
  Discover – Crawl the company site (depth-limited) + grab/parse LinkedIn.  
  Distill – GPT (JSON mode) returns a clean insight object + HTML summary.  
  Enrich – Update the Account record in Salesforce automatically.

  🛠 Setup Steps (≈15–25 minutes)

  Import the workflow JSON into n8n.  
  Connect Credentials: Salesforce OAuth2 + OpenAI API key.  
  Tune Settings: Set maxDepth (default = 1), confirm the model (e.g., gpt‑4o).  
  Test with a sample Account to verify crawl + update.  
  Enable Trigger and let it run.

  💼 Business Impact

  Zero manual research**: Insights appear in Salesforce instantly.  
  Consistent data**: Unified JSON schema + confidence rating.  
  Faster qualification**: Reps see services, size, HQ, etc., without leaving SF.  
  Scalable & automated**: Works 24/7 on every new Account.  
  AI-ready outputs**: Raw JSON for automations, HTML for dashboards/Lightning.

  🌟 Optional Enhancements

  Push insights to Slack/Teams.  
  Auto-create tasks if rating &lt; 60 or data missing.  
  Archive raw HTML to S3 for audits.

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.salesforceTrigger","n8n-nodes-base.salesforce","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.httpRequest","n8n-nodes-base.html","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.html","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.splitInBatches","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.salesforce","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["CRM","Data Enrichment","Marketing","Automation","AI/ML"],"complexity":"medium","use_cases":["Enrich customer accounts","Gather company insights","Parse LinkedIn profiles","Auto-update CRM data","Generate content summaries"],"estimated_setup_minutes":20,"required_services":["Salesforce","OpenAI","LinkedIn","General web crawler"],"key_features":["Web crawling and scraping","LinkedIn data extraction","AI content summarization","Automated CRM updates","JSON mode LLM output"],"target_audience":["sales reps","marketing managers","data analysts"]}


name: Automated Upwork Messages Alerts to Slack with Gmail and Google Gemini AI
author_name: Zain Khan
author_username: zain
categories: []
created_at: 2025-07-28T21:32:29.089Z
updated_at: 2025-07-28T21:32:29.089Z
url: https://n8n.io/workflows/6600
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:21
description:
  Upwork Messages Notifications (Gmail to Slack) - Fully Automated Alerts

  This n8n workflow streamlines how you receive Upwork client messages, sending instant notifications to Slack. It demonstrates two approaches: a code-based extraction and an AI-powered one with Google Gemini.

  Use Cases

  Instant Communication:** Get real-time alerts for new Upwork client messages in your team's Slack channel.
  Improved Responsiveness:** Quickly respond to client inquiries and maintain strong communication.
  Centralized Notifications:** Keep all your essential work-related notifications in one place.

  Good to Know

  The workflow is set to poll your Gmail every 3 minutes for unread Upwork messages, which can be reduced or increased.
  The AI Information Extractor with Google Gemini provides a more refined and robust method for data parsing compared to custom code.
  Usage of Google Gemini may incur costs. Refer to Gemini Pricing for updated information.
  Google Gemini models can be geo-restricted. If you encounter a "model not found" error, it might not be available in your region.

  How it Works

  Method 1: Code-Based Extraction

  Gmail Trigger: The workflow starts by monitoring your Gmail for new, unread emails from "via Upwork".
  Code Node: A custom JavaScript code block is used to extract the client's name and the message content directly from the email's text.
  Slack Notification: The extracted client name and message are then formatted and sent as a new message to a designated Slack channel.

  Method 2: AI-Powered Extraction with Google Gemini (Recommended)

  Gmail Trigger X: Similar to Method 1, this part also triggers on new unread Upwork emails.
  Information Extractor (AI): This powerful node, powered by Google Gemini, takes the entire email text and intelligently extracts structured information like the "client" name and the "message" content based on a defined schema. This method is more robust and requires less manual parsing logic.
  Google Gemini Chat Model: (Implicitly used by the Information Extractor) This node provides the underlying AI capabilities for intelligent information extraction.
  Send to Slack X: The refined output from the AI Information Extractor (client name and message) is then sent to a Slack channel.

  How to Use

  Gmail Credentials: Ensure you have configured your Gmail OAuth2 credentials in n8n for both "Gmail Trigger" nodes.
  Slack Credentials: Set up your Slack OAuth2 credentials in n8n for both "Send to Slack" nodes and select the desired Slack channel.
  Google Gemini Credentials: For the AI-powered workflow, you'll need to set up your Google Gemini API key as a credential in n8n.
  Activate Workflows: Enable both workflows in n8n to start receiving notifications. You can compare the output quality of each method.

  Requirements

  n8n instance** (self-hosted or cloud)
  Gmail Account** connected to Upwork notifications.
  Slack Workspace** and a designated channel for notifications.
  Google Gemini API key** for the AI-powered extraction workflow.

nodes_used:
  ["n8n-nodes-base.gmailTrigger","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.informationExtractor","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.gmailTrigger","n8n-nodes-base.slack","n8n-nodes-base.slack"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["Communication"],"complexity":"medium","use_cases":["receive real-time client notifications","alert team on new Upwork messages","integrate freelance platforms with team communication"],"estimated_setup_minutes":20,"required_services":["Upwork","Slack","Gmail","Google Gemini"],"key_features":["ai-powered message extraction","code-based extraction logic","multichannel notification distribution"],"target_audience":["freelancers","communication managers","operations leads"]}


name: Automate Browser Tasks with Airtop & GPT-4 - Reddit Posting Example
author_name: Joseph
author_username: mjomba
categories: []
created_at: 2025-07-29T13:20:24.335Z
updated_at: 2025-07-29T13:20:24.335Z
url: https://n8n.io/workflows/6638
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Overview

  This n8n workflow creates an intelligent AI agent that automates browser interactions through Airtop's browser automation platform. The agent can control real browser sessions, navigate websites, interact with web elements, and maintain detailed session records - all while providing live viewing capabilities for real-time monitoring.

  Youtube Tutorial: https://www.youtube.com/watch?v=XoZqFY7QFps

  What This Workflow Does

  The AI agent acts as your virtual assistant in the browser, capable of:

  Session Management**: Creates, monitors, and terminates browser sessions with proper tracking
  Web Navigation**: Visits websites, clicks elements, fills forms, and performs complex interactions
  Multi-Window Support**: Manages multiple browser windows within sessions
  Live Monitoring**: Provides real-time viewing URLs so you can watch the automation
  Data Tracking**: Maintains comprehensive records of all browser activities
  Profile Integration**: Uses Airtop profiles for authenticated sessions
  Email Notifications**: Sends live URLs and status updates via Gmail

  Demo Use Case: Automated Reddit Posting

  The tutorial demonstrates the agent's capabilities by:

  Logging into Reddit using pre-configured Airtop profile credentials
  Navigating to a specific subreddit based on user input
  Creating and publishing a new post with title and content
  Tracking the entire process with detailed session records
  Providing live viewing access throughout the automation

  Core Workflow Components

  1. Chat Interface Trigger
  Node Type**: Chat Trigger
  Purpose**: Accepts user commands for browser automation tasks
  Input**: Natural language instructions (e.g., "Create a Reddit post in r/automation")

  2. AI Agent Processing
  Node Type**: OpenAI GPT-4
  Purpose**: Interprets user requests and determines appropriate browser actions
  System Message**: Contains the comprehensive agent instructions from your documentation
  Capabilities**:
    Understands complex web interaction requests
    Plans multi-step browser workflows
    Manages session states intelligently
    Handles error scenarios gracefully

  3. Google Sheets Data Management
  Multiple Google Sheets nodes manage different aspects of session tracking:

  Browser Sessions Sheet
  Fields**: session_id, description, status, created_date
  Purpose**: Tracks active browser sessions
  Operations**: Create, read, update session records

  Window Sessions Sheet  
  Fields**: session_id, window_id, description, airtop_live_view_url, status
  Purpose**: Tracks individual browser windows within sessions
  Operations**: Create, read, update window records

  Airtop Profiles Sheet
  Fields**: platform_name, platform_url, profile_name
  Purpose**: Stores available authenticated profiles
  Operations**: Read available profiles for session creation

  4. Airtop Browser Automation Nodes
  Multiple specialized nodes for browser control:

  Session Management
  create_session**: Creates new browser sessions with optional profile authentication
  terminate_session**: Closes browser sessions and updates records
  read_airtop_profiles**: Retrieves available authentication profiles

  Window Management
  create_window**: Opens new browser windows with specified URLs
  query_page**: Analyzes page content and identifies interactive elements

  Web Interaction
  click_element**: Clicks specific page elements based on AI descriptions
  type_text**: Inputs text into form fields and input elements

  5. Gmail Integration
  Node Type**: Gmail Send
  Purpose**: Sends live viewing URLs and status updates
  Recipients**: User email for real-time monitoring
  Content**: Complete Airtop live view URLs for browser session observation

  6. Error Handling & Validation
  Input Validation**: Ensures required parameters are present
  Session State Checks**: Verifies browser session status before operations
  Error Recovery**: Handles failed operations gracefully
  Data Consistency**: Maintains accurate session records even during failures

  Technical Requirements

  API Credentials Needed
  Airtop.ai API Key
     Sign up at airtop.ai
     Generate API key from dashboard
     Required for all browser automation functions

  OpenAI API Key
     OpenAI account with GPT-4 access
     Required for AI agent intelligence and decision-making

  Google Sheets Access
     Google account with Google Sheets API access
     Copy the provided template and get your sheet URL
     Required for session and profile data management

  Gmail OAuth
     Google account with Gmail API access
     Required for sending live viewing URLs and notifications

  Airtable Base Structure
  Create three tables in your Airtable base:

  1. Browser Details (Sessions)
  session_id (Single line text)
  description (Single line text)
  status (Single select: Open, Closed)
  created_date (Date)

  2. Window Details (Windows)
  session_id (Single line text)
  window_id (Single line text)
  description (Single line text)
  airtop_live_view_url (URL)
  status (Single select: Open, Closed)

  3. Airtop Profiles
  platform_name (Single line text)
  platform_url (URL)
  profile_name (Single line text)

  Workflow Logic Flow

  User Request Processing
  User Input: Natural language command via chat interface
  AI Analysis: OpenAI processes request and determines required actions
  Session Check: Agent reads current browser session status
  Action Planning: AI creates step-by-step execution plan

  Browser Session Lifecycle
  Session Creation:
     Check for existing open sessions
     Ask user about profile usage if needed
     Create new Airtop session
     Record session details in Airtable

  Window Management:
     Create browser window with target URL
     Capture live viewing URL
     Record window details in Airtable
     Send live URL via Gmail

  Web Interactions:
     Query page content for element identification
     Execute clicks, form fills, navigation
     Monitor page state changes
     Handle dynamic content loading

  Session Cleanup:
     Terminate browser session when complete
     Update all related records to "Closed" status
     Send completion notification

  Data Flow Architecture
  User Input → AI Processing → Session Management → Browser Actions → Data Recording → User Notifications

  Key Features & Benefits

  Intelligent Automation
  Natural Language Control**: Users can describe tasks in plain English
  Context Awareness**: AI understands complex multi-step workflows
  Adaptive Responses**: Handles unexpected page changes and errors
  Profile Integration**: Seamlessly uses stored authentication credentials

  Real-Time Monitoring
  Live View URLs**: Watch browser automation as it happens
  Status Updates**: Real-time notifications of task progress
  Session Tracking**: Complete audit trail of all browser activities
  Multi-Window Support**: Handle complex workflows across multiple tabs

  Enterprise-Ready Features
  Error Recovery**: Robust handling of network issues and page failures
  Session Persistence**: Maintains state across workflow interruptions
  Data Integrity**: Consistent record-keeping even during failures
  Scalable Architecture**: Can handle multiple concurrent automation tasks

  Use Cases Beyond Reddit

  This workflow architecture supports automation for any website:

  Social Media Management
  Multi-platform posting**: Facebook, Twitter, LinkedIn, Instagram
  Community engagement**: Responding to comments, messages
  Content scheduling**: Publishing posts at optimal times
  Analytics gathering**: Collecting engagement metrics

  Business Process Automation
  CRM data entry**: Updating customer records across platforms
  Support ticket management**: Creating, updating, routing tickets
  E-commerce operations**: Product listings, inventory updates
  Report generation**: Gathering data from multiple web sources

  Personal Productivity
  Travel booking**: Comparing prices, making reservations
  Bill management**: Paying utilities, checking statements
  Job applications**: Submitting applications, tracking status
  Research tasks**: Gathering information from multiple sources

  Advanced Configuration Options

  Custom Profiles
  Create Airtop profiles for different websites
  Store authentication credentials securely
  Switch between different user accounts
  Handle multi-factor authentication flows

  Workflow Customization
  Modify AI system prompts for specific use cases
  Add custom validation rules
  Implement retry logic for failed operations
  Create domain-specific interaction patterns

  Integration Extensions
  Connect to additional data sources
  Add webhook notifications
  Implement approval workflows
  Create audit logs and reporting

  Getting Started

  📊 Copy the Google Sheets Template - Just click and make a copy!
  Set up credentials for Airtop, OpenAI, and Gmail
  Import workflow into your n8n instance
  Configure node credentials with your API keys and Google Sheets URL
  Test with simple commands like "Visit google.com"
  Expand to complex workflows as you become comfortable

  Best Practices

  Session Management
  Always check for existing sessions before creating new ones
  Properly terminate sessions to avoid resource waste
  Use descriptive names for sessions and windows
  Regularly clean up old session records

  Error Handling
  Implement timeout handling for slow-loading pages
  Add retry logic for network failures
  Validate element existence before interactions
  Log detailed error information for debugging

  Security Considerations
  Store sensitive credentials in Airtop profiles, not workflow
  Use webhook authentication for production deployments
  Implement rate limiting to avoid being blocked by websites
  Regular audit of browser session activities

  This workflow transforms n8n into a powerful browser automation platform, enabling you to automate virtually any web-based task while maintaining full visibility and control over the automation process.

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.airtopTool","n8n-nodes-base.airtopTool","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.airtopTool","n8n-nodes-base.airtopTool","n8n-nodes-base.airtopTool","n8n-nodes-base.airtopTool","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 8552 characters]

metadata_json:
  {"categories":["Automation","AI/ML"],"complexity":"medium","use_cases":["automate web scraping","parse web content","extract data","auto-fill forms"],"estimated_setup_minutes":45,"required_services":[],"key_features":["livelogue browser","context aware learning","structured data output","browser element interaction","memory buffer window"],"target_audience":["developers","automation engineers"]}


name: Automate Video Content Posting to Multiple Social Platforms with Postiz
author_name: Aitor | 1Node
author_username: aitoralonso
categories: []
created_at: 2025-07-29T16:01:19.131Z
updated_at: 2025-07-29T16:01:19.131Z
url: https://n8n.io/workflows/6653
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

  This workflow automates the distribution and scheduling of video content across multiple social platforms (TikTok, YouTube, Facebook, Instagram, Threads) through Postiz. Videos are collected from Google Drive, approved manually, and scheduled via the Postiz community node. 

  🧾 Requirements

  Google Drive** account with access to the folder that will watch for new items uploaded.
  videos in mp4 format ready to be shared or, alternatively you can connect a community node from Cloud Convert to convert the format before uploading into Postiz.
  Postiz account with integrations for TikTok, YouTube, Facebook, Instagram, and Threads
  🔗 Useful Links

  Postiz Docs
  Postiz Community Node

  🔄 Workflow Steps

  Trigger: Google Drive File Added
     Watches your selected Google Drive folder for new file uploads.

  Download File
     Downloads the detected video from Drive.

  Upload to Postiz
     Video is uploaded to Postiz to prepare for social scheduling.

  Set Fields
     Manual setting of social options 

  Extract Datetime (AI)
     Uses OpenAI to find/predict intended publish date & time, as the datetime format  is required to schedule on Postiz

  Get Social Integrations
     Fetches a list of user’s connected platforms from Postiz.

  Split and Filter Integrations
     Splits the process per platform (TikTok, YouTube, Facebook, Instagram, Threads).

  Schedule Post
     For each enabled platform, schedules the video with chosen options.

  🙋‍♂️ Need Help?

  Connect with 1 Node

nodes_used:
  ["n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.informationExtractor","n8n-nodes-base.stickyNote","n8n-nodes-postiz.postiz","n8n-nodes-base.httpRequest","n8n-nodes-postiz.postiz","n8n-nodes-postiz.postiz","n8n-nodes-postiz.postiz","n8n-nodes-postiz.postiz","n8n-nodes-postiz.postiz","n8n-nodes-base.set","n8n-nodes-base.splitOut","n8n-nodes-base.filter","n8n-nodes-base.filter","n8n-nodes-base.filter","n8n-nodes-base.filter","n8n-nodes-base.filter","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenRouter"]

workflow_json_compressed:
  [encoded data, 6112 characters]

metadata_json:
  {"categories":["Marketing","Communication","Social Media Management"],"complexity":"medium","use_cases":["Schedule video posts","Distribute content","Automate social media","Manage video assets"],"estimated_setup_minutes":30,"required_services":["Postiz","Google Drive","Telegram","OpenRouter/LM Chat"],"key_features":["Multi-platform scheduling","Community node integration","Conditional filtering","File watching automation"],"target_audience":["Social media managers","Marketing teams","Content creators"]}


name: Manage Construction Projects with Tasks, Photo Reports, Telegram & Google Sheets
author_name: Artem Boiko
author_username: datadrivenconstruction
categories: []
created_at: 2025-07-30T06:10:11.318Z
updated_at: 2025-07-30T06:10:11.318Z
url: https://n8n.io/workflows/6675
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  How it works
  This template helps project managers collect task updates and photo reports from field workers via Telegram and stores everything in a Google Sheet. It enables daily project reporting without paper or back-office overhead.

  High-level flow:

  Workers receive daily tasks via Telegram

  They respond with photo reports

  Bot auto-saves replies (photos + status) to a Google Sheet

  The system tracks task completion, adds timestamps, and maintains report history

  Set up steps
  🕒 Estimated setup time: 15–30 min
  You’ll need:

  A Telegram bot (via BotFather)

  A connected Google Sheet (with specific column headers)

  A set of preconfigured tasks

  👉 Detailed setup instructions and required table structure are documented in sticky notes inside the workflow.

  Consulting and Training
  We work with leading construction, engineering, consulting agencies and technology firms around the world to help them implement open data principles, automate CAD/BIM processing and build robust ETL pipelines.

  If you would like to test this solution with your own data, or are interested in adapting the workflow to real project tasks, feel free to contact us.


  Docs & Issues:  
    Full Readme on GitHub

nodes_used:
  ["n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.noOp","n8n-nodes-base.noOp","n8n-nodes-base.cron","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.telegram","n8n-nodes-base.googleSheets","n8n-nodes-base.cron","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.noOp","n8n-nodes-base.noOp","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.telegramTrigger","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.googleDrive","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 40656 characters]

metadata_json:
  {"categories":["Business Operations","Data Processing","Project Management"],"complexity":"medium","use_cases":["Collect field worker updates via Telegram","Store project reports in Google Sheets","Track task completion status","Automate daily project documentation","Reduce paper-based reporting"],"estimated_setup_minutes":45,"required_services":["Telegram Bot API","Google Sheets API"],"key_features":["Auto-saves Telegram messages and photos to spreadsheets","Integrates field worker communication with project tracking","Timestamps and categorizes task completion data"],"target_audience":["project managers","construction coordinators","site supervisors"]}


name: Generate multi-period financial reports from Google Sheets with AI analysis
author_name: DuyTran
author_username: duytran82
categories: []
created_at: 2025-07-30T08:06:27.976Z
updated_at: 2025-07-30T08:06:27.976Z
url: https://n8n.io/workflows/6679
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  Description:
  Overview
  This workflow generates automated revenue and expense comparison reports from a structured Google Sheet. It enables users to compare financial data across the current period, last month, and last year, then uses an AI agent to analyze and summarize the results for business reporting.

  Prerequisites
  A connected Google Sheets OAuth2 credential.

  A valid DeepSeek AI API (or replaceable with another Chat Model).

  A sub-workflow (child workflow) that handles processing logic.

  Properly structured Google Sheets data (see below).

  Required Google Sheet Structure
  Column headers must include at least: Date, Amount, Type.

  Setup Steps
  Import the workflow into your n8n instance.

  Connect your Google Sheets and DeepSeek API credentials.

  Update:

  Sheet ID and Tab Name (already embedded in node: Get revenual from google sheet).

  Custom sub-workflow ID (in the Call n8n Workflow Tool node).

  Optionally configure chatbot webhook in the When chat message received node.

  What the Workflow Does
  Accepts date inputs via AI chat interface (ChatTrigger + AI Agent).

  Fetches raw transaction data from Google Sheets.

  Segments and pivots revenue by classification for:

  Current period

  Last month

  Last year

  Aggregates totals and applies custom titles for comparison.

  Merges all summaries into a final unified JSON report.

  Customization Options
  Replace DeepSeek with OpenAI or other LLMs.

  Change the date fields or cycle comparisons (e.g., quarterly, weekly).

  Add more AI analysis steps such as sentiment scoring or forecasting.

  Modify the pivot logic to suit specific KPI tags or labels.

  Troubleshooting Tips
  If Google Sheets fetch fails: ensure the document is shared with your n8n Google credential.

  If parsing errors: verify that all dates follow the expected format.

  Sub-workflow must be active and configured to accept the correct inputs (6 dates).

  SEO Keywords:
  Google Sheets report, AI financial report, compare revenue by month, expense analysis automation, chatbot n8n report generator, n8n Google Sheet integration

  More template: https://aitool.wiki/

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatDeepSeek","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.set","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.aggregate","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.aggregate","n8n-nodes-base.aggregate","n8n-nodes-base.merge","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.aggregate","n8n-nodes-base.merge","n8n-nodes-base.aggregate"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["Finance","Data Processing","AI/ML"],"complexity":"medium","use_cases":["Generate financial comparisons across periods","Summarize revenue and expense data","Compare current metrics with historical data"],"estimated_setup_minutes":15,"required_services":["Google Sheets","DeepSeek AI","Chat Models"],"key_features":["Multi-period financial data comparison","AI-driven analysis and summarization","Sub-workflow processing for scalability"],"target_audience":["Finance managers","Analysts","Business owners"]}


name: Bulk Resume Screening & JD Matching with GPT-4 for HR Teams
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-07-30T08:07:01.612Z
updated_at: 2025-07-30T08:07:01.612Z
url: https://n8n.io/workflows/6680
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  TalentFlow AI – Bulk Resume Screening with JD Matching

  Automatically extract, evaluate, and shortlist multiple resumes against a selected job description using GPT-4. This smart, scalable n8n workflow helps HR/TA teams streamline hiring decisions while keeping results structured, auditable, and easy to share.

  👤 Who’s it for

  This workflow is designed for:
  HR or Talent Acquisition (TA) teams handling multiple candidates per role
  Recruiters who want AI-assisted resume screening to save time and reduce bias
  Organizations that want to automatically log evaluations and keep stakeholders updated in real-time via Slack or Sheets

  ⚙️ How it works / What it does

  HR/TA uploads multiple candidate resumes and selects a job role
  Each resume is:
     Uploaded to Google Drive
     Parsed with GPT-4 to extract structured profile data
  The job description for the selected role is:
     Retrieved from Google Sheets
     Downloaded from Drive and parsed
  The profile + JD are sent to an AI agent to generate:
     Fit score
     Strengths & gaps
     Final recommendation
  Results are:
     Appended to the evaluation tracking sheet
     Optionally shared with the hiring team on Slack
     Used to trigger emails to qualified or unqualified candidates

  🛠️ How to set up

  Clone or import the workflow into your n8n instance
  Connect your integrations:
     Google Sheets (positions & evaluation form)
     Google Drive (CV & JD folders)
     OpenAI API (GPT-4)
     Slack (for notifications)
     (Optional) SendGrid or SMTP for email notifications
  Update Google Sheets structure:
     Positions sheet: maps Job Role → JD file link
     Evaluation form: stores evaluation results
  Prepare Drive folders:
     /cv folder for uploaded resumes
     /jd folder for job description PDFs

  📋 Requirements

  ✅ n8n (hosted or self-hosted)
  ✅ OpenAI GPT-4 account (used in Profile & JD evaluator agents)
  ✅ Google Drive + Google Sheets access
  ✅ Slack workspace + bot token
  (Optional) SendGrid or email credentials for candidate follow-up

  🎨 How to customize the workflow

  Change the fit score threshold in the Candidate qualified? node
  Edit Slack message content/formatting to match your company tone
  Add additional candidate metadata to Sheets or Slack messages
  Use a webhook trigger to integrate with your ATS or job board
  Swap GPT-4 with Claude or Gemini if you prefer other AI services
  Expand to include multi-position batch screening logic

  Happy Hiring! 🚀  
  Automated with love using n8n

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.formTrigger","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.googleSheets","n8n-nodes-base.googleDrive","n8n-nodes-base.extractFromFile","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.sendGrid","n8n-nodes-base.slack","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.filter"]

workflow_json_compressed:
  [encoded data, 11720 characters]

metadata_json:
  {"categories":["Human Resources","AI/ML","Communication","Data Processing"],"complexity":"medium","use_cases":["screen resumes with AI","match candidates to job descriptions","automate hiring workflow","generate candidate scores"],"estimated_setup_minutes":45,"required_services":["OpenAI API","Google Drive","SendGrid","Spreadsheets API"],"key_features":["PDF/DOCx file parsing","embedding-based JD matching","structured output extraction","automated email communication","spreadsheet output generation"],"target_audience":["HR managers","Talent acquisition specialists","Recruiters"]}


name: Track Expenses from Receipt Photos with Telegram & Google Sheets using OCR.space
author_name: Candra Reza
author_username: candrareza
categories: []
created_at: 2025-07-30T09:02:35.042Z
updated_at: 2025-07-30T09:02:35.042Z
url: https://n8n.io/workflows/6686
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:20
description:
  Hello automation enthusiasts! 👋

  Want to automatically track your expenses from receipts without hefty OCR service costs? I've got you covered!

  I've updated my Personal Finance Tracking Chatbot template to incorporate a free OCR service (OCR.space). This powerful n8n workflow lets you effortlessly log your expenses by sending a picture of your receipt to your Telegram bot. The OCR will extract key details like amount, date, and description, which are then neatly saved into your Google Sheets!

  Why use this template?
  📸 Free OCR-Powered Expense Tracking: Simply send a photo of your receipt to your Telegram bot and let OCR.space do the heavy lifting – without breaking the bank!
  📊 Automated Google Sheets Entry: Extracted data is seamlessly appended to your Google Sheet for easy financial overview.
  💰 Manual Entry Still Available: Easily record incomes and expenses via text commands for transactions without receipts.
  🤖 Instant Telegram Confirmations: Get immediate feedback on successful recordings, whether manual or OCR-processed.
  ✨ Customizable Parsing: The included Function node allows you to refine the data extraction logic to perfectly match your receipt formats.

  What Do You Need?
  An n8n account (self-hosted or cloud)
  Your own Telegram Bot (free and easy to create!)
  A free API Key from OCR.space.
  A Google account and an empty Google Spreadsheet for your financial data.
  A Google Spreadsheet with "Income" and "Expenses" sheets (with columns like Date, Description, Amount, Category, Type, Source).

  Who Is This For?
  This template is perfect for anyone who wants to gain more control over their personal finances in an efficient and hassle-free way. No more complex apps, just use your personal chatbot!

  How to Use It?
  Get Your Free OCR.space API Key: Visit ocr.space/OCRAPI and sign up for a free key.
  Import this JSON template into your n8n instance.
  Configure Credentials: Set your Telegram Bot Token, Google Sheet ID, and OCR.space API Key as environment variables in n8n.
  Activate the workflow.
  Start tracking your finances by sending text commands (e.g., income salary 5000, expense coffee 15 food) or just snapping a photo of your receipt to your Telegram bot!

  Let's simplify your financial management with automation! Feel free to try it out and modify it to suit your needs. If you have any questions, leave a comment below!

nodes_used:
  ["n8n-nodes-base.telegramBot","n8n-nodes-base.if","n8n-nodes-base.telegramBot","n8n-nodes-base.httpRequest","n8n-nodes-base.telegramBot"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["Personal Finance","Data Processing"],"complexity":"medium","use_cases":["Expense tracking","Receipt digitization","Financial logging"],"estimated_setup_minutes":30,"required_services":["Telegram","Google Sheets","OCR.space"],"key_features":["OCR integration","WhatsApp/Telegram usage","Database logging"],"target_audience":["Personal finance users","Individuals","Automation enthusiasts"]}


name: Match Medical Symptoms to Products with OpenAI, Qdrant & Google Sheets RAG
author_name: Zain Ali
author_username: zain104
categories: []
created_at: 2025-07-30T13:34:57.126Z
updated_at: 2025-07-30T13:34:57.126Z
url: https://n8n.io/workflows/6699
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  🧠 RAG AI Medical Agent – n8n Workflow

  👥 Who’s it for
  This workflow is perfect for:
  Healthcare ecommerce businesses** that want to automate product recommendations.
  Founders or developers** building an AI assistant using retrieval-augmented generation (RAG) with product data.
  Anyone** wanting to combine OpenAI, Qdrant vector search, and Google Sheets to power intelligent medical queries.

  ⚙️ How it works / What it does

  This RAG-based workflow allows users to ask medical questions related to hair or scalp issues (e.g., hair loss, thinning). It:

  Retrieves product info from a Google Sheet.
  Converts product data into text embeddings using OpenAI.
  Stores those embeddings in a Qdrant vector database.
  On chat message trigger, performs a vector similarity search to match user symptoms with relevant products.
  Uses an AI agent to respond with top 3 matching products from your catalog.

  🛠️ How to set up

  Step 1: 🗂 Get your data
  Make sure your Google Sheet contains the following columns:
    Product Name
    Symptoms Involved
    Product Description
    ForeverBetty Product Page Link
    Category (optional but recommended)

  Step 2: 🔐 Connect your accounts
  Add your Google Sheets OAuth2 credentials in the "Get all products" node.
  Add your OpenAI API key in the embedding nodes.
  Add your Qdrant credentials in the vector store nodes.

  Step 3: 🧠 Populate the Vector DB
  Click “Execute workflow” manually.
  This pulls data from the Google Sheet.
  Each row is:
     Formatted properly into a vector-friendly string.
     Converted into an embedding using OpenAI.
     Stored into Qdrant.

  Step 4: 💬 Enable Chat Interface
  Use the ChatTrigger to receive user queries.
  The agent searches Qdrant for relevant vectors.
  Replies with product suggestions via LangChain's LLM agent.

  📋 Requirements

  🧠 n8n
  📄 A Google Sheet with product data.
  🔐 Google Sheets OAuth2 credentials.
  🧠 OpenAI API key (for embeddings + chat LLM).
  🗃️ Qdrant Vector DB instance (Cloud or self-hosted).
  🧩 How to customize it

  🔄 Change the data structure
  Update the "Set Data Properly in vector database" node to modify what fields are embedded.
  Example:
      --- 
    Product: {{ $json['Product Name '] }}
    Use-case: {{ $json['Symptoms Involved'] }}
    Link: {{ $json['ForeverBetty Product Page Link '] }}

nodes_used:
  ["n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.vectorStoreQdrant","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter","@n8n/n8n-nodes-langchain.embeddingsOpenAi","n8n-nodes-base.splitInBatches","@n8n/n8n-nodes-langchain.vectorStoreQdrant","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.googleSheets"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["AI/ML","Healthcare","Ecommerce"],"complexity":"medium","use_cases":["automated medical product recommendations","RAG-based AI assistant","symptom-to-product matching"],"estimated_setup_minutes":30,"required_services":["OpenAI","Qdrant","Google Sheets"],"key_features":["retrieval-augmented generation","vector search integration","intelligent medical query processing","real-time product recommendations"],"target_audience":["healthcare ecommerce business owners","product recommendation developers","AI assistant builders"]}


name: AI blog automation: Publish hourly SEO articles to WordPress & Twitter v3
author_name: Jay Emp0
author_username: jay-emp0
categories: []
created_at: 2025-07-31T09:51:02.860Z
updated_at: 2025-07-31T09:51:02.860Z
url: https://n8n.io/workflows/6734
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  ==🔥 Upgrade to V4==
  We’ve released Version 4 of our AI Powered Blog Automation workflow. We heard your complains and made a complete redesign built for serious content creators.

  ChatGPT 5, Inbound Links, Verified Outbound Links,YOAST seo integration, Company profile, higher SEO ranking, banner images using companys mascot, FAQ sections and conclusions, 35% cost reduction, 

  📝 Read the New Articles published by Content Farming v4

  🛒 View the updated and improved v4 workflow

  👻 No technical experience ? use Ghost.Blog

  AI Powered Blog Automation Workflow for Wordpress and Twitter - v3 

  Introduction



  This is a fully automated AI powered blog content generation and distribution workflow built for the n8n automation platform. It's designed for solo founders, creators, indie hackers, marketers, SEO consultants, or lean startup teams who run multiple projects and want to consistently publish high quality, search optimized articles without relying on a human marketing team.

  Buy Now for only $29 and get instant traffic to your blog / wordpress site



  Running a blog is essential to drive traffic, build authority, and rank on Google, but it’s time consuming and expensive to manage. This workflow turns your blog into a living, breathing content engine that generates, enhances, and publishes articles every day using a team of autonomous AI agents. If you want to boost your site’s visibility and promote it across multiple channels like WordPress, Twitter, and Dev.to, this workflow is for you.

  Checkout the articles generated with this workflow

  Before You Start

  To get the most out of this workflow, prepare the following:

  Define your content pillars** e.g., AI, business, automation, developer tools, healthtech, etc.
  List your RSS or news sources** like TechCrunch, Wired, CNN Tech, The Verge, etc.
  Know your audience** Who are you trying to attract? Developers? Founders? Investors? Enterprises?

  How It Works

  Step 1: Ingest Recent News via RSS + Vectorization  
  Step 2: Topic Generation with Semantic Clustering  
  Step 3: Research + Data Enrichment  
  Step 4: Content Generation (3 Agent Loop)  
  Step 5: Blog Title Optimization  
  Step 6: Metadata Generation  
  Step 7: Featured Image Generation 
  Step 8: WordPress Draft Creation  
  Step 9: Distribute to Twitter and Dev.to

  Read the complete technical architecture and cost structure

  What makes this flow unique ? 

  This isn’t just automation. It’s AI workflow orchestration. You get a full scale, modular content team simulated by multi agent communication using the following architecture:

  3-Agent System

  Agent 1: Task Manager**
    Defines objectives
    Assigns sections and goals
  Agent 2: Content Generator**
    Equipped with MCP plugins:
      Web Search
      Image Generator
      Graph/Chart Generator
      Section Optimizer
  Agent 3: Quality Control**
    Checks SEO metrics, flow, clarity, link strategy
    Gives detailed recommendations back to Agent 1

  Each agent talks via shared JSON memory and only modifies content blocks relevant to their scope, reducing token usage and preserving structure. This modularity mimics how a marketing team operates. The agents operate in a looped chain of thought format using n8n loops and memory iterating until the article crosses an 80% quality threshold or max loop limit.

  MCP tools for visuals

  The article is generated in a loop involving:
    Internet search to generate outbound links (via MCP tool)



    Image generation (Leonardo or DALL·E via MCP)



    Chart/graph generation (via QuickChart )



    Table generation (via AI agent and HTML blocks)

  Revenue Potential & Monetization Use Cases

  This workflow can generate revenue if deployed strategically.

  💸 Monetization Strategies

  Affiliate Blog Engine**  
    Populate your WordPress with long form articles optimized for affiliate products, SaaS tools, or service reviews. Insert call-to-actions and outbound links to affiliate platforms like Amazon, Gumroad, or Impact.

  Lead Magnet Factory**  
    Target SEO keywords for high-intent leads in your niche (e.g., “best CRM for freelancers”). Capture emails via lead forms in every article and nurture via outbound marketing. Drive subscribers into your Substack or ConvertKit funnel—without writing anything manually.

  Agency/Client Work**  
    Use the workflow to generate blog content for your SEO clients or sell content automation as a service. Deliver consistent value at scale while reducing human cost.

  📈 Traffic Results (v2 Example)

  Daily traffic increase: ~10–30 visitors/day
  Monthly cost: ~$21 for OpenAI tokens
  Content output: 10 SEO-rich posts/day



  With the v3 upgrade, including charts, images, and outbound links, expect higher engagement, lower bounce rate, and better SERP visibility.

  Need Help or Customization?

  Need to customize this workflow for your niche? Or need some help setting it up? Reach out to us and we can help

  ⭐ Read Customer Reviews and how they scaled their blog traffic using this workflow
  ✍️ Write to us via Email: tool@emp0.com
  💬 Chat with us: Discord @jay.ai.automation 

  Join the community

  Other free n8n workflows
  Github repository
  Discord Community
  Official website

  Changelog: From v2 to v3

  I have previously posted a free version of this content generator. You can find FREE v2 on the n8n official website 

  Here is the visual difference of the content length and visual components

  Problems with v2

  RSS links broke when source URLs changed → HTTP 404
  Target length 1500 words never met → hallucinations capped around 600–800
  Content lacked media → zero images/tables/graphs, was very boring to read
  Low SEO score due to minimal outbound links and broken links
  No content repurposing → missed visibility on Dev.to, Twitter for backlinking and gaining traffic
  Single topic limitation → no support for multi pillar blogs

  v3 Upgrades

  Vector DB Integration  
     Store full text and embeddings. Enables multiple content pillar filtering and prevents broken links. Making it customizable per topic

   

  3-Agent AI Architecture  
     Task Manager → Content Writer → QC Loop  
     AI agents loop until threshold met  
     Dynamic sections  
     Visual generation tools built in  
     See architecture image



  Modular Content Blocks  
     Content is saved per section → you can modify one section without touching the rest. Saves tokens and cost.

   

  MCP Tools (included)  
     Generate images. Find the tool here

   

     Generate graphs. Find the tool here

   

     Search web for factual support. Generate tables Improve outbound linking and reader engagement   

   


  Improved Twitter Integration  
     Media rich tweets  
     Auto hashtag generation  
     10x better impressions than plain-text tweets

     Checkout our Automated Twitter Account

   

  Dev.to Posting with Signature  
     Example Dev.to article 

  ✍️ Written by Emp0.com
  🧠 AI Workflows on GitHub: github.com/Jharilela
  💬 Chat with us: Discord @jay.ai.automation
  `

nodes_used:
  ["n8n-nodes-base.splitOut","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.rssFeedRead","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.aggregate","n8n-nodes-base.filter","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.splitOut","n8n-nodes-base.mongoDb","n8n-nodes-base.mongoDb","n8n-nodes-base.mongoDb","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.mongoDb","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.mongoDb","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.mongoDb","n8n-nodes-base.mongoDb","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.code","n8n-nodes-base.mongoDb","n8n-nodes-base.stickyNote","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.splitOut","n8n-nodes-base.splitInBatches","n8n-nodes-base.code","n8n-nodes-base.mongoDb","n8n-nodes-base.mongoDb","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.code","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.vectorStoreMongoDBAtlas","n8n-nodes-base.splitInBatches","n8n-nodes-base.limit","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.crypto","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.vectorStoreMongoDBAtlas","n8n-nodes-base.mongoDb","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.if","n8n-nodes-base.splitInBatches","n8n-nodes-base.mongoDb","n8n-nodes-base.splitOut","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.mongoDb","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.toolThink","n8n-nodes-base.executeWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.mongoDb","n8n-nodes-base.code","n8n-nodes-base.aggregate","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.mongoDb","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.code","n8n-nodes-base.mongoDb","n8n-nodes-base.mongoDb","n8n-nodes-base.mongoDb","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code","n8n-nodes-base.manualTrigger","n8n-nodes-base.wordpress","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.mongoDb","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.mongoDb","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.embeddingsOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.twitter","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.splitOut","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.aggregate","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.mongoDb","n8n-nodes-base.code","n8n-nodes-base.mongoDb","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.mongoDb","n8n-nodes-base.wordpress","n8n-nodes-base.mongoDb","n8n-nodes-base.code","n8n-nodes-base.mongoDb","n8n-nodes-base.code","n8n-nodes-base.mongoDb","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.mongoDb","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 10224 characters]

metadata_json:
  {"categories":["Content Marketing","AI/ML"],"complexity":"medium","use_cases":["automated blog content generation","hourly social media posting","seo optimization","inbound link verification","company mascot image generation"],"estimated_setup_minutes":45,"required_services":["MongoDB","WordPress","Twitter","chatgpt","yoast seo"],"key_features":["hourly content scheduling","seo integration","verified outbound link generation","company profile integration","automated FAQ sections"],"target_audience":["content creators","marketing teams","seo specialists"]}


name: Automate IT Support: Convert Emails to Jira Tickets with AI Resolution
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-07-31T10:19:09.456Z
updated_at: 2025-07-31T10:19:09.456Z
url: https://n8n.io/workflows/6735
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  SmartSupport Flow: Auto-Handle IT Requests from Email to JIRA with Slack notification
  Watch the demo video below:

  Who’s it for
  &gt; This workflow is built for lean IT teams, office managers, and business operators who receive support requests via email and want to automate ticket creation, smart AI resolution advice, and seamless communication with both users and internal teams, all without lifting a finger.  
  If your team is tired of manually triaging inbox requests, this AI-powered flow will transform your support handling process.

  How it works / What it does

  Trigger on New Email: Uses Gmail Trigger to detect new support request emails.
  Fetch Email Content: Retrieves the full message body and metadata.
  Check for Duplication: Skips processing if the email has already been handled (based on READ/UNREAD label).
  Mark as Read: Updates Gmail to mark the email as processed.
  Extract Structured Request: Uses the Support Request Reader Agent powered by OpenAI to extract:
     Request title
     Request description
     Requested by
     Department
     Category and priority
  Create Jira Ticket: A main issue is created in Jira using the structured request.
  Generate AI-Based Solution: Invokes the IT Support Advisor Agent to propose resolution(s).
  Post Comment to Jira: Adds the suggested solution(s) to the issue as a comment.
  Notify IT Team: Sends the ticket and context to a Slack channel for visibility and action.
  (Optional) Send Email to Requester: Currently deactivated. Can be enabled to acknowledge receipt.

  How to set up

  Gmail Integration
     Connect Gmail in the “Gmail Trigger” and “Get Email Content” nodes.
  OpenAI Configuration
     Use OpenAI API credentials in both the Reader and Advisor agent models.
  Jira Integration
     Authenticate your Jira account.
     Set project key and issue fields in the “Create Main Issue” node.
  Slack Notification
     Configure Slack connection and select a target channel.
  Set up Jira, Slack, Email
     Set your company Jira based URL, IT Support slack channel and IT Support email in the Edit Fields (Set) node 
  (Optional) Email Acknowledgment
     Provide SendGrid credentials and email template in the “Send email to requester” node if re-enabled.

  Requirements

  Gmail API access with appropriate permissions  
  OpenAI account with API access (for GPT-4 or GPT-3.5)  
  Jira instance with project and permission to create/comment on issues  
  Slack workspace and Webhook or OAuth setup  
  n8n instance running with all above integrations configured

  How to customize the workflow

  Enhance Email Deduplication**: Adjust the deduplication logic to use message-id, threadId, or custom headers.
  Expand Reader Agent**: Configure the LLM to extract more details such as asset tags, urgency levels, or locations.
  Tailor Advisor Agent**: Adjust prompt to generate multiple solutions, troubleshooting guides, or internal references.
  Routing by Department**: Add logic to forward requests to different teams based on the request category or department.
  Enable Email Acknowledgment**: Activate and customize the email notification step to inform requesters that their issue is being handled.

nodes_used:
  ["n8n-nodes-base.gmailTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.filter","n8n-nodes-base.slack","n8n-nodes-base.sendGrid","n8n-nodes-base.gmail","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.jira","n8n-nodes-base.gmail","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.jira","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 10228 characters]

metadata_json:
  {"categories":["IT Support","Communication","Automation"],"complexity":"medium","use_cases":["create IT support tickets from email","generate AI-based resolution steps","send email notifications","create Jira tickets"],"estimated_setup_minutes":15,"required_services":["Jira","SendGrid","AI/LLM model","Slack","Email provider (Gmail/Outlook/Exchange)"],"key_features":["Auto-converts support emails to Jira tickets","AI generates resolution steps","Automated Slack notifications","Conditional branching for ticket priority","Structured output parsing"],"target_audience":["IT support staff","Office managers","Business operations teams"]}


name: Reddit Lead Finder: Automated Prospecting with GPT-4, Supabase and Gmail Alerts
author_name: BluePro
author_username: bluepro
categories: []
created_at: 2025-08-01T01:36:19.492Z
updated_at: 2025-08-01T01:36:19.492Z
url: https://n8n.io/workflows/6756
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  This workflow monitors targeted subreddits for potential sales leads using Reddit’s API, AI content analysis, Supabase, and Google Sheets.

  It is built specifically to discover posts from Reddit users who may benefit from a particular product or service. It can be easily customized for any market.

  🔍 Features

  Targeted Subreddit Monitoring:**  
    Searches multiple niche subreddits like smallbusiness, startup, sweatystartup, etc., using relevant keywords.

  AI-Powered Relevance Scoring:**  
    Uses OpenAI GPT to analyze each post and determine if it’s written by someone who might benefit from your product, returning a simple “yes” or “no.”

  Duplicate Lead Filtering with Supabase:**  
    Ensures you don’t email the same lead more than once by storing already-processed Reddit post IDs in a Supabase table.

  Content Filtering:**  
    Filters out posts with no body text or no upvotes to ensure only high-quality content is processed.

  Lead Storage in Google Sheets:**  
    Saves qualified leads into a connected Google Sheet with key data (URL, post content, subreddit, and timestamp).

  Email Digest Alerts:**  
    Compiles relevant leads and sends a daily digest of matched posts to your team’s inbox for review or outreach.

  Manual or Scheduled Trigger:**  
    Can be manually triggered or automatically scheduled (via the built-in Schedule Trigger node).

  ⚙️ Tech Stack

  Reddit API** – For post discovery  
  OpenAI Chat Model** – For AI-based relevance filtering  
  Supabase** – For lead de-duplication  
  Google Sheets** – For storing lead details  
  Gmail API** – For sending email alerts

  🔧 Customization Tips

  Adjust Audience**: Modify the subreddits and keywords in the initial Code node to match your market.
  Change the AI Prompt**: Customize the prompt in the “Analysis Content by AI” node to describe your product or service.
  Search Comments Instead**: To monitor comments instead of posts, change type=link to type=comment in the Reddit Search node.
  Change Email Recipients**: Edit the Gmail node to direct leads to a different email address or format.

nodes_used:
  ["n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.reddit","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.gmail","n8n-nodes-base.splitInBatches","n8n-nodes-base.supabase","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.splitInBatches","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.splitInBatches","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.splitInBatches","n8n-nodes-base.supabase","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.scheduleTrigger"]

workflow_json_compressed:
  [encoded data, 4440 characters]

metadata_json:
  {"categories":["Marketing","Data Processing","Communication"],"complexity":"medium","use_cases":["Identify potential sales leads","Automate social media prospecting","Monitor niche community discussions","Qualify leads using AI analysis","Centralize lead data in spreadsheet"],"estimated_setup_minutes":45,"required_services":["Reddit","Google Sheets","Supabase","OpenAI GPT-4"],"key_features":["Multi-channel subreddit monitoring","AI-powered lead relevance scoring","Automated filtering and categorization","Real-time lead data storage","Customizable keyword search"],"target_audience":["Sales Professionals","Marketing Team","Business Development"]}


name: Scheduled Instagram Auto-Liker with Phantombuster, GPT-4o & Cookie Rotation
author_name: plemeo
author_username: plemeo
categories: []
created_at: 2025-08-01T08:20:52.647Z
updated_at: 2025-08-01T08:20:52.647Z
url: https://n8n.io/workflows/6765
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:21
description:
  Who’s it for  
  Social-media managers and brands that want to keep their Instagram
  accounts active by automatically liking fresh posts under selected
  hashtags—hands-free and rate-limited.

  How it works / What it does  
  Schedule Trigger runs every 2 hours at a specified minute.  
  Select Cookie chooses a rotating Instagram session-cookie
     (time-slice logic).  
  Generate Random Hashtag (GPT-4o) outputs a realistic AI/BPA
     hashtag.  
  Instagram Hashtag Agent (Phantombuster) scrapes up to
     ENV_MAX_POSTS_PER_HASHTAG recent posts.  
  Get Random Post selects one; duplicate checker ensures it
     hasn’t been liked before (SharePoint CSV).  
  Builds instagram_posts_to_like.csv, uploads to SharePoint, then
     launches the Auto-like Agent which likes the post.  
  Post URL is appended to instagram_posts_already_liked.csv to avoid
     duplicates.  
  Wait nodes throttle launches to ~12 likes per profile daily.

  How to set up  
  Add credentials: Phantombuster API, SharePoint OAuth2, OpenAI API
     key.  
  In SharePoint › “Phantombuster” folder create:  
     • instagram_session_cookies.txt – one cookie per line.  
     • instagram_posts_already_liked.csv with header postUrl.  
  Adjust Set ENV Variables to change max posts per scrape.  
  Activate the workflow; it will like one post every 2 hours.

  Requirements  
  n8n 1.33 +  
  Phantombuster Growth plan (API access)  
  OpenAI account
  Microsoft 365 SharePoint tenant

  How to customize  
  Target a different niche: edit hashtag prompt in Generate Random Hashtag.  
  Like more posts: raise ENV_MAX_POSTS_PER_HASHTAG,
    numberOfPostsPerLaunch, or schedule frequency.  
  Replace SharePoint with Drive/Dropbox by swapping storage nodes.

nodes_used:
  ["n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.phantombuster","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.code","n8n-nodes-base.extractFromFile","n8n-nodes-base.convertToFile","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["Marketing","Social Media"],"complexity":"medium","use_cases":["Auto-like Instagram posts","Schedule hashtag generation","Rotate session cookies"],"estimated_setup_minutes":15,"required_services":["Phantombuster","OpenAI (GPT-4o)"],"key_features":["Hashtag generation via AI","Cookie rotation logic","Scheduled execution"],"target_audience":["Social media managers"]}


name: Auto-follow Instagram profiles via Phantombuster and SharePoint
author_name: plemeo
author_username: plemeo
categories: []
created_at: 2025-08-01T08:26:18.753Z
updated_at: 2025-08-01T08:26:18.753Z
url: https://n8n.io/workflows/6766
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:22
description:
  Who’s it for  
  Community managers, growth hackers, and brands that want to grow their
  Instagram audience by automatically following new, relevant profiles—
  while respecting daily limits.

  How it works / What it does  
  Schedule Trigger runs hourly at a specified minute.  
  Select Cookie chooses a rotating Instagram session-cookie (time-slice logic).  
  Get List of Accounts downloads a CSV of seed profiles from SharePoint.  
  Follower Collector Agent (Phantombuster) fetches each seed
     profile’s followers (limit set by ENV_AMOUNT_FOLLOWERS_PER_PROFILE).  
  Autofollow Agent follows up to ENV_PROFILES_TO_PROCESS of those
     followers per launch.  
  Wait nodes pause between Phantombuster calls and poll until each
     run is complete.  
  Rate-limit configuration keeps follows between 1 and 40 per hour.

  How to set up  
  Add credentials: Phantombuster API, SharePoint OAuth2, (optional) OpenAI API key if you later add AI.  
  In SharePoint › “Phantombuster” folder add:  
     • instagram_session_cookies.txt – one cookie per line.  
     • accounts_to_follow.csv – header profileUrl, one seed profile per line.  
  Update Set ENV Variables to control profiles/launch and followers/profile.  
  Adjust schedule frequency or Wait durations to meet your plan limits.  
  Activate the workflow; it will follow new profiles every hour.

  Requirements  
  n8n 1.33 +  
  Phantombuster Growth plan (API access)  
  Microsoft 365 SharePoint tenant

  How to customize  
  Scrape hashtags instead of followers: replace the Follower Collector
    agent with a Hashtag‐to‐Profiles agent.  
  Increase speed: raise ENV_PROFILES_TO_PROCESS and cron frequency
    (ensure you stay within Instagram limits).  
  Swap SharePoint for Drive/Dropbox by replacing storage nodes.

nodes_used:
  ["n8n-nodes-base.wait","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.phantombuster","n8n-nodes-base.wait","n8n-nodes-base.set","n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["Marketing","Social Media Management","Automation"],"complexity":"medium","use_cases":["grow Instagram following","automate profile engagement","manage social community"],"estimated_setup_minutes":30,"required_services":["Phantombuster","Microsoft SharePoint","Instagram"],"key_features":["rotating session cookies","CSV triggered data fetching","automated follower collection","schedule-based workflow"],"target_audience":["community managers","growth hackers","social media marketers"]}


name: Generate Tailored Interview Questions with GPT-4 Based on CV, JD, and Round
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-08-01T08:29:51.767Z
updated_at: 2025-08-01T08:29:51.767Z
url: https://n8n.io/workflows/6767
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:55
description:
  🤖 Smart Interview Assistant: Tailored Questions Based on CV, JD, and Round
  Watch the demo video below:

  📌 Who’s it for
  This workflow is designed for:
  Recruiters* and *Talent Acquisition Specialists** who want to automate candidate interview prep.
  Hiring Managers** conducting multiple interviews and needing personalized question sets.
  Technical Interviewers** who want to save time and be well-prepared with relevant questions.

  ⚙️ How it works / What it does
  The Smart Interview Assistant automates the interview preparation process in a few clicks:

  Accepts:
     Multiple resumes (PDFs)
     Selected job role
     Chosen interview round
  Extracts structured data from:
     The candidate’s CV
     The corresponding Job Description (JD)
  Uses GPT-4 to analyze:
     Candidate profile
     Role requirements
     Interview round context
  Generates:
     Tailored interview questions
     Expected answers
     A summarized interview prep report
  Sends the report directly to the hiring team via email (SMTP)

  📁 Google Drive Structure

  📂 Root Folder
  ├── 📁 jd/                          # Stores all job descriptions in PDF format
  │   ├── Backend_Engineer.pdf
  │   ├── Azure_DevOps_Lead.pdf
  │   └── ...
  └── 📄 Positions (Google Sheet)    # Maps Job Role ↔ JD File Link

  📝 Sample Mapping Sheet:  
  Positions Sheet

  Columns:
  Job Role
  Job Description File URL (pointing to PDF in jd/ folder)

  🛠️ How to Set Up

  Step 1: Configure API Integrations
  ✅ Connect your OpenAI GPT-4 API Key
  ✅ Enable Google Cloud APIs:
    Google Sheets API (to read job roles)
    Google Drive API (to access CV and JD files)
  ✅ Set up SMTP credentials (for email delivery)

  Step 2: Prepare Google Drive & Mapping Sheet

  Create a root folder on Google Drive  
  Inside the root folder:
     Create a folder named /jd/ and upload all job descriptions (PDFs)  
  Create a Google Sheet named Positions with the following format:

  | Job Role                     | Job Description File URL                   |
  |-----------------------------|--------------------------------------------|
  | Azure DevOps Engineer        | https://drive.google.com/xxx/jd1.pdf       |
  | Full-Stack Developer (.NET)  | https://drive.google.com/xxx/jd2.pdf       |

  Step 3: Build the Application Form

  Use any form tool (e.g., Typeform, Tally, or custom HTML) that collects:
  📎 Resume file (PDF)
  🧾 Job Role (dropdown)
  🔄 Interview Round (dropdown)

  Step 4: Resume & JD Extraction

  🔍 Use Extract from PDF to parse the resume content
  📄 Retrieve the JD link from the Positions sheet based on the selected Job Role
  🔗 Use Download file to pull the PDF for processing

  Step 5: Analyze with GPT-4

  Run both Resume and JD through a Profile Analyzer Agent (GPT-4 with JSON output)
  Merge results
  Add manual input or mapping for the Interview Round metadata

  Step 6: Generate Interview Report

  Use a second GPT-4 agent (e.g., HR Expert Agent) to:
    Generate 6–8 tailored interview questions
    Include expected answers and rationale

  Step 7: Deliver Final Report

  Format the content as:
    📄 PDF (optional)
    📨 Email body
  Send the report to the recruiter, hiring manager, or interviewer via SMTP

  ✅ Requirements

  🔑 OpenAI GPT-4 API Key
  📁 Google Drive (for resume and JD storage)
  📊 Google Sheet (job role mapping)
  📬 SMTP credentials (host, username, password)
  🧰 n8n self-hosted or cloud instance with:
    PDF Parser
    Google Sheets node
    HTTP Download node
    Email node

  ✏️ How to Customize the Workflow

  | Part                        | Customization Options                                      |
  |----------------------------|-------------------------------------------------------------|
  | Form UI                | Modify the design, dropdown options, or input validations   |
  | Job Description Source | Replace Google Sheet with Notion, Airtable, or database     |
  | Interview Metadata     | Add job level, region, or language preference               |
  | AI Prompt Tuning       | Adjust prompt phrasing or temperature in GPT nodes          |
  | Report Format          | Generate PDF instead of email body using PDF node           |
  | Delivery Method        | Add internal HR portal webhook or generate downloadable link |

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.formTrigger","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.googleSheets","n8n-nodes-base.googleDrive","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.code","n8n-nodes-base.emailSend","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 12572 characters]

metadata_json:
  {"categories":["Recruitment","AI/ML"],"complexity":"medium","use_cases":["Generate tailored interview questions","Automate candidate prep","Personalize question sets"],"estimated_setup_minutes":15,"required_services":["GPT-4","Google Drive","Google Sheets"],"key_features":["Dynamic question generation","CV and JD analysis","Round-specific tailoring"],"target_audience":["recruiters","hiring managers","talent acquisition specialists"]}


name: Auto-comment on Instagram posts with GPT-4o, Phantombuster, and SharePoint
author_name: plemeo
author_username: plemeo
categories: []
created_at: 2025-08-01T08:32:37.238Z
updated_at: 2025-08-01T08:32:37.238Z
url: https://n8n.io/workflows/6768
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:21
description:
  Who’s it for  
  Social-media teams and influencers who want to grow engagement by
  automatically posting short, relevant comments on new Instagram posts
  under rotating hashtags—while staying under platform limits.

  How it works / What it does  
  Schedule Trigger fires every 2 h at a specified minute.  
  Select Cookie chooses a rotating Instagram session-cookie by
     time slice.  
  Generate Random Hashtag (GPT-4o) outputs a realistic AI/BPA tag.  
  Hashtag Agent (Phantombuster) scrapes up to
     ENV_MAX_POSTS_PER_HASHTAG recent posts.  
  Get Random Post picks one; Create Comment (GPT-4o) crafts a
     ≤150-character reply in the chosen language.  
  Builds instagram_post_to_comment.csv, uploads to SharePoint, then
     launches the Auto-comment Agent which posts the reply.  
  Post URL is logged to instagram_posts_already_commented.csv
     to avoid duplicates.  
  Wait nodes throttle launches to ≈80 comments/day.

  How to set up  
  Add credentials: Phantombuster API, SharePoint OAuth2, OpenAI API key.  
  In SharePoint › “Phantombuster” folder create:  
     • instagram_session_cookies.txt – one cookie per line.  
     • instagram_posts_already_commented.csv with header postUrl.  
  Edit Set ENV Variables to set default language, prompt, and max
     posts per scrape.  
  Activate the workflow; it will comment every 2 h.

  Requirements  
  n8n 1.33 +  
  Phantombuster Growth plan (API access)  
  OpenAI account (GPT-4o)  
  Microsoft 365 SharePoint tenant

  How to customize  
  Change tone/length: tweak prompt in Create Comment.  
  Comment more often: raise ENV_MAX_POSTS_PER_HASHTAG,
    adjust cron, and agent limits.  
  Swap SharePoint for Drive/Dropbox by replacing storage nodes.

nodes_used:
  ["n8n-nodes-base.wait","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.wait","n8n-nodes-base.phantombuster","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.code","n8n-nodes-base.extractFromFile","n8n-nodes-base.convertToFile","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["Communication","Marketing","Social Media"],"complexity":"medium","use_cases":["automated engagement","hashtag generation","social media monitoring"],"estimated_setup_minutes":30,"required_services":["Instagram","Phantombuster","GPT-4o","SharePoint"],"key_features":["schedule-based execution","AI-powered content creation","data extraction and scraping","rotation of session cookies","error handling via conditional logic"],"target_audience":["social media managers","marketing teams","content creators"]}


name: Automate QuickBooks customers & sales receipts generation from a Google Sheet
author_name: Intuz
author_username: intuz
categories: []
created_at: 2025-08-01T08:59:09.867Z
updated_at: 2025-08-01T08:59:09.867Z
url: https://n8n.io/workflows/6770
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  This n8n template from Intuz provides a complete and automated solution to streamline your sales and accounting process.

  Simply add new transaction details to a designated Google Sheet, and this workflow takes over. Using specific status keywords in a column to trigger the process, it automatically creates new customer profiles and generates sales receipts in QuickBooks. This creates a complete, end-to-end system from a simple spreadsheet entry to a formal accounting record, eliminating manual data entry.

  How it works

  This workflow streamlines the process of recording sales from a Google Sheet into QuickBooks Online, intelligently handling both new and existing customers.

  1. Trigger on New Row: The workflow starts automatically whenever a new row is added to your specified Google Sheet.

  2. Check for Existing Customer: It takes the customer's name from the new row and searches your QuickBooks account to see if a customer with that DisplayName already exists.

  3. Conditional Logic (IF Node): Based on the search result, the workflow splits into two paths:

  If Customer Exists (True Path): The workflow proceeds directly to create a Sales Receipt, linking it to the existing customer's ID found in the search.
  If Customer Does Not Exist (False Path): The workflow first creates a new customer in QuickBooks using the name and email from the sheet. It then uses the ID of this newly created customer to generate the corresponding Sales Receipt.

  How to Use: Quick Start Guide

  Prepare your Google Sheet: Make sure you have a Google Sheet with clear headers for your sales data. The template is configured for the following columns: CustomerName, Email, Amount, and Quantity.

  Import the Template: Click the "Use Template" button to import the workflow into your n8n instance.

  Configure Google Sheet Node: 
  Enter the Spreadsheet ID from your Google Sheet's URL.
  Enter the Sheet Name where your sales data is located (e.g., Sheet1).

  Configure the QuickBooks Nodes: 
  Select your QuickBooks Online credential or create a new one for the "Search for Customer", "Create Receipt for EXISTING Customer", "Create New Customer", and "Create Receipt for NEW Customer" nodes.
  Important: In both "Create Receipt" nodes, you must provide a valid Product/Service ID from your QuickBooks account. Find this in the node parameters under Line &gt; Sales Item Line Detail &gt; Item Ref &gt; Value.

  Activate the Workflow: Save your changes and activate the workflow. Now, every new row you add to the Google Sheet will automatically create the necessary records in QuickBooks.
  Key Requirements to Use Template
  An active n8n instance.
  A Google account with a prepared Google Sheet.
  A QuickBooks Online account.
  A QuickBooks Developer account to obtain the API credentials needed to connect to n8n.
  At least one Product or Service item set up in your QuickBooks account to be referenced in the sales receipts.
  Connect with us

  Website: https://www.intuz.com/n8n-workflow-automation-templates
  Email: getstarted@intuz.com
  LinkedIn: https://www.linkedin.com/company/intuz
  Get Started: https://n8n.partnerlinks.io/intuz

  For Custom Workflow Automation
  Click here- Get Started

nodes_used:
  ["n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.quickbooks","n8n-nodes-base.quickbooks","n8n-nodes-base.stickyNote","n8n-nodes-base.quickbooks"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["Accounting","Finance"],"complexity":"medium","use_cases":["creating customer profiles","generating sales receipts","automating transaction processing","online transaction entry","manual input automation"],"estimated_setup_minutes":15,"required_services":["QuickBooks Online","Google Sheets"],"key_features":["status keyword triggers","transaction to customer creation","spreadsheet to accounting integration","end-to-end automation"],"target_audience":["accountants","bookkeepers","small business owners"]}


name: WhatsApp RAG Chatbot with Supabase, Gemini 2.5 Flash, and OpenAI Embeddings
author_name: Manav Desai
author_username: manavdesai17
categories: []
created_at: 2025-08-01T09:17:50.511Z
updated_at: 2025-08-01T09:17:50.511Z
url: https://n8n.io/workflows/6771
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:21
description:
  WhatsApp RAG Chatbot with Supabase, Gemini 2.5 Flash, and OpenAI Embeddings

  This n8n template demonstrates how to build a WhatsApp-based AI chatbot that answers user questions using document retrieval (RAG) powered by Supabase for storage, OpenAI embeddings for semantic search, and Gemini 2.5 Flash LLM for generating high-quality responses.

  Use cases are many: Turn your WhatsApp into a knowledge assistant for FAQs, customer support, or internal company documents — all without coding.

  Good to know

  The workflow uses OpenAI embeddings for both document embeddings and query embeddings, ensuring accurate semantic search.  
  Gemini 2.5 Flash LLM** is used to generate user-friendly answers from the retrieved context.  
  Messages are processed in real-time and sent back directly to WhatsApp.  
  Workflow is modular — you can split document ingestion and query handling for large-scale setups.  
  Supabase and WhatsApp API credentials must be configured before running.  

  How it works

  Trigger: A new WhatsApp message triggers the workflow via webhook.  
  Message Check: Determines if the message is a query or a document upload.  
  Document Handling:  
     Fetch file URL from WhatsApp.  
     Convert binary to text.  
     Generate embeddings with OpenAI and store them in Supabase.  
  Query Handling:  
     Generate query embeddings with OpenAI.  
     Retrieve relevant context from Supabase.  
     Pass context to Gemini 2.5 Flash LLM to compose a response.  
  Response: Send the answer back to the user on WhatsApp.  

  Optional: Add Gmail node to forward chat logs or daily summaries.

  How to use

  Configure WhatsApp Business API webhook for incoming messages.  
  Add your Supabase and OpenAI credentials in n8n’s credentials manager.  
  Upload documents via WhatsApp to populate the Supabase vector store.  
  Ask queries — the bot retrieves context and answers using Gemini 2.5 Flash.

  Requirements

  WhatsApp Business API** (or Twilio WhatsApp Sandbox)  
  Supabase account** (vector storage for embeddings)  
  OpenAI API key** (for generating embeddings)  
  Gemini API access** (for LLM responses)  

  Customising this workflow

  Swap WhatsApp with Telegram, Slack, or email for different chat channels.  
  Extend ingestion to other sources like Google Drive or Notion.  
  Adjust the number of retrieved documents or prompt style in Gemini for tone control.  
  Add a Gmail output node to send logs or alerts automatically.  

nodes_used:
  ["@n8n/n8n-nodes-langchain.vectorStoreSupabase","n8n-nodes-base.whatsAppTrigger","n8n-nodes-base.switch","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.vectorStoreSupabase","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.whatsApp","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.whatsApp","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4624 characters]

metadata_json:
  {"categories":["AI/ML","Communication","Data Processing"],"complexity":"medium","use_cases":["customer support","FAQ automation","internal knowledge base","WhatsApp knowledge assistant"],"estimated_setup_minutes":30,"required_services":["WhatsApp API","Supabase","OpenAI","Google Gemini"],"key_features":["RAG-based document retrieval","embedding generation","WhatsApp chatbot integration","semantic search"],"target_audience":["customer success managers","tech teams","support staff"]}


name: Automate GitHub PRs & JIRA updates from Git commit commands-single repo
author_name: Intuz
author_username: intuz
categories: []
created_at: 2025-08-01T10:22:39.160Z
updated_at: 2025-08-01T10:22:39.160Z
url: https://n8n.io/workflows/6773
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  This n8n template from Intuz delivers a complete and automated solution to streamline your development workflow for a single repository.

  By embedding specific keywords and a JIRA issue ID within your git commit commands, this workflow automatically creates a Pull Request in GitHub and simultaneously updates the corresponding JIRA ticket. This provides a complete, seamless integration that eliminates manual steps and keeps your project management perfectly in sync with your codebase.

  How it works

  This workflow acts as a powerful bridge between your Git repository and your project management tools, driven entirely by the structure of your commit messages.

  GitHub Webhook Trigger: 
  The workflow starts when a developer pushes a new commit to a specified repository in GitHub.

  Parse Commit Message: A Code node extracts key information from the commit message:

  The JIRA Issue Key (e.g., FF-1196).
  The base branch for the PR (e.g., development).
  Action commands like [auto-pr] and [taskcompleted].

  Conditional PR Creation: An IF node checks if the [auto-pr] command is present.

  If yes, it uses the GitHub node to automatically create a pull request from the developer's branch to the specified base branch.
  If no, this step is skipped, allowing for multiple commits before a PR is made.

  Conditional JIRA Update: Another IF node checks for the [taskcompleted] command.

  If yes, it uses the JIRA node to transition the corresponding issue to your "Done" status (e.g., "Task Completed" or "In Review").
  If no, the JIRA issue remains in its current state, perfect for work-in-progress commits.

  How to Use: Quick Start Guide

  Click the "Use Template" button to import this workflow into your n8n instance.

  Configure the GitHub Trigger:
  Open the "GitHub Push Trigger" node. It will display a unique Webhook URL. Copy this URL.
  In your GitHub repository, go to Settings &gt; Webhooks &gt; Add webhook.
  Paste the URL into the Payload URL field.
  Set the Content type to application/json.
  Under "Which events would you like to trigger this webhook?", select Just the push event.
  Click Add webhook.

  Connect Your Accounts:
  GitHub: Select your GitHub API credential in the "Create Pull Request" node.
  JIRA : Select your JIRA API credential in the "Update JIRA Issue Status" node.

  Customize the JIRA Transition (Important):
  Open the "Update JIRA Issue Status" node.
  In the Transition parameter, you need to set the specific status you want to move the issue to (e.g., 'Done', 'Completed', 'In Review'). You can use the ID or the exact name of the transition from your JIRA  project's workflow.

  Activate the Workflow: Save your changes and activate the workflow. You're ready to automate!

  Example Commit Message:
  git commit -m "FF-1196 Implement OAuth login [auto-pr,development,taskcompleted]"

  Key Requirements to Use Template

  An active n8n instance.
  A GitHub account with repository admin permissions to create webhooks.
  A JIRA Cloud account with permissions to update issues.
  Developers who can follow the specified git commit message format.

  Connect with us

  Website: https://www.intuz.com/n8n-workflow-automation-templates
  Email: getstarted@intuz.com
  LinkedIn: https://www.linkedin.com/company/intuz
  Get Started: https://n8n.partnerlinks.io/intuz

  For Custom Worflow Automation
  Click here- Get Started

nodes_used:
  ["n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.githubTrigger","n8n-nodes-base.stopAndError","n8n-nodes-base.stopAndError","n8n-nodes-base.if","n8n-nodes-base.jira","n8n-nodes-base.jira","n8n-nodes-base.if","n8n-nodes-base.jira","n8n-nodes-base.if","n8n-nodes-base.jira","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5644 characters]

metadata_json:
  {"categories":["DevOps","Development"],"complexity":"medium","use_cases":["create pull requests","update jira tickets","sync development workflow","automate commit commands"],"estimated_setup_minutes":15,"required_services":["GitHub","Jira"],"key_features":["keyword-based triggers","issue ID parsing","pr creation automation","jira ticket updates","single repository focus"],"target_audience":["developers","devops engineers","project managers"]}


name: AI-Generated LinkedIn Posts with Human Approval using GPT-4, GoToHuman & Blotato
author_name: Robert Breen
author_username: rbreen
categories: []
created_at: 2025-08-02T00:04:14.003Z
updated_at: 2025-08-02T00:04:14.003Z
url: https://n8n.io/workflows/6827
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:22
description:
  This workflow is designed for creators, marketers, and agencies who want to automate content publishing while keeping quality control through human review. It integrates four powerful tools — Google Sheets, OpenAI, GoToHuman, and Blotato — to deliver a seamless AI-assisted, human-approved, auto-publishing system for LinkedIn.

  ⚙️ What This Workflow Does

  📅 Pulls Today’s Topic from Google Sheets  
     You store ideas in a spreadsheet with a date column.  
     The workflow runs daily (or manually) and selects the row matching today’s date.

  🧠 Generates a Caption with OpenAI  
     The selected idea is passed to GPT-4 via an AI Agent node.  
     OpenAI returns a short, emoji-rich LinkedIn caption (1–2 sentences).  
     The result is saved back to the sheet.

  👤 Sends the Caption for Human Review via GoToHuman  
     A human reviewer sees the AI-generated caption.  
     They approve or reject it using a GoToHuman review template.  
     Only approved captions move forward.

  🚀 Publishes the Approved Caption to LinkedIn via Blotato  
     The caption is posted to a LinkedIn account via Blotato's API.  
     No additional input is required — it's fully automated after approval.

  🔧 Setup Requirements

  ✅ Google Sheets
  Create or copy the provided sample sheet.
  Connect your Google Sheets account in n8n using OAuth2.

  ✅ OpenAI
  Create an API key at platform.openai.com.
  Add it to n8n as an OpenAI credential.

  ✅ GoToHuman
  Create an account and a Review Template at gotohuman.com.
  Add your API credential in n8n and use your reviewTemplateId in the node.

  ✅ Blotato
  Create an account at blotato.com.
  Get your API key and Account ID.
  Insert them into the HTTP Request node that publishes the LinkedIn post.

  🧪 Testing the Workflow

  Use the Manual Trigger node for step-by-step debugging.  
  Review nodes like AI Agent, Ask Human for Approval, and Post to LinkedIn to verify output.  
  Once confirmed, activate the schedule for fully hands-free publishing.

  👋 Built By

  Robert Breen  
  Founder of Ynteractive — Automation, AI, and Data Strategy

  🌐 Website: https://ynteractive.com  
  📧 Email: robert@ynteractive.com  
  🔗 LinkedIn: https://www.linkedin.com/in/robert-breen-29429625/  
  📺 YouTube: YnteractiveTraining

  🏷 Tags

  linkedin openai gotohuman social automation ai content approval workflow google sheets blotato marketing automation

nodes_used:
  ["n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolThink","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.manualTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","@gotohuman/n8n-nodes-gotohuman.gotoHuman","n8n-nodes-base.filter","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5368 characters]

metadata_json:
  {"categories":["Marketing"],"complexity":"simple","use_cases":["create linkedin posts","draft social content","approve ai-generated text","schedule social posts","curate content ideas"],"estimated_setup_minutes":10,"required_services":["Google Sheets","OpenAI","GoToHuman","LinkedIn"],"key_features":["AI-powered content generation","human approval gate","autonomous scheduling","spreadsheets integration"],"target_audience":["creators","marketers","agencies"]}


name: AI-Powered CV Extractor: Google Drive to Sheet with GPT-4 + Slack for Recruiters
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-08-02T05:56:38.102Z
updated_at: 2025-08-02T05:56:38.102Z
url: https://n8n.io/workflows/6835
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  CV Extractor: Google Drive to Sheet + Slack Update for Recruiters
  Watch the demo video below:

  &gt; This workflow automatically processes resumes (PDFs) uploaded or updated in a Google Drive folder. It extracts and structures the candidate’s information using AI, then updates or inserts the data into a Google Sheet, acting as a central talent database. Finally, it notifies the hiring team via Slack with a summary. Perfect for HR and TA teams, this automation eliminates the repetitive task of manually copying candidate details from CVs into spreadsheets, saving hours of admin work every week and keeping your hiring pipeline clean, fast, and up to date.
  👤 Who’s it for
  This workflow is designed for:
  Recruiters* and *HR coordinators** who manage candidate profiles via Google Drive.
  Talent Acquisition teams** who want to automate CV parsing, enrichment, and database updating.
  Companies or hiring agencies** using spreadsheets for candidate tracking and CRM-like HR ops.
  ⚙️ How it works / What it does
  This smart and fully automated workflow:
  Monitors a Google Drive folder for any uploaded or updated resumes (PDFs).
  Downloads and extracts resume content using PDF parsing.
  Sends the raw text to GPT-4, which returns a structured profile (name, title, experience, skills, etc.).
  Verifies the profile and transforms it into a clean, row-based format.
  Upserts the candidate profile into a Google Sheet (insert or update by email).
  Notifies the hiring team in Slack or email that a profile was added or updated.

  This is a no-touch pipeline to keep your candidate data clean, current, and centralized.
  🛠️ How to set up
  Step 1: Prepare your Google Drive folder
  Create a folder like /SmartHR/cv/
  Upload sample resumes in .pdf format

  Step 2: Create your Google Sheet
  Columns to include: Email, FullName, JobTitle, Phone, Location, Experience, Education, Skills, etc.
  Optional: Add conditional formatting to highlight updates

  Step 3: Connect the n8n workflow
  Use the Google Drive Trigger:
    fileCreated → new profile uploaded
    fileUpdated → existing profile modified
  Use Google Drive (Download file) to fetch the resume
  Use Extract From PDF to get raw content

  Step 4: Configure GPT-4 node
  Use the structured system prompt to extract profile information
  Use json parser node to ensure safe formatting for next steps

  Step 5: Transform & Save
  Use a Function node to map fields to Google Sheet columns
  Use Append or update row (based on email as unique key)
  Optionally send Slack or email message to notify hiring team

  ✅ Requirements

  🔑 OpenAI GPT-4 API key
  🟩 n8n Cloud or Self-hosted with:
    Google Drive integration
    Google Sheets integration
    Email/Slack credentials (optional)
  📄 Resume files in readable PDF format
  📊 Google Sheet prepared with relevant headers

  ✏️ How to customize the workflow

  | Part                        | Customization Options                                                                 |
  |----------------------------|----------------------------------------------------------------------------------------|
  | GPT Prompt             | Tune for different job levels or fields (e.g., engineers vs marketers)                |
  | Field Mapping          | Update transform node to include other profile fields (LinkedIn, portfolio, etc.)     |
  | Notification           | Switch to Microsoft Teams, Telegram, or email alerts instead of Slack                 |
  | Data Store             | Replace Google Sheet with Airtable, Notion, or database system                        |
  | Trigger Source         | Trigger from email attachments or webhook instead of Google Drive if needed           |
  | Output Format          | Generate PDF profile cards or summary documents using HTML → PDF node                 |

nodes_used:
  ["n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","n8n-nodes-base.googleSheets","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.filter","n8n-nodes-base.extractFromFile","n8n-nodes-base.stickyNote","n8n-nodes-base.slack","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 8108 characters]

metadata_json:
  {"categories":["HR","Communication","Data Processing"],"complexity":"simple","use_cases":["extract resume data","catalog candidates","notify hiring team"],"estimated_setup_minutes":5,"required_services":["Google Drive","Slack","GPT-4"],"key_features":["PDF resume parsing","structured data extraction","automated updates","Slack notifications"],"target_audience":["HR managers","recruiters"]}


name: Extract Contacts from Business Cards to Google Sheets With GPT4o
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-08-02T06:44:32.114Z
updated_at: 2025-08-02T06:44:32.114Z
url: https://n8n.io/workflows/6840
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  📄 Auto Extract Contacts from Business Cards to Sheet With GPT4o

  &gt; This smart workflow extracts names, phone numbers, emails, and more from uploaded name card photos using AI, then logs them neatly into your Google Sheet. No typing. No mess. Just upload and go.

  👤 Who’s it for

  Sales & Business Development Teams  
  Recruiters & Talent Acquisition Specialists  
  Event Teams collecting business cards  
  Admins who manage contact databases manually  

  ⚙️ How it works / What it does

  This workflow automates the extraction of contact details from uploaded name card (business card) images and stores them in a structured Google Sheet for easy tracking and follow-up.

  Workflow Steps:
  User uploads one or more name card images through a web form.
  The uploaded files are saved to a Google Drive folder for archiving.
  A smart AI agent (with OCR and GPT capabilities) scans each image and extracts relevant contact data into structured JSON format.
  Data is transformed, cleaned (e.g., removing + from phone numbers), and filtered.
  Valid contacts are appended to a Google Sheet for central tracking and future use.

  🛠 How to set up

  Create a Form  
     Allow file upload (JPG/PNG format).
     Label it as “Name Card Uploader” with a clear description.

  Upload to Google Drive  
     Use the Google Drive node to store uploaded images.

  Configure Smart Agent  
     Use GPT-4o or similar model with OCR capability.
     Apply a structured output parser to extract contact fields like name, phone, email, company, etc.

  Transform Data  
     Use the Code node to clean and structure contact info.
     Strip out unwanted characters from phone numbers (e.g., +).

  Filter Invalid Records  
     Remove entries with no meaningful contact data.

  Append to Google Sheets  
     Use the Google Sheets node with "Append Sheet Row".
     Map fields to columns like Name, Phone, Email, etc.

  ✅ Requirements

  n8n workflow environment  
  Google Drive integration (for file storage)  
  Google Sheets integration (for storing contacts)  
  GPT-4o or any image-capable LLM  
  Clear name card images (PNG/JPG, readable text)  
  (Optional) Slack/email integration for notifications

  🧩 How to customize the workflow

  CRM Sync**: Connect to platforms like HubSpot, Salesforce, or Zoho.  
  Validation Logic**: Ensure records contain key fields like name or email before writing.  
  Uploader Info**: Attach submitter metadata to each contact record.  
  Language Adaptation**: Adjust extracted field labels/output to target your preferred language.  
  Batch Upload**: Handle multiple cards in a single image or multiple uploads in one go.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.formTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.filter","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 6416 characters]

metadata_json:
  {"categories":["AI/ML","Data Processing","Communication"],"complexity":"medium","use_cases":["automating contact entry from business cards","extracting data from card images","uploading contact information to spreadsheets"],"estimated_setup_minutes":15,"required_services":["Google Sheets API","Google Drive API","rich-text model"],"key_features":["OCR using AI vision models","automatic data parsing and extraction","direct integration with spreadsheet systems"],"target_audience":["sales representatives","recruiters","administrative staff"]}


name: Automate weekly Hollywood film briefing via Tavily and Gemini
author_name: Manav Desai
author_username: manavdesai17
categories: []
created_at: 2025-08-02T08:23:11.194Z
updated_at: 2025-08-02T08:23:11.194Z
url: https://n8n.io/workflows/6841
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:21
description:
  This n8n template demonstrates how to build a weekly Hollywood film industry briefing using Tavily for real-time search and Google Gemini for summarization. It sends a concise, emoji‑styled email with movie releases, box office results, industry news, and must‑watch recommendations every week automatically.

  Use cases: Great for film journalists, entertainment bloggers, or movie enthusiasts who want automated weekly updates without manually checking multiple sources.

  Good to know

  Free to use: Tavily provides **1,000 API credits per month on their free plan (no credit card required), so this workflow can run at zero cost.
  Real-time data**: Tavily’s search API is optimized for up-to-date information — perfect for weekly movie releases and box office stats.
  Google Gemini is used for summarization, and you only need basic API access (no paid tier required).

  How it works

  Trigger**: Scheduled every Thursday morning (configurable).
  Search**: Four Tavily API calls gather:

    Movies releasing this week
    Last week’s box office results
    Hollywood industry news
    Must‑watch movies currently in theatres
  Summarization**: Google Gemini turns this into Gmail‑friendly HTML with emojis and bullet points.
  Email**: The formatted newsletter is sent via Gmail node.

  How to use

  Configure Tavily API and Gmail OAuth2 credentials in n8n’s credential manager.
  (Optional) Edit Tavily queries to focus on specific genres or add filters.
  Adjust the schedule trigger to any day/time you prefer.

  Requirements

  Tavily API account (free plan – 1,000 monthly requests)
  Google Gemini API key for summarization
  Gmail account (OAuth2 credentials for sending emails)

  Want insane output quality?

  You can swap Gemini for OpenAI’s ChatGPT models:

  GPT‑3.5 Turbo** – \~\$0.002/run (crazy cheap)
  GPT‑4o** – \~\$0.009/run (latte price)
  GPT‑4.5** – \~\$0.15/run (god‑mode quality)

  This upgrade gives you cleaner, richer, “did‑a‑human‑write‑this?” vibes — perfect for journalist‑grade Hollywood briefings. Just note: OpenAI API requires a \$5 minimum credit to activate usage.

  Example Output (ChatGPT version)

  Subject: Daily Hollywood Film Industry Briefing – August 3, 2025

  Good morning,
  Here's your daily Hollywood film briefing for August 3, 2025:

  🎬 Releases

  The Bad Guys 2 – Released Friday, August 1, 2025
  The Naked Gun – Released Friday, August 1, 2025

  These are the confirmed new wide theatrical Hollywood releases this week (Monday through Sunday of current week). No additional new Hollywood theatrical releases found for this week.

  📊 Box Office

  Highest‑grossing Hollywood films of 2025 (worldwide):

  Ne Zha 2 – approx. \$1.90 billion (non‑Hollywood Chinese animated film leads)
  Lilo & Stitch – approx. \$1.02 billion
  A Minecraft Movie – approx. \$955 million
  Jurassic World Rebirth – approx. \$731 million
  How to Train Your Dragon – approx. \$610 million

  Last week’s box office performance (Monday–Sunday):

  The Fantastic Four: First Steps – domestic debut \\$118 M; global \\$218 M, Marvel’s biggest opening of 2025
  Superman – added \~\$94 M worldwide last week, passing \$500 M global total
  Jurassic World Rebirth – up \\$70 M worldwide last week, despite \40 % drop week‑on‑week
  F1: The Movie – up \~\$48 M last week internationally/domestically growth visible
  Lilo & Stitch – added \~\$10 M worldwide last week, slower tail but still billion‑plus gross

  Highlights & trends:
  Fantastic Four’s strong debut reboots Marvel success, signaling resumed audience interest; Superman continues to hold strong; Jurassic World Rebirth remains durable after holiday surge; surge in box office recovery noted across key titles. Overall box office up \~12–15 % year‑on‑year.

  📰 Industry Buzz

  Christopher Nolan has signed to direct a massive \$250 million adaptation of Homer’s The Odyssey, starring Matt Damon and Tom Holland, with Imax pre‑sales at 95 % capacity across major locations.
  Marvel has relaunched the Fantastic Four franchise successfully with First Steps; positive CinemaScore and strong visuals marking a fresh start.
  DC’s Superman continues strong with over \$500 M global, solidifying DC’s summer comeback.
  Universal’s Jurassic World Rebirth continues strong overseas, especially in China, contributing to \$318 M global in opening holiday weekend.
  Warner Bros.–Discovery stock surges (\~30 %) amid box office rebound, with Disney, IMAX and Cinemark also seeing robust growth in 2025.
  Ne Zha 2 becomes highest‑grossing animated and non‑Hollywood film ever, crossing \$2 billion globally—though not Hollywood, its impact on global trends is notable.
  Mission: Impossible – The Final Reckoning quietly solidifies strong global numbers (\~\$562 M) and continues reliable franchise performance.

  🎥 Must‑Watch in Theatres (Surat, India)

  The Fantastic Four: First Steps** – Currently showing in English/Hindi/Tamil/Telugu in Surat cinemas; hyped globally, strong visuals, action‑heavy, best experienced in IMAX or premium formats if available in Surat multiplexes. Runs this week.
  F1: The Movie** – Available in Surat in multiple languages, strong reviews praising adrenaline‑fuelled direction and visuals and growing fan hype; ideal in standard or Dolby formats for immersive sound and speed feel.
  Jurassic World Rebirth** – Still playing in Surat, popular with family audiences; grand visuals and dinosaur action well‑suited to IMAX or large format screens.

  That’s all for today’s briefing. Have a great theatrical weekend ahead!

nodes_used:
  ["n8n-nodes-base.gmail","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.httpRequestTool","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 9228 characters]

metadata_json:
  {"categories":["AI/ML","Communication"],"complexity":"medium","use_cases":["generate weekly film briefings","summarize entertainment news","send curated movie updates"],"estimated_setup_minutes":15,"required_services":["Tavily","Google Gemini","Email Provider"],"key_features":["natural language search","AI-powered summarization","scheduled automation"],"target_audience":["journalists","entertainment bloggers","film industry professionals"]}


name: Manage Cloudflare DNS Records with AI-powered Chat Assistant
author_name: KPendic
author_username: kres
categories: []
created_at: 2025-08-02T10:45:57.207Z
updated_at: 2025-08-02T10:45:57.207Z
url: https://n8n.io/workflows/6844
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  This n8n flow demos basic dev-ops operation task, dns records management. 

  AI agent with light and basic prompt functions like getter and setter for DNS records. 

  In this special case, we are managing remote dns server, via API calls - that are handled on CloudFlare platform side.

  Use-cases for this flow can be standalone, or you can chain it in your pipe-line to get powerful infrastructure flows for your needs.

  How it works

  we created basic agent and gave it a prompt to know about one tool: cf_tool - sub-routine (to itself flow - or it can be separate dedicated one)
  prompt have defined arguments that are needed for passing them when calling agent, for each action specifically
  tool it self have basic if switch that is - based of a action call - calling specific CloudFlare API endpoint (and pass down the args from the tool)

  Requirements

  For storing and processing of data in this flow you will need:

  CloudFlare.com API key/token - for retrieving your data (https://dash.cloudflare.com/?to=/:account/api-tokens)
  OpenAPI credentials (or any other LLM provider) saved - for agent chat
  (Optional) PostGres table for chat history saving

  Official CloudFlare api Documentation

  For full details and specifications please use API documentation from: https://developers.cloudflare.com/api/

  Linkedin post

  Let me know if you found this flow usefull on my Linkedin post &gt; here.

  tags: #cloudflare, #dns, #domain

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.switch","@n8n/n8n-nodes-langchain.memoryPostgresChat","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.noOp","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.splitOut","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest"]

workflow_json_compressed:
  [encoded data, 4416 characters]

metadata_json:
  {"categories":["DevOps","AI/ML","Communication"],"complexity":"medium","use_cases":["manage DNS records","automate infrastructure tasks","chatbot for dev ops"],"estimated_setup_minutes":15,"required_services":["Cloudflare Workers","Postgres","Chatbot platform","HTTP"],"key_features":["AI-driven task completion","state management","API integration","workflow orchestration"],"target_audience":["DevOps engineers","site administrators","infrastructure managers"]}


name: Generate Animated Human Videos from Images & Audio with Bytedance Omni Human
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T12:19:24.841Z
updated_at: 2025-08-02T12:19:24.841Z
url: https://n8n.io/workflows/6876
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Generate Animated Human Videos from Images & Audio with Bytedance Omni Human

  Built with n8n + Replicate

  This workflow takes an image + audio, sends them to Bytedance’s omni-human model, waits for processing, and returns a generated video.

  ⚡ Section 1: Start & Authenticate

  ▶️ On clicking ‘execute’** → Manual trigger to start the workflow.
  🔑 Set API Key** → Stores your Replicate API key so future requests are authorized.

  Benefit: Secures your API credentials in one place for easy re-use.

  🛠️ Section 2: Send Video Generation Request

  📡 Create Prediction** → Makes a POST request to Replicate with:

    image: input image URL
    audio: input audio URL
    Model version: 7ec44f5140c7338b3496cbf99ee8ea391a4bc18ff5d1677a146dfc936a91f65b

  Benefit: Combines visual and audio inputs to start AI-powered video generation.

  🔍 Section 3: Track the Prediction

  📦 Extract Prediction ID** → Saves predictionId, status, and predictionUrl for polling.
  ⏳ Wait** → Pauses 2 seconds between status checks (to avoid spamming the API).
  🔁 Check Prediction Status** → Queries Replicate using the stored prediction URL.
  ✅ Check If Complete** → Branches:

    If status = succeeded → move forward.
    Else → loop back to Wait until completion.

  Benefit: Ensures workflow patiently waits for the video instead of timing out.

  📽️ Section 4: Process & Return Results

  📦 Process Result** → Cleans the API response, returning:

    status
    video_url (generated video)
    metrics
    created_at & completed_at
    model: bytedance/omni-human

  Benefit: Gives you a neat, structured output with the generated video link ready to use.

  📊 Workflow Overview

  | Section             | Purpose                     | Key Nodes                                     | Benefit                          |
  | ------------------- | --------------------------- | --------------------------------------------- | -------------------------------- |
  | ⚡ Start & Auth      | Initialize & secure API key | Manual Trigger, Set API Key                   | Keeps credentials safe           |
  | 🛠️ Send Request    | Start video generation      | Create Prediction                             | Submits image+audio to Replicate |
  | 🔍 Track Prediction | Poll status until done      | Extract Prediction ID, Wait, Check Status, If | Reliable async handling          |
  | 📽️ Process Result  | Format output               | Process Result                                | Easy access to final video link  |

  ✅ Final Benefits

  🎬 Turns static image + audio into full AI-generated video.
  🔑 API key stored securely in workflow.
  🔄 Handles async generation with auto-polling.
  📤 Outputs clean JSON with direct video link.
  🧩 Modular — you can connect results to Slack, Gmail, or Google Drive for auto-sharing.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4500 characters]

metadata_json:
  {"categories":["AI/ML","Content Creation"],"complexity":"medium","use_cases":["create talking head videos","automate video generation","sync lips to audio"],"estimated_setup_minutes":15,"required_services":["Replicate"],"key_features":["Bytedance Omni Human integration","API key management","manual trigger initiation"],"target_audience":["creators","developers","content producers"]}


name: Convert Multiple Files to Base64 with JavaScript Code
author_name: Viktor Klepikovskyi
author_username: vklepikovskyi
categories: []
created_at: 2025-08-02T12:39:55.614Z
updated_at: 2025-08-02T12:39:55.614Z
url: https://n8n.io/workflows/6885
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Base64 Encode Multiple Binary Files with a Code Node
  This template demonstrates how to handle multiple binary files in n8n by using a Code node to convert them into a Base64 encoded string. It's particularly useful when an API requires file uploads in this format and the standard 'Extract From File' node is not sufficient for batch processing. The workflow starts by downloading a ZIP file, unzipping it to get multiple binary files, and then uses a Code node with custom JavaScript to encode each file individually.
  Instructions
  Download and import this template into your n8n instance.
  Run the workflow once to see how it downloads, unzips, and then encodes multiple files.
  Modify the 'HTTP Request' node to download your own binary file or a ZIP file containing multiple files.
  Update the 'Code' node if you need to adjust the output format or file paths.
  Use the output of the 'Code' node in a subsequent node, such as another 'HTTP Request' to send the Base64-encoded files to your desired API.

  A link to the full blog post is available here.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.compression","n8n-nodes-base.code","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["DevOps"],"complexity":"medium","use_cases":["batch encoding files","API file upload preparation"],"estimated_setup_minutes":15,"required_services":["HTTP APIs"],"key_features":["custom JavaScript execution","binary file processing","batch conversion handling"],"target_audience":["developers","devops engineers"]}


name: Enhance AI Chatbot Responses with InfraNodus Knowledge Graph Reasoning
author_name: InfraNodus
author_username: infranodus
categories: []
created_at: 2025-08-02T13:49:53.846Z
updated_at: 2025-08-02T13:49:53.846Z
url: https://n8n.io/workflows/6887
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  Augment AI chatbot prompts with a knowledge graph reasoning ontology and improve the quality of responses with Graph RAG.

  In this workflow, we augment the original prompt using the InfraNodus GraphRAG system that will extract a reasoning ontology from a graph that you create (or that you can copy from our repository of public graphs). 

  This additional reasoning logic will improve the user's prompt and make it more descriptive and closely related to the logic you want to use. 

  As the next step, you can send it back to the same graph to generate a high-quality response using Graph RAG or to another graph (or AI model) to apply one type of knowledge in a completely different field.

  How it works

  Receives a request from a user (via n8n or a publicly available URL chat bot, you can also connect it to Telegram
  Sends the request to the knowledge graph in your InfraNodus account that contains a reasoning ontology represented as a knowledge graph. Reformulates the original prompt to include the reasoning logic provided. 
  Sends the request to the knowledge graph in your InfraNodus account (same as the previous one or a new one for cross-disciplinary research) to retrieve a high-quality response using GraphRAG

  Special sauce: InfraNodus will build a graph from your augmented prompt, then overlap it on the knowledge graph you want to inquire, traverse this graph based on the overlapped parts and extended relations, then retrieve the necessary part of the graph and include it in the context to improve the quality of your response. This helps InfraNodus grasp the relations and nuances that are not usually available through standard RAG.

  How to use

  • Just get an InfraNodus API key and add it into your Prompt Augmentation and Knowledge Base InfraNodus HTTP nodes for authentication

  • Then provide the name of the graphs you want to be using for prompt augmentation and retrieval. Note, these can be two different graphs if you want to apply a reasoning logic from one domain in another (e.g. machine learning in biology or philosophy in electrical engineering).

  Support

  If you wan to create your own reasoning ontology graphs, please, refer to this article on generating your own knowledge graph ontologies.

  You may also be interested to watch this video that explains the logic of this approach in detail:



  Help article on the same topic: Using knowledge graphs as reasoning experts. 

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["AI/ML","Knowledge Graph"],"complexity":"medium","use_cases":["Improve AI chatbot responses","Augment prompts with ontology","Enhance reasoning in LLM prompts"],"estimated_setup_minutes":15,"required_services":["InfraNodus","Anywording/LLM","HTTP server or Webhook endpoint"],"key_features":["Graph RAG integration","Ontology extraction","Prompt enrichment","Knowledge graph reasoning"],"target_audience":["AI developers","Knowledge engineers","Prompt engineers"]}


name: Generate High-Quality Audio with Voxtral Small 24B 2507
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T14:22:43.454Z
updated_at: 2025-08-02T14:22:43.454Z
url: https://n8n.io/workflows/6890
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Generate High-Quality Audio with Voxtral Small 24B 2507

  This workflow integrates the notdaniel/voxtral-small-24b-2507 model from Replicate to generate audio content from provided inputs. It handles API authentication, creates predictions, polls until completion, and outputs the final generated audio file.

  ⚡ Section 1: Trigger & Authentication

  🔘 On clicking 'execute'** → Manually starts the workflow.
  🔑 Set API Key** → Stores your Replicate API key to authenticate requests.

  Benefit: Securely connects your workflow to Replicate’s API and ensures only authorized requests are made.

  🎛️ Section 2: Create Prediction

  🌐 Create Prediction** → Sends a request to Replicate’s API with parameters like:

    audio: Input audio file (e.g., a reference sample).
    max\_new\_tokens: Maximum number of tokens to generate (controls audio length/complexity).

  Benefit: Starts the audio generation process with configurable input and settings.

  ⏳ Section 3: Polling & Status Tracking

  🆔 Extract Prediction ID** → Captures the unique prediction ID and endpoint for polling.
  ⏱️ Wait** → Pauses for 2 seconds before re-checking.
  📡 Check Prediction Status** → Polls Replicate’s API to see if the audio generation is done.
  ✅ Check If Complete** →

    If finished: moves forward to process results.
    If not: loops back to wait and check again.

  Benefit: Efficiently manages asynchronous audio generation, ensuring the workflow only proceeds when results are ready.

  🎧 Section 4: Process Result

  📝 Process Result** → Extracts and structures final output data:

    status (success or failure)
    output (raw response)
    metrics (generation statistics)
    timestamps (created and completed times)
    audio\_url (final generated audio link)

  Benefit: Provides a clean, structured output that can be used in follow-up automations (e.g., sending audio to users, storing in a database, or sharing via email).

  📊 Workflow Overview

  | Section                     | Purpose                         | Key Nodes                                                               | Benefit                          |
  | --------------------------- | ------------------------------- | ----------------------------------------------------------------------- | -------------------------------- |
  | ⚡ Trigger & Authentication  | Start workflow & authenticate   | Manual Trigger, Set API Key                                             | Secure execution                 |
  | 🎛️ Create Prediction       | Submit audio generation request | Create Prediction                                                       | Start model processing           |
  | ⏳ Polling & Status Tracking | Monitor prediction progress     | Extract Prediction ID, Wait, Check Prediction Status, Check If Complete | Ensures reliable completion      |
  | 🎧 Process Result           | Format and deliver output       | Process Result                                                          | Clean audio result ready for use |

  ✅ Final Benefits

  🔒 Secure authentication with Replicate
  🎛️ Flexible audio generation using voxtral-small-24b-2507
  ⏳ Reliable polling until results are ready
  🎧 Clean and structured audio output

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4524 characters]

metadata_json:
  {"categories":["AI/ML"],"complexity":"medium","use_cases":["generate speech from text","create audio files","synthesize voice content"],"estimated_setup_minutes":15,"required_services":["Replicate"],"key_features":["API authentication","async task polling","audio output generation"],"target_audience":["developers","audio engineers","content creators"]}


name: Automated Trip Expense Claim Form With OpenAI Agent & Google Drive
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-08-02T15:21:04.891Z
updated_at: 2025-08-02T15:21:04.891Z
url: https://n8n.io/workflows/6896
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  🧾 Automated Trip Expense Claim Form With OpenAI Agent & Google Drive
  Watch the demo video below:

  &gt; This workflow is designed for employees who need to submit expense claims for business trips. It automates the process of extracting data from receipts/invoices, logging it to a Google Sheet, and notifying the finance team via email.
  👤 Who’s it for
  Ideal users:
  Employees submitting business trip expense claims
  HR or Admins reviewing travel-related reimbursements
  Finance teams responsible for processing claims

  ⚙️ How it works / What it does

  Employee submits a form with trip information (name, department, purpose, dates) and uploads one or more receipts/invoices (PDF).
  Uploaded files are saved to Google Drive for record-keeping.
  Each PDF is passed to a DocClaim Assistant agent, which uses GPT-4o and a structured parser to extract structured invoice data.
  The data is transformed and formatted into a standard JSON structure.
  Two parallel paths are followed:
     Invoice records are appended to a Google Sheet for centralized tracking.
     A detailed HTML email summarizing the trip and expenses is generated and sent to the finance department for claim processing.

  🛠 How to set up

  Create a form to capture:
     Employee Name
     Department
     Trip Purpose
     From Date / To Date
     Receipt/Invoice File Upload (multiple PDFs)

  Configure file upload node to store files in a specific Google Drive folder.

  Set up DocClaim Agent using:
     GPT-4o or any LLM with document analysis capability
     Output parser for standardizing extracted receipt data (e.g., vendor, total, tax, date)

  Transform extracted data into a structured claim record (Code Node).

  Path 1: Save records to a Google Sheet (one row per expense).

  Path 2:
     Format the employee + claim data into a dynamic HTML email
     Use Send Email node to notify the finance department (e.g., finance@yourcompany.com)

  ✅ Requirements

  n8n running with access to:
    Google Drive API (for file uploads)
    Google Sheets API (for logging expenses)
    Email node (SMTP or Gmail for sending)
  GPT-4o or equivalent LLM with document parsing ability
  PDF invoices with clear formatting
  Shared Google Sheet for claim tracking
  Optional: Shared inbox for finance team

  🧩 How to customize the workflow

  Add approval steps**: route the email to a manager before finance
  Attach original PDFs**: include uploaded files in the email as attachments
  Localize for other languages**: adapt form labels, email content, or parser prompts
  Sync to ERP or accounting system**: replace Google Sheet with QuickBooks, Xero, etc.
  Set limits/validation**: enforce max claim per trip or required fields before submission
  Auto-tag expenses**: add categories (e.g., travel, accommodation) for better reporting

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.formTrigger","n8n-nodes-base.code","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleSheets","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.emailSend","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatOpenAi"]

workflow_json_compressed:
  [encoded data, 9220 characters]

metadata_json:
  {"categories":["Finance","Productivity"],"complexity":"medium","use_cases":["auto-extract receipt details","populate expense claim form","sync data to cloud spreadsheet","summarize expenses with NLP"],"estimated_setup_minutes":45,"required_services":["Google Drive","Google Sheets","OpenAI API","Gmail","Adobe Extractpdf"],"key_features":["OCR receipt parsing","LLM prompt engineering","form trigger integration","spreadsheet data logging","email notifications"],"target_audience":["travel managers","accountants","finance professionals"]}


name: Automate Financial Operations with O3 CFO & GPT-4.1-mini Finance Team
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:00:37.200Z
updated_at: 2025-08-02T18:00:37.200Z
url: https://n8n.io/workflows/6906
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Automate Financial Operations with O3 CFO & GPT-4.1-mini Finance Team

  This workflow builds a virtual finance department inside n8n. At the center is a CFO Agent (O3 model) who acts like a strategic leader. When a financial request comes in, the CFO interprets it, decides the strategy, and delegates to the specialist agents (each powered by GPT-4.1-mini for cost efficiency).

  🟢 Section 1 – Entry & Leadership

  Nodes:

  💬 When chat message received → Entry point for user financial requests.
  💼 CFO Agent (O3) → Acts as the Chief Financial Officer. Interprets the request, decides the approach, and delegates tasks.
  💡 Think Tool → Helps the CFO brainstorm and refine financial strategies.
  🧠 OpenAI Chat Model CFO (O3) → High-level reasoning engine for strategic leadership.

  ✅ Beginner view: Think of this as your finance CEO’s desk — requests land here, the CFO figures out what needs to be done, and the right specialists are assigned.

  📊 Section 2 – Specialist Finance Agents

  Each specialist is powered by GPT-4.1-mini (fast + cost-effective).

  📈 Financial Planning Analyst → Builds budgets, forecasts, and financial models.
  📚 Accounting Specialist → Handles bookkeeping, tax prep, and compliance.
  🏦 Treasury & Cash Management Specialist → Manages liquidity, banking, and cash flow.
  📊 Financial Analyst → Runs KPI tracking, performance metrics, variance analysis.
  💼 Investment & Risk Analyst → Performs investment evaluations, capital allocation, and risk management.
  🔍 Internal Audit & Controls Specialist → Checks compliance, internal controls, and audits.

  ✅ Beginner view: This section is your finance department — every role you’d find in a real company, automated by AI.

  📋 Section 3 – Flow of Execution

  User sends a request (e.g., “Create a financial forecast for Q1 2026”).
  CFO Agent (O3) interprets it → “We need planning, analysis, and treasury.”
  Delegates tasks to the relevant specialists.
  Specialists process in parallel, generating plans, numbers, and insights.
  CFO Agent compiles and returns a comprehensive financial report.

  ✅ Beginner view: The CFO is the conductor, and the specialists are the musicians. Together, they produce the financial “symphony.”

  📊 Summary Table

  | Section                | Key Roles                                               | Model             | Purpose             | Beginner Benefit                       |
  | ---------------------- | ------------------------------------------------------- | ----------------- | ------------------- | -------------------------------------- |
  | 🟢 Entry & Leadership  | CFO Agent, Think Tool                                   | O3                | Strategic direction | Acts like a real CFO                   |
  | 📊 Finance Specialists | FP Analyst, Accounting, Treasury, FA, Investment, Audit | GPT-4.1-mini      | Specialized tasks   | Each agent = finance department role   |
  | 📋 Execution Flow      | All connected                                           | O3 + GPT-4.1-mini | Collaboration       | Output = complete financial management |

  🌟 Why This Workflow Rocks

  Full finance department in n8n**
  Strategic + execution separation** → O3 for CFO, GPT-4.1-mini for team
  Cost-optimized** → Heavy lifting done by mini models
  Scalable** → Easily add more finance roles (tax, payroll, compliance, etc.)
  Practical outputs** → Reports, budgets, risk analyses, audit notes

  👉 Example Use Case:
  “Generate a Q1 financial forecast with cash flow analysis and risk report.”

  CFO reviews request.
  Financial Planning Analyst → Budget + Forecast.
  Treasury Specialist → Cash flow modeling.
  Investment Analyst → Risk review.
  Audit Specialist → Compliance check.
  CFO delivers a packaged financial report back to you.

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.toolThink","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4672 characters]

metadata_json:
  {"categories":["AI/ML","Finance"],"complexity":"complex","use_cases":["automate financial requests","delegate tasks to specialist agents","process financial operations"],"estimated_setup_minutes":30,"required_services":["OpenRouter","Docker"],"key_features":["strategic financial leadership","multi-agent delegation","advanced reasoning"],"target_audience":["finance professionals","workflow architects","business analysts"]}


name: Revenue Growth Strategy with CRO-led Multi-Agent Team using O3 & GPT-4.1-mini
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:01:02.218Z
updated_at: 2025-08-02T18:01:02.218Z
url: https://n8n.io/workflows/6907
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  Revenue Growth Strategy with CRO-led Multi-Agent Team using O3 & GPT-4.1-mini

  🔥 Powered by OpenAI O3 & GPT-4.1-mini Multi-Agent System
  \#RevOps #n8nWorkflows #AIRevenue #OpenAI #GrowthHacking

  ⚡ Section 1: Start & Orchestrator

  💬 Chat Trigger* → Listens for revenue-related requests (e.g., *“Optimize our sales funnel”).
  🤖 CRO Agent (O3)* → Acts as the *Chief Revenue Officer**.

    Thinks strategically with the Think Node.
    Decides which specialist agents to call.
  🧠 OpenAI O3 Model** → Provides advanced reasoning for CRO decisions.

  Benefit: Central orchestration ensures every request gets a strategic, executive-level response before delegation.

  🛠️ Section 2: Specialist Agents

  Each specialist agent uses GPT-4.1-mini for fast, cost-effective execution.
  They receive the CRO’s instructions and return insights.

  📈 Sales Pipeline Analyst

     Funnel optimization, conversion tracking, bottleneck fixes.
     Outputs: Pipeline health, drop-off points, recommendations.

  🎯 Revenue Attribution Specialist

     Multi-touch attribution, ROI analysis, campaign efficiency.
     Outputs: Attribution models, marketing ROI.

  📊 Revenue Forecasting Analyst

     Predictive modeling, scenario planning, growth projections.
     Outputs: Forecast reports, “what-if” scenarios.

  ⚙️ Revenue Operations Manager

     CRM optimization, territory planning, sales automation.
     Outputs: Process improvements, efficiency boosts.

  💰 Pricing & Packaging Strategist

     Competitive pricing analysis, packaging strategy, revenue optimization.
     Outputs: Price models, package recommendations.

  🧠 Revenue Intelligence Analyst

     BI dashboards, performance tracking, KPI insights.
     Outputs: Reports with actionable intelligence.

  Benefit: Breaks complex revenue problems into specialized tasks handled by domain experts.

  🔄 Section 3: Feedback & Integration

  Each agent → sends results back to CRO Agent.
  CRO Agent → compiles a comprehensive revenue strategy.
  Can integrate with CRM, BI dashboards, or Slack/Email for delivery.

  Benefit: Clear, actionable insights delivered in one place — like having a virtual RevOps team on demand.

  📊 Workflow Overview

  | Section                 | Key Nodes                           | Purpose                                           | Benefit                              |
  | ----------------------- | ----------------------------------- | ------------------------------------------------- | ------------------------------------ |
  | ⚡ Start & Orchestration | Chat Trigger, CRO Agent, O3 Model   | Capture request & assign to CRO                   | Centralized leadership               |
  | 🛠️ Specialists         | 6 Agent Nodes + GPT-4.1-mini models | Analyze pipeline, pricing, ops, attribution, etc. | Specialized, cost-efficient insights |
  | 🔄 Feedback Loop        | CRO Agent aggregation               | Compiles strategy from multiple agents            | Unified, data-driven revenue plan    |

  💡 Use Cases

  Pipeline Optimization** → Identify bottlenecks, improve conversions.
  Attribution Modeling** → Know exactly where revenue comes from.
  Revenue Forecasting** → Plan growth scenarios and projections.
  Ops Excellence** → Automate CRM, streamline sales ops.
  Pricing Strategy** → Compete smarter with optimized pricing models.
  Revenue Intelligence** → Ongoing tracking and performance monitoring.

  💸 Cost Optimization

  O3 only for CRO decisions** → Strategic layer.
  GPT-4.1-mini for specialists** → Low-cost execution (\~90% cheaper).
  Parallel processing** → All agents can run simultaneously.

  ✅ Final Result: A virtual AI-powered RevOps team that turns any revenue-related question into a comprehensive growth strategy — instantly.

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.toolThink","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4712 characters]

metadata_json:
  {"categories":["Sales & Revenue","Marketing"],"complexity":"medium","use_cases":["optimize sales funnel","analyze revenue strategy","coordinate multi-agent planning","generate CRO recommendations"],"estimated_setup_minutes":15,"required_services":["OpenAI O3","OpenAI GPT-4.1-mini","N8N"],"key_features":["CRO-led decision making","multi-agent orchestration","sequential task delegation","strategic planning capabilities"],"target_audience":["revenue managers","marketing leads","growth hackers"]}


name: Comprehensive SEO Strategy with O3 Director & GPT-4 Specialist Team
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:01:26.784Z
updated_at: 2025-08-02T18:01:26.784Z
url: https://n8n.io/workflows/6908
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Comprehensive SEO Strategy with O3 Director & GPT-4 Specialist Team

  Trigger

     When chat message received → User submits an SEO request (e.g., “Help me rank for project management software”).
     The message goes straight to the SEO Director Agent.

  SEO Director Agent (O3)

     Acts like the head of SEO strategy.
     Uses the Think node to plan and decide which specialists to call.
     Delegates tasks to relevant agents.

  Specialist Agents (GPT-4.1-mini)

     Each agent has its own OpenAI model connection for lightweight cost-efficient execution.
     Tasks include:

       Keyword Research Specialist → Keyword discovery, clustering, competitor analysis.
       SEO Content Writer → Generates optimized blog posts, landing pages, etc.
       Technical SEO Specialist → Site audit, schema markup, crawling fixes.
       Link Building Strategist → Backlink strategies, outreach campaign ideas.
       Local SEO Specialist → Local citations, GMB optimization, geo-content.
       Analytics Specialist → Reports, performance insights, ranking metrics.

  Feedback Loop

     Each agent sends results back to the SEO Director.
     Director compiles insights into a comprehensive SEO campaign plan.

  ✅ Why This Setup Works Well

  O3 Model for Director** → Handles reasoning-heavy orchestration (strategy, delegation).
  GPT-4.1-mini for Specialists** → Cheap, fast, task-specific execution.
  Parallel Execution** → All specialists can run at the same time.
  Scalable & Modular** → You can add/remove agents depending on campaign needs.
  Sticky Notes** → Already document the workflow (great for onboarding & sharing).

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.toolThink","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["Marketing","AI/ML"],"complexity":"medium","use_cases":["conducting SEO research","generating ranking strategies","analyzing competitor data"],"estimated_setup_minutes":120,"required_services":["OpenAI","Telegram"],"key_features":["multi-agent collaboration","hierarchical task delegation","dynamic specialist selection"],"target_audience":["SEO professionals","marketing managers","content strategists"]}


name: Multi-Agent Cold Email Campaign Generator with O3 Director & GPT-4.1 Specialists
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:01:52.773Z
updated_at: 2025-08-02T18:01:52.773Z
url: https://n8n.io/workflows/6909
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Multi-Agent Cold Email Campaign Generator with O3 Director & GPT-4.1 Specialists

  🌍 Overview

  This workflow simulates a virtual sales & marketing team where each AI agent has a role:

  A Director Agent (O3) who manages strategy.
  Multiple Specialist Agents (GPT-4.1-mini) for research, writing, personalization, deliverability, sequencing, and analytics.
  Everything is triggered automatically when a new chat message request comes in.

  🟢 Section 1: Entry & Director

  🔗 Nodes:
  1️⃣ When chat message received (Trigger)
  💬 Starts the workflow when a new request arrives (e.g., “Create a cold email campaign for SaaS CTOs”).

  2️⃣ Outreach Director Agent (O3 model)
  🎯 The “manager” agent. Decides what kind of campaign is needed and assigns tasks.

  3️⃣ Think (Planning Node)
  🧠 Helps the Director structure thoughts before delegating.

  💡 Why useful?

  Director uses O3 (strong reasoning model) only where strategy is needed → reduces cost.
  Provides a single point of control to coordinate all other agents.

  🔵 Section 2: Specialist Agents

  Each is powered by GPT-4.1-mini (cheaper + faster).

  🔍 Prospect Research Specialist → researches target companies, roles, pain points.
  ✍️ Cold Email Copywriter → drafts subject lines, hooks, and persuasive body copy.
  🎯 Personalization Specialist → inserts custom variables for each recipient.
  📅 Email Sequence Strategist → designs follow-ups, timing, nurture flows.
  📬 Email Deliverability Expert → ensures emails land in inbox, not spam.
  📊 Outreach Analytics Specialist → tracks performance, runs A/B tests, optimizes campaigns.

  💡 Why useful?

  Each agent is a specialist → just like a real marketing team.
  Parallel execution** in n8n means faster results.
  Modular → you can remove or add more specialists.

  🟣 Section 3: Execution Flow

  Request comes in via chat trigger
  Director (O3) interprets and delegates → calls specialists as tools
  Specialists generate their pieces (research → copy → personalization → sequence → deliverability → analytics)
  Director integrates results into a cohesive cold email campaign

  🟡 Section 4: Documentation & Notes

  There are two Sticky Notes inside the workflow:

  Header Note** → Support info + tutorials (YouTube & LinkedIn by Yaron Been)
  Main Note** → Full documentation (overview, use cases, cost optimization, tags)

  📊 Final Overview

  | Section        | What Happens             | Why It’s Useful             |
  | -------------- | ------------------------ | --------------------------- |
  | 🟢 Director    | Trigger + O3 strategy    | Ensures smart coordination  |
  | 🔵 Specialists | GPT-4.1-mini agents      | Faster, cheaper execution   |
  | 🟣 Flow        | Delegation + Integration | Automated campaign building |
  | 🟡 Docs        | Sticky Notes             | In-workflow guide for users |

  🚀 Benefits

  ✅ AI-powered cold email team without hiring humans
  ✅ Cost-optimized (O3 only for strategy, GPT-4.1-mini for tasks → \~90% cheaper)
  ✅ End-to-end coverage (research → writing → personalization → sequencing → analytics)
  ✅ Scalable: can run multiple campaigns in parallel
  ✅ Customizable: swap models, add tools, or expand team

nodes_used:
[cell repeats an earlier one in this file: 668 characters]

workflow_json_compressed:
  [encoded data, 4712 characters]

metadata_json:
  {"categories":["Marketing","Communication","AI/ML"],"complexity":"medium","use_cases":["generate cold email campaigns","simulate sales teams","automate marketing outreach"],"estimated_setup_minutes":15,"required_services":["oobabooga","o3"],"key_features":["multi-agent orchestration","role-based AI agents","automated campaign generation"],"target_audience":["industrial engineers","AI researchers"]}


name: Create Multi-Channel Content with O3 Director & GPT-4 Specialist Agents
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:02:16.967Z
updated_at: 2025-08-02T18:02:16.967Z
url: https://n8n.io/workflows/6910
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Create Multi-Channel Content with O3 Director & GPT-4 Specialist Agents

  This n8n workflow creates a complete AI-powered content department. It starts when a chat request is received, then a Content Director Agent (powered by OpenAI O3) analyzes the request and delegates tasks to specialized agents (blogs, social, video, email, website, strategy). Each agent is powered by GPT-4.1-mini, keeping costs low and quality high.

  ✅ 📩 Section 1: Trigger & Director Setup

  ⚙️ Nodes

  1️⃣ When Chat Message Received

  What it does:** Starts the workflow whenever a user sends a content request.
  Why it’s useful:** Allows real-time or on-demand content creation from chat inputs.

  2️⃣ Content Director Agent (O3)

  What it does:** Analyzes user request, defines the best content mix, and delegates tasks to specialist agents.
  Why it’s useful:** Keeps your brand voice consistent and ensures all channels align to a unified content strategy.

  💡 Beginner Benefit

  ✅ Single entry point → just type your content idea once
  ✅ AI Director coordinates everything for you
  ✅ No need to manage multiple tools

  ✅ 👥 Section 2: Specialist Content Agents

  Each request gets routed to one (or several) of these agents, depending on the strategy.

  3️⃣ Blog Content Writer

  Long-form articles, editorials, and thought leadership pieces.

  4️⃣ Social Media Content Creator

  Social posts, captions, hashtags, and community content.

  5️⃣ Video Script Writer

  YouTube scripts, explainer videos, and video marketing content.

  6️⃣ Email Newsletter Writer

  Campaigns, nurture sequences, and newsletter copy.

  7️⃣ Website Copy Specialist

  Landing pages, product descriptions, and conversion-focused web copy.

  8️⃣ Content Strategist & Planner
  Editorial calendars, campaign planning, and audience strategy.

  💡 Beginner Benefit

  ✅ Each agent is an expert in its field
  ✅ Powered by GPT-4.1-mini → faster and cheaper
  ✅ Parallel execution → all content types can be generated at once

  ✅ 🧠 Section 3: Language Models & Execution Flow

  O3 Model → Content Director**

    Handles analysis, strategy, and delegation.

  GPT-4.1-mini → All Specialists**

    Powers blog, social, video, email, website, and strategy agents.

  Think Node**

    Helps the Content Director organize reasoning before delegating tasks.

  💡 Beginner Benefit

  ✅ AI Director (O3) = smart leadership
  ✅ Specialists (GPT-4.1-mini) = cost-efficient execution
  ✅ Built-in reasoning = better, more aligned campaigns

  📊 Workflow Overview

  | Section                     | What Happens                                                    | Key Benefit                |
  | --------------------------- | --------------------------------------------------------------- | -------------------------- |
  | 📩 Trigger & Director Setup | Workflow starts from chat → Content Director interprets request | Centralized control        |
  | 👥 Specialist Agents        | Each AI agent produces tailored content                         | Multi-channel coverage     |
  | 🧠 Models & Flow            | O3 for Director, GPT-4.1-mini for specialists                   | Cost-efficient + strategic |

  📌 How You Benefit Overall

  ✅ One input → full content campaign
  ✅ Consistent brand voice across all platforms
  ✅ Cost-effective (O3 only for strategy, GPT-4.1-mini for bulk work)
  ✅ Ready-to-publish content in minutes

  ✨ You’ve basically built an AI marketing department inside n8n — no extra staff required! 🚀

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.toolThink","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi"]

workflow_json_compressed:
  [encoded data, 4504 characters]

metadata_json:
  {"categories":["AI/ML","Marketing","Communication"],"complexity":"medium","use_cases":["automated content generation","multi-channel marketing automation","AI agent orchestration"],"estimated_setup_minutes":30,"required_services":["OpenAI O3","OpenAI GPT-4.1-mini","chat platform trigger"],"key_features":["hierarchical agent delegation","specialized content creation agents","cost-optimized model routing"],"target_audience":["content strategists","marketing managers","AI developers"]}


name: Creative Design Agency Simulation with OpenAI O3 and GPT-4.1-mini Multi-Agent
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:03:54.373Z
updated_at: 2025-08-02T18:03:54.373Z
url: https://n8n.io/workflows/6914
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Creative Design Agency Simulation with OpenAI O3 and GPT-4.1-mini Multi-Agent Team

  This n8n workflow simulates a full-service creative agency powered by AI. At the center is a Creative Director Agent (O3 model) who takes client requests, plans the creative direction, and delegates work to a specialized design team. Each specialist runs on GPT-4.1-mini, keeping execution fast and cost-efficient.

  🟢 Section 1 – Entry & Strategic Leadership

  Nodes:

  💬 When chat message received → Entry point, listens for design briefs.
  🎨 Creative Director Agent (O3) → The “agency head” who interprets requirements and decides which specialists to involve.
  💡 Think Tool → Helps the Director brainstorm, evaluate alternatives, and refine direction.
  🧠 OpenAI Chat Model Director (O3) → Strategic reasoning engine for the Director.

  ✅ Benefit for beginners: Think of this as the project manager’s desk — you submit a design request, and the Director figures out how to make it happen.

  ✍️ Section 2 – Core Creative Specialists

  Nodes:

  🖼️ Graphic Designer → Logos, visual identity, print, packaging.
  📱 UI/UX Designer → Wireframes, prototypes, interaction design.
  🎯 Brand Strategist → Market positioning, brand guidelines, competitive research.
  📝 Creative Copywriter → Taglines, messaging, campaign copy.

  Each agent is powered by GPT-4.1-mini.

  ✅ Benefit for beginners: This section is your creative studio team — they craft visuals, design user experiences, and write compelling words.

  🚀 Section 3 – Extended Design & Motion Team

  Nodes:

  🎬 Motion Graphics Designer → Animations, promo videos, explainer graphics.
  🌐 Web Designer → Websites, responsive layouts, accessibility improvements.
  🖌️ OpenAI Chat Model Agents (GPT-4.1-mini) → Back each specialist with creative power.

  ✅ Benefit for beginners: This section brings motion and web into the mix, ensuring your creative package isn’t static — it moves, animates, and lives online.

  📊 Summary Table

  | Section             | Key Roles                         | Model        | Purpose               | Beginner Benefit                      |
  | ------------------- | --------------------------------- | ------------ | --------------------- | ------------------------------------- |
  | 🟢 Entry & Strategy | Chat Trigger, Director, Think     | O3           | Leadership & planning | Turns briefs into action plans        |
  | ✍️ Core Creatives   | Graphic, UI/UX, Brand, Copywriter | GPT-4.1-mini | Design & content      | Produces visuals, UX, and words       |
  | 🚀 Extended Team    | Motion Graphics, Web              | GPT-4.1-mini | Motion & web design   | Animates, builds, and scales projects |

  🌟 Why This Workflow Rocks

  Complete agency in a box** → Strategy + Design + Motion + Web + Copy
  Smart leadership** → Director (O3) only used for high-level thinking
  Cost-effective execution** → GPT-4.1-mini runs most tasks
  Parallel creativity** → Specialists work simultaneously
  Scalable** → Adaptable to any design or branding request

  👉 Example: Send a message like “Design a brand identity for a sustainable clothing startup”.
  Within minutes, your AI agency produces:

  A logo & color scheme 🎨
  A UX prototype 📱
  A brand positioning doc 🎯
  Animated ad ideas 🎬
  Website mockups 🌐
  A tagline & ad copy ✍️

nodes_used:
[cell repeats an earlier one in this file: 668 characters]

workflow_json_compressed:
  [encoded data, 4656 characters]

metadata_json:
  {"categories":["AI/ML","Creative Design"],"complexity":"medium","use_cases":["run multi-agent creative workflows","simulate AI design teams","automate client proposal generation","coordinate AI agent task delegation"],"estimated_setup_minutes":25,"required_services":["OpenAI","ElevenLabs","Notion","webhook"],"key_features":["specialized AI agent roles","multi-model orchestration","dynamic tool execution","strategic planning delegation"],"target_audience":["creative directors","developers","agency managers"]}


name: Amplify Social Media Presence with O3 and GPT-4 Multi-Agent Team
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:04:18.274Z
updated_at: 2025-08-02T18:04:18.274Z
url: https://n8n.io/workflows/6915
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  Amplify Social Media Presence with O3 and GPT-4 Multi-Agent Team

  🌍 Overview

  This n8n workflow acts like a virtual social media department. A Social Media Director Agent coordinates multiple specialized AI agents (Instagram, Twitter/X, Facebook, TikTok, YouTube, and Analytics). Each agent creates or analyzes content for its platform, powered by OpenAI models.

  The result? A fully automated, cross-platform social media strategy—from content creation to performance tracking.

  🟢 Section 1: Trigger & Director Setup

  🔗 Nodes:

  When chat message received (Trigger)** → Starts the workflow whenever you send a request (e.g., “Plan a TikTok campaign for my product launch”).
  Social Media Director Agent* (connected to *OpenAI O3 model**) → Acts as the strategist.
  Think Tool** → Helps the Director “reason” before delegating.

  💡 Beginner takeaway:
  This section makes your workflow interactive. You send a request → the Director decides the best approach → then it assigns tasks.

  📈 Advantage:
  Instead of manually planning content per platform, you only send one command, and the AI Director handles the strategy.

  🟦 Section 2: Specialized Social Media Agents

  🔗 Nodes (each paired with GPT-4.1-mini):

  📸 Instagram Content Creator → Visual storytelling, Reels, Hashtags
  🐦 Twitter/X Strategist → Viral tweets, trends, engagement
  👥 Facebook Community Manager → Audience growth, ads, group engagement
  🎵 TikTok Video Creator → Short-form video, viral trends
  🎬 YouTube Content Planner → Long-form strategy, SEO, thumbnails
  📊 Analytics Specialist → Performance insights, cross-platform reporting

  💡 Beginner takeaway:
  Each platform has its own AI expert. They receive the Director’s strategy and produce tailored content for their platform.

  📈 Advantage:
  Instead of one-size-fits-all posts, you get optimized content per platform—increasing reach and engagement.

  🟣 Section 3: Models & Connections

  🔗 Nodes:

  OpenAI Chat Models** (O3 + multiple GPT-4.1-mini models)
  Each model is connected to its respective agent.

  💡 Beginner takeaway:
  Think of these as the “brains” behind each specialist. The Director uses O3 for advanced reasoning, while the specialists use GPT-4.1-mini (cheaper, faster) for content generation.

  📈 Advantage:
  This keeps costs low while maintaining quality output.

  📊 Final Overview Table

  | Section               | Nodes                                                    | Purpose                                | Benefit                        |
  | --------------------- | -------------------------------------------------------- | -------------------------------------- | ------------------------------ |
  | 🟢 Trigger & Director | Chat Trigger, Director, Think Tool                       | Capture requests & plan strategy       | One command → full social plan |
  | 🟦 Specialists        | Instagram, Twitter, Facebook, TikTok, YouTube, Analytics | Platform-specific content              | Optimized posts per platform   |
  | 🟣 Models             | O3 + GPT-4.1-mini                                        | Provide reasoning & content generation | High-quality, cost-efficient   |

  🚀 Why This Workflow is Powerful

  Multi-platform coverage**: All major platforms handled in one flow
  Human-like strategy**: Director agent makes real marketing decisions
  Scalable & fast**: Generate a full campaign in minutes
  Cost-effective**: O3 only for strategy, GPT-4.1-mini for bulk content
  Beginner-friendly**: Just type your request → get full campaign output

nodes_used:
[cell repeats an earlier one in this file: 668 characters]

workflow_json_compressed:
  [encoded data, 4644 characters]

metadata_json:
  {"categories":["AI/ML"],"complexity":"medium","use_cases":["automate social media content creation","manage multi-platform posting","track social analytics"],"estimated_setup_minutes":120,"required_services":["OpenAI API"],"key_features":["multi-agent team coordination","cross-platform social management","auto content optimization"],"target_audience":["marketing managers","social media specialists","content creators"]}


name: Create Viral LinkedIn Content with O3 & GPT-4.1-mini Multi-Agent Team
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:04:42.673Z
updated_at: 2025-08-02T18:04:42.673Z
url: https://n8n.io/workflows/6916
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Create Viral LinkedIn Content with O3 & GPT-4.1-mini Multi-Agent Team

  This n8n workflow is a multi-agent LinkedIn content factory.
  At its heart is the Content Director Agent (O3 model), who acts as the project manager. It listens for LinkedIn chat messages, analyzes them, and coordinates a team of AI specialists (all powered by GPT-4.1-mini) to produce viral, engaging, and optimized LinkedIn content.

  🟢 Section 1 – Workflow Entry & Strategy Layer

  Nodes:

  🔔 When chat message received → Captures LinkedIn requests (your idea, draft, or prompt).
  🧠 Content Director Agent (O3) → Acts as the leader, deciding how the content should be structured and which specialists to call.
  💡 Think Node → Helps the Director brainstorm and evaluate possible approaches before delegating.
  🤖 OpenAI Chat Model Director (O3) → The Director’s brain, providing strategic-level thinking.

  ✅ Beginner-friendly benefit: This section is like the “command center.” Any LinkedIn content request starts here and gets transformed into a clear, strategic plan before moving to specialists.

  ✍️ Section 2 – Content Creation Specialists

  Nodes:

  ✍️ LinkedIn Copywriter → Creates viral hooks, compelling posts, and platform-friendly messaging.
  🎓 Domain Expert → Ensures technical accuracy and industry authority in the post.
  📝 Proofreader & Editor → Polishes content for grammar, tone, and style.

  Each agent connects to its own GPT-4.1-mini model for cost-efficient, specialized output.

  ✅ Beginner-friendly benefit: This section is like your content writing team—from drafting, to adding expertise, to polishing for professional LinkedIn standards.

  🚀 Section 3 – Engagement & Optimization Specialists

  Nodes:

  🚀 Engagement Strategist → Crafts hashtags, posting times, and audience growth strategies.
  🎨 Visual Content Strategist → Designs carousels, infographics, and visual ideas.
  📊 Content Performance Analyst → Tracks analytics, measures performance, and suggests improvements.

  Each of these also relies on GPT-4.1-mini, keeping cost low while delivering specialized insights.

  ✅ Beginner-friendly benefit: This section is like your growth & marketing team—they ensure your content doesn’t just look good but also performs well and reaches the right audience.

  📊 Summary Table

  | Section                      | Key Nodes                              | Role                 | Beginner Benefit                        |
  | ---------------------------- | -------------------------------------- | -------------------- | --------------------------------------- |
  | 🟢 Entry & Strategy          | Trigger, Director, Think, O3 Model     | Strategy & planning  | Turns your idea into a clear strategy   |
  | ✍️ Content Creation          | Copywriter, Domain Expert, Proofreader | Writing & refinement | Produces expert-level, polished content |
  | 🚀 Engagement & Optimization | Engagement, Visuals, Analytics         | Growth & performance | Maximizes reach, visuals, and results   |

  🌟 Why This Workflow Rocks

  All-in-one content team** → Strategy + Writing + Optimization
  Low cost** → O3 only for strategy, GPT-4.1-mini for specialists
  Parallel agents** → Work simultaneously for faster results
  Scalable** → Reusable for any LinkedIn content need

  👉 Even a beginner can use this workflow: just send a LinkedIn content idea (e.g., “Write a post on AI in finance”), and your AI team handles the rest—writing, polishing, visuals, and engagement tactics.

nodes_used:
[cell repeats an earlier one in this file: 668 characters]

workflow_json_compressed:
  [encoded data, 4680 characters]

metadata_json:
  {"categories":["Marketing","AI/ML"],"complexity":"medium","use_cases":["generating viral content","social media automation","multi-agent collaboration"],"estimated_setup_minutes":15,"required_services":["O3 AI model","GPT-4.1-mini","LinkedIn"],"key_features":["content strategy planning","multi-agent workflow","automated social posting"],"target_audience":["social media managers","content creators","marketing teams"]}


