Workflow Templates

Generate AI Voiceovers from Scripts and Upload to Google Drive This is the final piece of the AI content factory. This workflow takes your text-based video scripts and automatically generates high-quality audio voiceovers for each one, turning your text into ready-to-use audio assets for your video ads. Go from a spreadsheet of text to a folder of audio files, completely on autopilot. ⚠️ CRITICAL REQUIREMENTS (Read First!) This is an advanced, self-hosted workflow that requires specific local setup: Self-Hosted n8n Only:** This workflow uses the Execute Command and Read/Write Files nodes, which requires you to run your own instance of n8n. It will not work on n8n Cloud. FFmpeg Installation:** You must have FFmpeg installed on the same machine where your n8n instance is running. This is used to convert the audio files to a standard format. What it does This is Part 3 of the AI marketing series. It connects to the Google Sheet where you generated your video scripts (in Part 2). For each script that hasn't been processed, it: Uses the Google Gemini Text-to-Speech (TTS) API to generate a voiceover. Saves the audio file to your local computer. Uses FFmpeg to convert the raw audio into a standard .wav file. Uploads the final .wav file to your Google Drive. Updates the original Google Sheet with a link to the audio file in Drive and marks the script as complete. How to set up IMPORTANT: This workflow is Part 3 of a series and requires the output from Part 2 ("Generate AI Video Ad Scripts"). If you need Part 1 or Part 2 of this workflow series, you can find them for free on my n8n Creator Profile. Connect to Your Scripts Sheet: In the "Getting Video Scripts" node, connect your Google Sheets account and provide the URL to the sheet containing your generated video scripts from Part 2. Configure AI Voice Generation (HTTP Request): In the "HTTP Request To Generate Voice" node, go to the Query Parameters and replace INSERT YOUR API KEY HERE with your Google Gemini API key. In the JSON Body, you can customize the voice prompt (e.g., change <INSERT YOUR DESIRED ACCENT HERE>). Set Your Local File Path: In the first "Read/Write Files from Disk" node, update the File Name field to a valid directory on your local machine where n8n has permission to write files. Replace /Users/INSERT_YOUR_LOCAL_STORAGE_HERE/. Connect Google Drive: In the "Uploading Wav File" node, connect your Google Drive account and choose the folder where your audio files will be saved. Update Your Tracking Sheet: In the final "Uploading Google Drive Link..." node, ensure it's connected to the same Google Sheet from Step 1. This node will update your sheet with the results. Name and Description for Submission Form Here are the name and description, updated with the new information, ready for you to copy and paste. Name: Generate AI Voiceovers from Scripts and Upload to Google Drive Description: Welcome to the final piece of the AI content factory! 🔊 This advanced workflow takes the video ad scripts you've generated and automatically creates high-quality audio voiceovers for each one, completing your journey from strategy to ready-to-use media assets. ⚠️ This is an advanced workflow for self-hosted n8n instances only and requires FFmpeg to be installed locally. ⚙️ How it works This workflow is Part 3 of a series. It reads your video scripts from a Google Sheet, then for each script it: Generates a voiceover using the Google Gemini TTS API. Saves the audio file to your local machine. Converts the file to a standard .wav format using FFmpeg. Uploads the final audio file to Google Drive. Updates your Google Sheet with a link to the new audio file. 👥 Who’s it for? Video Creators & Marketers: Mass-produce voiceovers for video ads, tutorials, or social media content without hiring voice actors. Automation Power Users: A powerful example of how n8n can bridge cloud APIs with local machine commands. Agencies: Drastically speed up the production of audio assets for client campaigns. 🛠️ How to set up This workflow requires specific local setup due to its advanced nature. IMPORTANT: This is Part 3 of a series. To find Part 1 ("Generate a Strategic Plan") and Part 2 ("Generate Video Scripts"), please visit my n8n Creator Profile where they are available for free. Setup involves connecting to your scripts sheet, configuring the AI voice API, setting a local file path for n8n to write to, and connecting your Google Drive.

Automatically fetches daily sales, shifts, and receipts from Loyverse. Calculates gross profit, net operating profit, other key metrics, saves them to a Google Sheet and sends out a daily report via email. Who’s it for This template is for any business owner, manager, or analyst using Loyverse POS who needs more advanced financial reporting. If you're a restaurant, bar, or retail owner who wants to automatically track daily net profit, compare sales to historical averages, and build a custom financial dashboard in Google Sheets, this workflow is for you. How it works / What it does This workflow runs automatically on a daily schedule. It fetches all sales data and receipts from your Loyverse account for the previous business day, defined by your custom shift times (even past midnight). A powerful Code node then processes all the data to calculate the metrics that Loyverse either doesn't provide at all, or only spreads out across several separate reports instead of in one consolidated place. Already set up are metrics like... -Total Revenue, Gross Profit, and Net Operating Profit Cash handling differences (over/under) Average spend per receipt (ATV) 30-day rolling Net Operating Profit (NOP) Performance vs. your historical weekday average Finally, it appends the single, calculated row of daily metrics to a Google Sheet and sends an easily customizable summary report to your email. How to set up This workflow includes detailed Sticky Notes to guide you through the setup process. Because every business has a unique POS configuration (different POS devices, categories, and payment types), you'll need to set up a few things manually before executing the workflow. I've tried to make this as easy as possible to follow, and the entire setup should only take about 15 minutes. Preparations & Credential setup Subscribe to "Integrations" Add-on in Loyverse ($9 / month) to gain API access. Create an Access token in Loyverse Create Credentials: In your n8n instance, create credentials for Loyverse (use "Generic" > "Bearer Auth"), Google Sheets (OAuth2), and your Email (SMTP or other). Make a copy of a prep-configured Google Spreadsheet (Link in the second sticky note inside the workflow). Fill MASTER CONFIG: Open the MASTER CONFIG node. Follow the comments inside to add your Google Sheet ID, Sheet Names, business hours, timezone, and Loyverse IDs (for POS devices, payment types, and categories). Configure Google Sheet Nodes Configure Read Historical Data: Open this node. Follow the instructions in the nearby Sticky Note to paste the expressions for your Document ID and Sheet Name. Configure Save Product List: Open this node. Paste in the expressions for Document ID and Sheet Name. The column mapper will load; map your sheet columns (e.g., item_name) to the data on the left (e.g., {{ $json.item_name }}). Configure Save Latest Sales Data: Open this node. Paste in the expressions for Document ID and Sheet Name. Save and run the workflow. After that, the column mapper will load. This is the most important step: map your sheet's column names (e.g., "Total Revenue") to the calculated metrics from the Calculate All Metrics node (e.g., {{ $json.totalGrossRevenue }}). Activate the workflow. 🫡 Requirements Loyverse Integrations Subscription Loyverse Access Token Credentials for Loyverse (Bearer Auth) Credentials for Google Sheets (OAuth2) Credentials for Email/SMTP sender How to customize the workflow This template is designed to be highly flexible. Central Configuration: Almost all customization (POS devices, categories, payment types, sheet names) is done in the MASTER CONFIG node. You don't need to dig through other nodes. Add/Remove Metrics: The Calculate All Metrics node has additional metrics already set up, just add the relevant collumns to the SalesData sheet or even add your own calculations to the node. Any new metric you add (e.g., metrics.myNewMetric = 123) will be available to map in the Save Latest Sales Data node. Email Body: You can easily edit the Send email node to change the text or add new metrics from the Calculate All Metrics node.

This template introduces a revolutionary approach to automated web research. Instead of a rigid workflow that can only find one type of information, this system uses a "thinker" and "doer" AI architecture. It dynamically interprets your plain-English research request, designs a custom spreadsheet (CSV) with the perfect columns for your goal, and then deploys a web-scraping AI to fill it out. It's like having an expert research assistant who not only finds the data you need but also builds the perfect container for it on the fly. Whether you're looking for sales leads, competitor data, or market trends, this workflow adapts to your request and delivers a perfectly structured, ready-to-use dataset every time. Who is this for? Sales & marketing teams:** Generate targeted lead lists, compile competitor analysis, or gather market intelligence with a simple text prompt. Researchers & analysts:** Quickly gather and structure data from the web for any topic without needing to write custom scrapers. Entrepreneurs & business owners:** Perform rapid market research to validate ideas, find suppliers, or identify opportunities. Anyone who needs structured data:** Transform unstructured, natural language requests into clean, organized spreadsheets. What problem does this solve? Eliminates rigid, single-purpose workflows:** This workflow isn't hardcoded to find just one thing. It dynamically adapts its entire research plan and data structure based on your request. Automates the entire research process:** It handles everything from understanding the goal and planning the research to executing the web search and structuring the final data. Bridges the gap between questions and data:** It translates your high-level goal (e.g., "I need sales leads") into a concrete, structured spreadsheet with all the necessary columns (Company Name, Website, Key Contacts, etc.). Optimizes for cost and efficiency:* It intelligently uses a combination of deep-dive and standard web searches from *Linkup.so** to gather high-quality initial results and then enrich them cost-effectively. How it works (The "Thinker & Doer" Method) The process is cleverly split into two main phases: The "Thinker" (AI Planner): You submit a research request via the built-in form (e.g., "Find 50 US-based fashion companies for a sales outreach campaign"). The first AI node acts as the "thinker." It analyzes your request and determines the optimal structure for your final spreadsheet. It dynamically generates a plan, which includes a discoveryQuery to find the initial list, an enrichmentQuery to get details for each item, and the JSON schemas that define the exact columns for your CSV. The "Doer" (AI Researcher): The rest of the workflow is the "doer," which executes the plan. Discovery: It uses a powerful "deep search" with Linkup.so to execute the discoveryQuery and find the initial list of items (e.g., the 50 fashion companies). Enrichment: It then loops through each item in the list. For each one, it performs a fast and cost-effective "standard search" with Linkup to execute the enrichmentQuery, filling in all the detailed columns defined by the "thinker." Final Output: The workflow consolidates all the enriched data and converts it into a final CSV file, ready for download or further processing. Setup Connect your AI provider: In the OpenAI Chat Model node, add your AI provider's credentials. Connect your Linkup account: In the two Linkup (HTTP Request) nodes, add your Linkup API key (free account at linkup.so). We recommend creating a "Generic Credential" of type "Bearer Token" for this. Linkup offers €5 of free credits monthly, which is enough for 1k standard searches or 100 deep queries. Activate the workflow: Toggle the workflow to "Active." You can now use the form to submit your first research request! Taking it further Add a custom dashboard:** Replace the form trigger and final CSV output with a more polished user experience. For example, build a simple web app where users can submit requests and download their completed research files. Make it company-aware:** Modify the "thinker" AI's prompt to include context about your company. This will allow it to generate research plans that are automatically tailored to finding leads or data relevant to your specific products and services. Add an AI summary layer:** After the CSV is generated, add a final AI node to read the entire file and produce a high-level summary, such as "Here are the top 5 leads to contact first and why," turning the raw data into an instant, actionable report.

Overview This n8n template automates the entire process of generating short-form AI videos and publishing them across multiple social media platforms. It combines Google Gemini for structured prompt creation, KIE AI for video generation, and Blotato for centralized publishing. The result is a fully automated content pipeline ideal for creators, marketers, agencies, or anyone who wants consistent, hands-free content generation. This workflow is especially useful for short-video creators, meme pages, educational creators, UGC teams, auto-posting accounts, and brands who want to maintain high-frequency posting without manual effort. Good to Know API costs:** KIE AI generates videos using paid tokens/credits. Prices vary based on model, duration, and resolution (check KIE AI pricing). Google Gemini model restrictions:** Certain Gemini models are geo-limited. If you receive “model not found,” the model may not be available in your region. Blotato publishing:** Blotato supports many platforms: YouTube, Instagram, Facebook, LinkedIn, TikTok, X, Bluesky, and more. Platform availability depends on your Blotato setup. Runtime considerations:** Video generation can take time (10–60 seconds+, depending on the complexity). Self-hosted requirement:** This workflow uses a community node (Blotato). Community nodes do not run on n8n Cloud. A self-hosted instance is required. How It Works Scheduler Trigger Defines how frequently new videos should be created (e.g., every 12 hours). Random Template Selector A JavaScript node generates a random number to choose from multiple creative prompt templates. AI Agent (Google Gemini) Gemini generates a JSON object containing: A short title A human-readable video description A detailed text-to-video prompt The Structured Output Parser ensures strict JSON shape. Video Generation with KIE AI The prompt is sent to KIE AI’s video generation API. KIE AI creates a synthetic AI video based on the description and your chosen parameters (aspect ratio, frames, watermark removal, etc.). Polling & Retrieval The workflow waits until the video is fully rendered, then fetches the final video URL. Media Upload to Blotato The generated video is uploaded into Blotato’s media storage for publishing. Automatic Posting to Social Platforms Blotato distributes the video to all connected platforms. Examples include: YouTube Instagram Facebook LinkedIn Bluesky TikTok X Any platform supported by your Blotato account This results in a fully automated “idea → video → upload → publish” pipeline. How to Use Start by testing the workflow manually to verify video generation and posting. Adjust the Scheduler Trigger to fit your posting frequency. Add your API credentials for: Google Gemini KIE AI Blotato Ensure your Blotato account has social channels connected. Edit or expand the prompt templates for your content niche: Comedy clips Educational videos Product demos Storytelling Pet videos Motivational content The more template prompts you add, the more diverse your automated videos will be. Requirements Google Gemini** API Key Used for generating structured titles, descriptions, and video prompts. KIE AI API key** Required for creating the actual AI-generated video. Blotato account** Required for uploading media and automatically posting to platforms. Self-hosted n8n instance** Needed because Blotato uses a community node, which n8n Cloud does not support. Limitations KIE AI models may output inconsistent results if prompts are vague. High-frequency scheduling may consume API credits quickly. Some platforms (e.g., TikTok or Facebook Pages) may require additional permissions or account linking steps in Blotato. Video rendering time varies depending on prompt complexity. Customization Ideas Add more prompt templates to increase variety. Swap Gemini for an LLM of your choice (OpenAI, Claude, etc.). Add a Telegram, Discord, or Slack notification once posting is complete. Store all generated titles, descriptions, and video URLs in: Google Sheets Notion Airtable Supabase Add multi-language support using a translation node. Add an approval step where videos go to your team before publishing. Add analytics logging (impressions, views, etc.) using Blotato or another service. Troubleshooting Video not generating?** Check if your KIE AI model accepts your chosen parameters. Model not found?** Switch to a supported Gemini model for your region. Publishing fails?** Ensure Blotato platform accounts are authenticated. Workflow stops early?** Increase the wait timeout before polling KIE AI. This template is designed for easy setup and high flexibility. All technical details, configuration steps, and workflow logic are already included in sticky notes inside the workflow. Once configured, this pipeline becomes a hands-free AI-powered content engine capable of generating and publishing content at scale.

This n8n template from Intuz provides a complete solution to automate your entire invoicing process. It intelligently syncs confirmed sales orders from your Airtable base to QuickBooks, automatically creating new customers if they don't exist before generating a perfectly matched invoice. It then logs all invoice details back into Airtable, creating a flawless, end-to-end financial workflow. Use Cases 1. Accounting & Finance Teams: Automatically generate QuickBooks invoices from new orders confirmed in Airtable. Keep all invoices and customer details synced across systems in real time. 2. Sales & Operations Teams: Track order status and billing progress directly from Airtable without switching platforms. Ensure every confirmed sale automatically triggers an invoice in QuickBooks. 3. Business Owners / Admins: Eliminate double-entry between Airtable and QuickBooks. Maintain accurate, audit-ready financial records with minimal effort. How it works 1. Trigger from Airtable: The workflow starts instantly when a sales order is ready to be invoiced in your Airtable base (triggered via a webhook). 2. Check for Customer in QuickBooks: It searches your QuickBooks account to see if the customer from the sales order already exists. 3. Create New Customer (If Needed): If the customer is not found, it automatically creates a new customer record in QuickBooks using the details from your Airtable Customers table. 4. Create QuickBooks Invoice: Using the correct customer record (either existing or newly created), it gathers all order line items from Airtable and generates a detailed invoice in QuickBooks. 5. Log Invoice Back to Airtable: After the invoice is successfully created, the workflow updates your Airtable base by adding a new record to your Invoices & Payments table and updating the original Confirmed Orders record with the new QuickBooks Invoice ID, marking it as synced. Key Requirements to Use This Template 1. n8n Instance: An active n8n account (Cloud or self-hosted). 2. Airtable Base: An Airtable base on a "Pro" plan or higher with tables for Confirmed Orders, Customers, Order Lines, Product & Service, and Invoices & Payments. Field names must match those in the setup guide. 3. QuickBooks Online Account: An active QuickBooks Online account with API access. Step-by-Step Setup Instructions Step 1: Import and Configure the n8n Workflow Import Workflow:** In n8n, import the Client-Quickbook-Invoices-via-AirTable.json file. Get Webhook URL:** Click on the first node, "Webhook". Copy the "Test URL". Keep this n8n tab open. Configure Airtable Nodes:** There are six Airtable nodes. For each one, connect your Airtable credentials and select the correct Base and Table. Configure QuickBooks Nodes:** There are four QuickBooks-related nodes. For each one, connect your QuickBooks Online credentials. CRITICAL:** Click on the "Create Invoice URL" (HTTP Request) node. You must edit the URL and replace the placeholder number (9341455145770046) with your own QuickBooks Company ID. (Find this in your QuickBooks account settings under "Billing & Subscription"). Save and Activate**: Click "Save", then toggle the workflow to "Active". After activating, copy the new "Production URL" from the Webhook node. Customization Guide You can adapt this template for various workflows by tweaking a few nodes: Use a different Airtable Base:** Update the Base ID and Table ID in all Airtable nodes (Get Orders Records, Get Customer Details, Get Products, etc.). Switch from Sandbox to Live QuickBooks:** Replace the Sandbox company ID and endpoint in the “Create Invoice URL” node with your production QuickBooks company ID. Add more invoice details:** Edit the Code and Parse in HTTP nodes to include additional fields (like Tax, Shipping, or Notes). Support multiple currencies:** Add a “Currency” field mapping in both Airtable and QuickBooks nodes. Connect with us Website: https://www.intuz.com/services 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

This n8n workflow automatically scrapes TechCrunch articles, filters for AI-related content using OpenAI, and delivers curated summaries to your Slack channels. Perfect for individuals or teams who need to stay current on artificial intelligence developments without manually browsing tech news sites. Who's it for AI product teams tracking industry developments and competitive moves Tech investors monitoring AI startup coverage and funding announcements Marketing teams following AI trends for content and positioning strategies Executives needing daily AI industry briefings without manual research overhead Development teams staying current on AI tools, frameworks, and breakthrough technologies How it works The workflow runs on a daily schedule, crawling a specificed amount of TechCrunch articles from the current year. Firecrawl extracts clean markdown content while bypassing anti-bot measures and handling JavaScript rendering automatically. Each article gets analyzed by an AI research assistant that determines if the content relates to artificial intelligence, machine learning, AI companies, or AI technology. Articles marked as "NOT_AI_RELATED" get filtered out automatically. For AI-relevant articles, OpenAI generates focused 3-bullet-point summaries that capture key insights. These summaries get delivered to your specified Slack channel with the original TechCrunch article title and source link for deeper reading. How to set up Configure Firecrawl: Add your Firecrawl API key to the HTTP Request node Set OpenAI credentials: Add your OpenAI API key to the AI Agent node Connect Slack: Configure your Slack webhook URL and target channel Adjust scheduling: Set your preferred trigger frequency (daily recommended) Test the workflow: Run manually to verify article extraction and Slack delivery Requirements Firecrawl account** with API access for TechCrunch web scraping OpenAI API key** for AI content analysis and summarization Slack workspace** with webhook permissions for message delivery n8n instance** (cloud or self-hosted) for workflow execution How to customize the workflow Source expansion: Modify the HTTP node URL to target additional tech publications beyond TechCrunch, or adjust the article limit and date filtering for different coverage needs. AI focus refinement: Update the OpenAI prompt to focus on specific AI verticals like generative AI, robotics, or ML infrastructure. Add company names or technology terms to the relevance filtering logic. Summary formats: Change from 3-bullet summaries to executive briefs, technical analyses, or competitive intelligence reports by modifying the OpenAI summarization prompt. Multi-channel delivery: Extend beyond Slack to email notifications, Microsoft Teams, or database storage for historical trend analysis and executive dashboards.

🛍️ Pick Best-Value Products from Any Website Using Dumpling AI, GPT-4o, and Google Sheets Who’s it for This workflow is for eCommerce researchers, affiliate marketers, and anyone who needs to compare product listings across sites like Amazon. It’s perfect for quickly identifying top product picks based on delivery speed, free shipping, and price. What it does Just submit a product listing URL. The workflow will crawl it using Dumpling AI, take screenshots of the pages, and pass them to GPT-4o to extract up to 3 best-value picks. It analyzes screenshots visually—no HTML scraping needed. Each result includes: product name price review count free delivery date (if available) How it works 📝 Receives a URL through a web form 🧠 Uses Dumpling AI to crawl the website 📸 Takes screenshots of each product listing 🔍 GPT-4o analyzes each image to pick top products 🔧 A code node parses and flattens the output 📊 Google Sheets stores the result 📧 Sends the spreadsheet link via email Requirements Dumpling AI token** OpenAI key** (GPT-4o) Google Sheet** with columns: product name, price, reviews no., free_delivery_date > You can customize the AI prompt to extract other visual insights (e.g., ratings, specs).

Jira MCP Server Integration with n8n Overview Transform your Jira project management with the power of AI and automation! This n8n workflow template demonstrates how to create a seamless integration between chat interfaces, AI processing, and Jira Software using MCP (Model Context Protocol) server architecture. What This Workflow Does Chat-Driven Automation**: Trigger Jira operations through simple chat messages AI-Powered Issue Creation**: Automatically generate detailed Jira issues with descriptions and acceptance criteria Complete Jira Management**: Get issue status, changelogs, comments, and perform full CRUD operations Memory Integration**: Maintain context across conversations for smarter automations Zero Manual Entry**: Eliminate repetitive data entry and human errors Key Features ✅ Natural Language Processing: Use Google Gemini to understand and process chat requests ✅ MCP Server Integration: Secure, efficient communication with Jira APIs ✅ Comprehensive Jira Operations: Create, read, update, delete issues and comments ✅ Smart Memory: Context-aware conversations for better automation ✅ Multi-Action Workflow: Handle multiple Jira operations from a single trigger Demo Video 🎥 Watch the Complete Demo: Automate Jira Issue Creation with n8n & AI | MCP Server Integration Prerequisites Before setting up this workflow, ensure you have: n8n instance** (cloud or self-hosted) Jira Software** account with appropriate permissions Google Gemini API** credentials MCP Server** configured and accessible Basic understanding of n8n workflows Setup Guide Step 1: Import the Workflow Copy the workflow JSON from this template In your n8n instance, click Import > From Text Paste the JSON and click Import Step 2: Configure Google Gemini Open the Google Gemini Chat Model node Add your Google Gemini API credentials Configure the model parameters: Model: gemini-pro (recommended) Temperature: 0.7 for balanced creativity Max tokens: As per your requirements Step 3: Set Up MCP Server Connection Configure the MCP Client node: Server URL: Your MCP server endpoint Authentication: Add required credentials Timeout: Set appropriate timeout values Ensure your MCP server supports Jira operations: Issue creation and retrieval Comment management Status updates Changelog access Step 4: Configure Jira Integration Set up Jira credentials in n8n: Go to Credentials > Add Credential Select Jira Software API Add your Jira instance URL, email, and API token Configure each Jira node: Get Issue Status: Set project key and filters Create Issue: Define issue type and required fields Manage Comments: Set permissions and content rules Step 5: Memory Configuration Configure the Simple Memory node: Set memory key for conversation context Define memory retention duration Configure memory scope (user/session level) Step 6: Chat Trigger Setup Configure the When Chat Message Received trigger: Set up webhook URL or chat platform integration Define message filters if needed Test the trigger with sample messages Usage Examples Creating a Jira Issue Chat Input: Can you create an issue in Jira for Login Page with detailed description and acceptance criteria? Expected Output: New Jira issue created with structured description Automatically generated acceptance criteria Proper labeling and categorization Getting Issue Status Chat Input: What's the status of issue PROJ-123? Expected Output: Current issue status Last updated information Assigned user details Managing Comments Chat Input: Add a comment to issue PROJ-123: "Ready for testing in staging environment" Expected Output: Comment added to specified issue Notification sent to relevant team members Customization Options Extending Jira Operations Add more Jira operations (transitions, watchers, attachments) Implement custom field handling Create multi-project workflows AI Enhancement Fine-tune Gemini prompts for better issue descriptions Add custom validation rules Implement approval workflows Integration Expansion Connect to Slack, Discord, or Teams Add email notifications Integrate with time tracking tools Troubleshooting Common Issues MCP Server Connection Failed Verify server URL and credentials Check network connectivity Ensure MCP server is running and accessible Jira API Errors Validate Jira credentials and permissions Check project access rights Verify issue type and field configurations AI Response Issues Review Gemini API quotas and limits Adjust prompt engineering for better results Check model parameters and settings Performance Tips Optimize memory usage for long conversations Implement rate limiting for API calls Use error handling and retry mechanisms Monitor workflow execution times Best Practices Security: Store all credentials securely using n8n's credential system Testing: Test each node individually before running the complete workflow Monitoring: Set up alerts for workflow failures and API limits Documentation: Keep track of custom configurations and modifications Backup: Regular backup of workflow configurations and credentials Happy Automating! 🚀 This workflow template is designed to boost productivity and eliminate manual Jira management tasks. Customize it according to your team's specific needs and processes.

This n8n workflow template automatically processes phone interview transcripts using AI to evaluate candidates against specific criteria and saves the results to Google Sheets. Perfect for HR departments, recruitment agencies, or any business conducting phone screenings. What This Workflow Does This automated workflow: Receives phone interview transcripts via webhook Uses OpenAI GPT models to analyze candidate responses against predefined qualification criteria Extracts key information (name, phone, location, qualification status) Automatically saves structured results to a Google Sheet for easy review and follow-up The workflow is specifically designed for driving job interviews but can be easily adapted for any position with custom evaluation criteria. Tools & Services Used N8N** - Workflow automation platform OpenAI API** - AI-powered transcript analysis (GPT-4o-mini) Google Sheets** - Data storage and management Webhook** - Receiving transcript data Prerequisites Before implementing this workflow, you'll need: N8N Instance - Self-hosted or cloud version OpenAI API Account - For AI transcript processing Google Account - For Google Sheets integration Phone Interview System - That can send webhooks (like Vapi.ai) Step-by-Step Setup Instructions Step 1: Set Up OpenAI API Access Visit OpenAI's API platform Create an account or log in Navigate to API Keys section Generate a new API key Copy and securely store your API key Step 2: Create Your Google Sheet Option 1: Use Our Pre-Made Template (Recommended) Copy our template: Driver Interview Results Template Click "File" → "Make a copy" to create your own version Rename it as desired Copy your new sheet's URL - you'll need this for the workflow Option 2: Create From Scratch Go to Google Sheets Create a new spreadsheet Name it "Driver Interview Results" (or your preferred name) Set up the following column headers in row 1: A1: name B1: phone C1: cityState D1: qualifies E1: reasoning Copy the Google Sheet URL - you'll need this for the workflow Step 3: Import and Configure the N8N Workflow Import the Workflow Copy the workflow JSON from the template In your N8N instance, go to Workflows → Import from JSON Paste the JSON and import Configure OpenAI Credentials Click on either "OpenAI Chat Model" node Set up credentials using your OpenAI API key Test the connection to ensure it works Configure Google Sheets Integration Click on the "Save to Google Sheets" node Set up Google Sheets OAuth2 credentials Select your spreadsheet from the dropdown Choose the correct sheet (usually "Sheet1") Update the Webhook Click on the "Webhook" node Note the webhook URL that n8n generates This URL will receive your transcript data Step 4: Customize Evaluation Criteria The workflow includes predefined criteria for a Massachusetts driving job. To customize for your needs: Click on the "Evaluate Candidate" node Modify the system message to include your specific requirements Update the evaluation criteria checklist Adjust the JSON output format if needed Current Evaluation Criteria: Valid Massachusetts driver's license No felony convictions Clean driving record (no recent tickets/accidents) Willing to complete background check Can pass drug test (including marijuana) Available full-time Monday-Friday Lives in Massachusetts Step 5: Connect to Vapi.ai (Phone Interview System) This workflow is specifically designed to work with Vapi.ai's phone interview system. Here's how to connect it: Setting Up the Vapi Integration Copy Your N8N Webhook URL In your n8n workflow, click on the "Webhook" node Copy the webhook URL (it should look like: https://your-n8n-instance.com/webhook-test/351ffe7c-69f2-4657-b593-c848d59205c0) Configure Your Vapi Assistant Log into your Vapi.ai dashboard Create or edit your phone interview assistant In the assistant settings, find the "Server" section Set the Server URL to your n8n webhook URL Set timeout to 20 seconds (as configured in the workflow) Configure Server Messages In your Vapi assistant settings, enable these server messages: end-of-call-report transcript[transcriptType="final"] Set Up the Interview Script Use the provided interview script in your Vapi assistant (found in the workflow's system message) This ensures consistent data collection for the AI evaluation Expected Data Format from Vapi The workflow expects Vapi to send data in this specific format: { "body": { "message": { "artifact": { "transcript": "AI: Hi. Are you interested in driving for Bank of Transport?\nUser: Yes.\nAI: Great. Before we go further..." } } } } Vapi Configuration Checklist ✅ Webhook URL set in Vapi assistant server settings ✅ Server messages enabled: end-of-call-report, transcript[transcriptType="final"] ✅ Interview script configured in assistant ✅ Assistant set to send webhooks on call completion Alternative Phone Systems If you're not using Vapi.ai, you can adapt this workflow for other phone systems by: Modifying the "Edit Fields2" node to extract transcripts from your system's data format Updating the webhook data structure expectations Ensuring your phone system sends the complete interview transcript Step 6: Test the Workflow Test with Sample Data Use the "Execute Workflow" button with test data Verify that data appears correctly in your Google Sheet Check that the AI evaluation logic works as expected End-to-End Testing Send a test webhook with a real transcript Monitor each step of the workflow Confirm the final result is saved to Google Sheets Workflow Node Breakdown Webhook - Receives transcript data from your phone system Edit Fields2 - Extracts the transcript from the incoming data Evaluate Candidate - AI analysis using GPT-4o-mini to assess qualification Convert to JSON - Ensures proper JSON formatting with structured output parser Save to Google Sheets - Automatically logs results to your spreadsheet Customization Options Modify Evaluation Criteria Edit the system prompt in the "Evaluate Candidate" node Add or remove qualification requirements Adjust the scoring logic Change Output Format Modify the JSON schema in the "Structured Output Parser" node Update Google Sheets column mapping accordingly Add Additional Processing Insert nodes for email notifications Add Slack/Discord alerts for qualified candidates Integrate with your CRM or ATS system Troubleshooting Common Issues: OpenAI API Errors**: Check API key validity and billing status Google Sheets Not Updating**: Verify OAuth permissions and sheet access Webhook Not Receiving Data**: Confirm URL and POST format from your phone system AI Evaluation Inconsistencies**: Refine the system prompt with more specific criteria Usage Tips Monitor Token Usage**: OpenAI charges per token, so monitor your usage Regular Review**: Periodically review AI evaluations for accuracy Backup Data**: Export Google Sheets data regularly for backup Privacy Compliance**: Ensure transcript handling complies with local privacy laws Need Help with Implementation? For professional setup, customization, or troubleshooting of this workflow, contact: Robert - Ynteractive Solutions Email**: rbreen@ynteractive.com Website**: www.ynteractive.com LinkedIn**: linkedin.com/in/robert-interactive Specializing in AI-powered workflow automation, business process optimization, and custom integration solutions.

Automated AWS IAM Compliance Workflow for MFA Enforcement and Access Key Deactivation > This workflow leverages AWS IAM APIs and n8n automation to ensure strict security compliance by continuously monitoring IAM users for MFA (Multi-Factor Authentication) enforcement. .jpg) Who’s it for This workflow is designed for DevOps, Security, or Cloud Engineers responsible for maintaining IAM security compliance in AWS accounts. It's ideal for teams who want to enforce MFA usage and automatically disable access for non-compliant IAM users. How it works / What it does This automated workflow performs a daily check to detect IAM users without an MFA device and deactivate their access keys. Step-by-step: Daily scheduler: Triggers the workflow once a day. Get many users: Retrieves a list of all IAM users in the account. Get IAM User MFA Devices: Calls AWS API to get MFA device info for each user. Filter out IAM users with MFA: Keeps only users without any MFA device. Send warning message(s): Sends Slack alerts for users who do not have MFA enabled. Get User Access Key(s): Fetches access keys for each non-MFA user. Parse the list of user access key(s): Extracts and flattens key information like AccessKeyId, Status, and UserName. Filter out inactive keys: Keeps only active access keys for further action. Deactivate Access Key(s): Calls AWS API to deactivate each active key for non-MFA users. How to set up Configure AWS credentials in your environment (IAM role or AWS access key with required permissions). Connect Slack via the Slack node for alerting (set channel and credentials). Set the scheduler to your preferred frequency (e.g., daily at 9AM). Adjust any Slack message template or filtering conditions as needed. Requirements IAM user or role credentials with the following AWS IAM permissions: iam:ListUsers iam:ListMFADevices iam:ListAccessKeys iam:UpdateAccessKey Slack credentials (Bot token with chat:write permission). n8n environment with: Slack integration AWS credentials (set via environment or credentials manager) How to customize the workflow Alert threshold**: Instead of immediate deactivation, you can delay action (e.g., alert first, wait 24h, then disable). Change notification channel**: Modify the Slack node to send alerts to a different channel or add email integration. Whitelist exceptions**: Add a Set or IF node to exclude specific usernames (e.g., service accounts). Add audit logging**: Use Google Sheets, Airtable, or a database to log which users were flagged or had access disabled. Extend access checks**: Include console password check (GetLoginProfile) if needed.

🚀 Enrich CRM Leads with LinkedIn Company Data Using AI Who's it for Sales teams, marketers, and business development professionals who need to automatically enrich their CRM records with detailed company information from LinkedIn profiles. Perfect for anyone doing B2B outreach who wants to personalize their messaging at scale. What it does This workflow transforms bare-bones lead records into rich, personalized prospect profiles by: Automatically scraping LinkedIn company profiles Using AI (GPT-4) to extract key business intelligence Generating 15+ email-ready personalization variables Updating your CRM with structured, actionable data The workflow pulls company overviews, products/services, funding information, recent posts, and converts everything into natural-language variables that can be dropped directly into your outreach templates. How it works Trigger: Workflow starts when a new lead is added to Airtable (or on schedule) Fetch: Retrieves the lead record containing the LinkedIn company URL Scrape: Pulls the raw HTML from the company's LinkedIn profile Clean: Strips HTML tags and formats content for AI processing Analyze: GPT-4 extracts structured company intelligence (overview, products, market presence, recent posts) Transform: Converts analysis into 15+ email-ready variables with natural phrasing Update: Writes enriched data back to your CRM Setup Requirements Airtable account** (free tier works fine) OpenAI API key** (GPT-4o-mini recommended for cost-effectiveness) LinkedIn company URLs** stored in your CRM 5 minutes** for initial configuration How to set up Configure Airtable Connection Replace YOUR_AIRTABLE_BASE_ID with your base ID Replace YOUR_TABLE_ID with your leads table ID Ensure your table has a "LinkedIn Organization URL" field Add your Airtable API credentials Add OpenAI Credentials Click on both OpenAI nodes Add your OpenAI API key GPT-4o-mini is recommended (cost-effective and fast) Set Up Trigger Add a trigger node (Schedule, Webhook, or Airtable trigger) Configure to run when new leads are added or on a daily schedule Test the Workflow Add a test lead with a LinkedIn company URL Execute

How it works This Lead Capture & Auto-Qualification workflow transforms raw leads into qualified prospects through intelligent automation. Here's the high-level flow: Lead Intake → Data Validation → Enrichment → Scoring → Smart Routing → CRM Integration & Notifications The system captures leads from any source, validates the data, enriches it with company intelligence, scores based on qualification criteria, and automatically routes high-value prospects to sales while nurturing lower-priority leads. Set up steps Time to set up: Approximately 30-45 minutes Prerequisites: Active accounts with HubSpot, Clearbit, Apollo, and Slack Step 1: Import Workflow (2 minutes) Copy the workflow JSON and import into your n8n instance The workflow will appear with all nodes and sticky note documentation Step 2: Configure Environment Variables (5 minutes) Set these in your n8n environment: APOLLO_API_URL SLACK_SALES_CHANNEL_ID SLACK_MARKETING_CHANNEL_ID CRM_ASSIGNMENT_URL Step 3: Set Up API Credentials (15 minutes) Create credential connections for: Clearbit API (enrichment) Apollo API (HTTP Header Auth) HubSpot API (CRM integration) Slack API (notifications) Step 4: Customize Scoring Logic (10 minutes) Review the qualification criteria in the Code node Adjust scoring weights based on your ideal customer profile Modify industry targeting and company size thresholds Step 5: Test & Activate (8 minutes) Send test webhook requests to validate the flow Verify CRM contact creation and Slack notifications Activate the workflow for live lead processing