Workflow Templates

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.

Who’s it for Content/SEO teams who want a fast, consistent, research-driven brief for a copywriters from a single keyword—without manual review and analysis of the SERP (Google results). How it works / What it does Form Trigger collects the keyword/topic and redirects to Google Drive Folder after the final node. FireCrawl Search & Scrape pulls the top 5 pages for the chosen keyword. AI Agent (with Think + OpenAI Chat Model) analyzes sources and generates an original Markdown brief. Markdown to JSON converts the Markdown into Google Docs batchUpdate requests (H1/H2/H3, lists, links, spacing). Then this is used in Update a document for updating the empty doc. Create a document + Update a document write a Google Doc titled “SEO Brief for ” and update the Google Doc in your target Drive folder. How to set up Add credentials: Firecrawl (Authorization header), OpenAI (Chat), Google Docs OAuth2. Replace placeholders: {{APIKEY}}, {{googledrivefolderid}}, {{googledrivefolderurl}}. Publish and open the Form URL to test. Requirements Firecrawl API key • OpenAI API key • Google account with access to the target Drive folder. Resources Google OAuth2 Credentials Setup - https://docs.n8n.io/integrations/builtin/credentials/google/oauth-generic/ Firecrawl API key - https://take.ms/lGcUp OpenAI API key - https://docs.n8n.io/integrations/builtin/credentials/openai/

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. WordPress to Blotato Social Publisher Overview: This automation monitors your WordPress site for new posts and automatically creates platform-specific social media content using AI, then posts to Twitter, LinkedIn, and Facebook via Blotato. What it does: Monitors WordPress site for new posts every 30 minutes Filters posts published in the last hour to avoid duplicates Processes each new post individually AI generates optimized content for each social platform (Twitter, LinkedIn, Facebook) Extracts platform-specific content from AI response Publishes to all three social media platforms via Blotato API Setup Required: WordPress Connection Configure WordPress credentials in the "Check New Posts" node Enter your WordPress site URL, username, and password/app password Blotato Social Media API Setup Get your Blotato API key from your Blotato account Configure API credentials in the Blotato connection node Map each platform (Twitter, LinkedIn, Facebook) to the correct Blotato channel AI Configuration Set up Google Gemini API credentials Connect the Gemini model to the "AI Social Content Creator" node Customization Options Posting Frequency: Modify schedule trigger (default: every 30 minutes) Content Tone: Adjust AI system message for different writing styles Post Filtering: Change time window in WordPress node (default: last hour) Platform Selection: Remove any social media platforms you don’t want to use Testing Run workflow manually to test connections Verify posts appear correctly on all platforms Monitor for API rate limit issues Features: Platform-optimized content (hashtags, character limits, professional tone) Duplicate prevention system Batch processing for multiple posts Featured image support Customizable posting frequency Customization: Change monitoring frequency Adjust AI prompts for different tones Add/remove social platforms Modify hashtag strategies Need Help? For n8n coaching or one-on-one consultation

🚀 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

Automating AWS S3 Operations with n8n: Buckets, Folders, and Files Watch the demo video below: This tutorial walks you through setting up an automated workflow that generates AI-powered images from prompts and securely stores them in AWS S3. It leverages the new AI Tool Node and OpenAI models for prompt-to-image generation. Who’s it for This workflow is ideal for: Designers & marketers** who need quick, on-demand AI-generated visuals. Developers & automation builders* exploring *AI-driven workflows** integrated with cloud storage. Educators or trainers** creating tutorials or exercises on AI image generation. Businesses* looking to automate *image content pipelines** with AWS S3 storage. How it works / What it does Trigger: The workflow starts manually when you click “Execute Workflow”. Edit Fields: You can provide input fields such as image description, resolution, or naming convention. Create AWS S3 Bucket: Automatically creates a new S3 bucket if it doesn’t exist. Create a Folder: Inside the bucket, a folder is created to organize generated images. Prompt Generation Agent: An AI agent generates or refines the image prompt using the OpenAI Chat Model. Generate an Image: The refined prompt is used to generate an image using AI. Upload File to S3: The generated image is uploaded to the AWS S3 bucket for secure storage. This workflow showcases how to combine AI + Cloud Storage seamlessly in an automated pipeline. How to set up Import the workflow into n8n. Configure the following credentials: AWS S3 (Access Key, Secret Key, Region). OpenAI API Key (for Chat + Image models). Update the Edit Fields node with your preferred input fields (e.g., image size, description). Execute the workflow and test by entering a sample image prompt (e.g., “Futuristic city skyline in watercolor style”). Check your AWS S3 bucket to verify the uploaded image. Requirements n8n** (latest version with AI Tool Node support). AWS account** with S3 permissions to create buckets and upload files. OpenAI API key** (for prompt refinement and image generation). Basic familiarity with AWS S3 structure (buckets, folders, objects). How to customize the workflow Custom Buckets**: Replace the auto-create step with an existing S3 bucket. Image Variations**: Generate multiple image variations per prompt by looping the image generation step. File Naming**: Adjust file naming conventions (e.g., timestamp, user input). Metadata**: Add metadata such as tags, categories, or owner info when uploading to S3. Alternative Storage: Swap AWS S3 with **Google Cloud Storage, Azure Blob, or Dropbox. Trigger Options: Replace manual trigger with **Webhook, Form Submission, or Scheduler for automation. ✅ This workflow is a hands-on example of how to combine AI prompt engineering, image generation, and cloud storage automation into a single streamlined process.

Revolutionize your recruitment process with intelligent AI-driven candidate screening that evaluates resumes, scores applicants, and automatically routes them based on fit - saving 10-15 hours per week on initial screening. 🎯 What This Workflow Does Transforms your hiring pipeline from manual resume review to intelligent automation: 📝 Captures Applications - Jotform intake with resume upload 🤖 AI Resume Analysis - OpenAI parses skills, experience, education, and red flags 🎯 Intelligent Scoring - Evaluates candidates against job requirements with structured scoring (0-100) 🚦 Smart Routing - Automatically routes based on AI recommendation: Strong Yes (85-100): Instant Slack alert → Interview invitation Maybe/Yes (60-84): Manager review → Approval workflow No (<60): Polite rejection email 📊 Analytics Tracking - All data logged to Google Sheets for hiring insights ✨ Key Features AI Resume Parsing**: Extracts structured data from any resume format Intelligent Scoring System**: Multi-dimensional evaluation (skills match, experience quality, cultural fit) Structured Output**: Consistent JSON schema ensures reliable data for decision-making Automated Communication**: Personalized emails for every candidate outcome Human-in-the-Loop**: Manager approval for borderline candidates Comprehensive Analytics**: Track conversion rates, average scores, and hiring metrics Customizable Job Requirements**: Easy prompt editing to match any role 💼 Perfect For Startups & Scale-ups**: Processing 50+ applications per week HR Teams**: Wanting to reduce time-to-hire by 40-60% Technical Recruiters**: Screening engineering, product, or design roles Growing Companies**: Scaling hiring without scaling headcount 🔧 What You'll Need Required Integrations Jotform** - Application intake form (free tier works) Create your form for free on Jotform using this link OpenAI API** - GPT-4o-mini for cost-effective AI analysis (~$0.15 per candidate) Gmail** - Automated candidate communication Google Sheets** - Hiring database and analytics Optional Integrations Slack** - Instant alerts for hot candidates Linear/Asana** - Task creation for interview scheduling Calendar APIs** - Automated interview booking 🚀 Quick Start Import Template - Copy JSON and import into n8n Create Jotform - Use provided field structure (name, email, resume upload, etc.) Add API Keys - OpenAI, Jotform, Gmail, Google Sheets Customize Job Requirements - Edit AI screening prompt with your role details Personalize Emails - Update templates with your company branding Test & Deploy - Submit test application and verify all nodes 🎨 Customization Options Adjust Scoring Thresholds**: Change routing logic based on your needs Multiple Positions**: Clone workflow for different roles with unique requirements Add Technical Assessments**: Integrate HackerRank, CodeSignal, or custom tests Interview Scheduling**: Connect Calendly or Google Calendar for auto-booking ATS Integration**: Push data to Lever, Greenhouse, or BambooHR Diversity Tracking**: Add demographic fields and analytics Reference Checking**: Automate reference request emails 📈 Expected Results 90% reduction** in manual resume review time 24-hour response time** to all candidates Zero missed applications** - every candidate gets feedback Data-driven hiring** - track what works with comprehensive analytics Better candidate experience** - fast, professional communication Consistent evaluation** - eliminate unconscious bias with structured AI scoring 🏆 Use Cases Technology Companies Screen 100+ engineering applications per week, identify top 10% instantly, schedule interviews same-day. Agencies & Consultancies Evaluate consultant candidates across multiple skill dimensions, route to appropriate practice areas. High-Volume Hiring Process retail, customer service, or sales applications at scale with consistent quality. Remote-First Teams Evaluate global candidates 24/7, respond instantly regardless of timezone. 💡 Pro Tips Train Your AI**: After 50+ applications, refine prompts based on false positives/negatives A/B Test Thresholds**: Experiment with score cutoffs to optimize for your needs Build Talent Pipeline**: Keep "maybe" candidates in CRM for future roles Track Source Effectiveness**: Add UTM parameters to measure which job boards deliver best candidates Continuous Improvement**: Weekly review of AI assessments to calibrate accuracy 🎓 Learning Resources This workflow demonstrates: AI Agents with structured output Multi-stage conditional routing Human-in-the-loop automation Binary data processing (resume files) Email automation with HTML templates Real-time notifications Analytics and data logging Perfect for learning advanced n8n automation patterns! Ready to transform your hiring process? Import this template and start screening candidates intelligently in under 30 minutes. Questions or customization needs? The workflow includes detailed sticky notes explaining each section.

Workflow Purpose The workflow is designed to scan submitted URLs using urlscan.io and VirusTotal, combine the results into a single structured summary, and send the report via Telegram. I built this workflow for people who primarily work from their phones and receive a constant stream of emails throughout the day. If a user gets an email asking them to sign a document, review a report, or take any action where the link looks suspicious, they can simply open the Telegram bot and quickly check whether the URL is safe before clicking it. Key Components 1. Input / Trigger Accepts URLs that need to be checked. Initiates requests to VirusTotal and urlscan.io. 2. VirusTotal Scan Always returns results if the URL is reachable. Provides reputation, malicious/clean flags, and scan metadata. 3. urlscan.io Scan Returns details on how the URL behaves when loaded (domains, requests, resources, etc.). Sometimes fails due to blocks or restrictions. 4. Error Handling with Code Node Checks whether urlscan.io responded successfully. Ensures the workflow always produces a summary, even if urlscan.io fails. 5. Summary Generation If both scans succeed → summarize combined findings from VirusTotal + urlscan.io. If urlscan.io fails → state clearly in the summary “urlscan.io scan was blocked/failed. Relying on VirusTotal results.” Ensures user still gets a complete security report. 6. Telegram Output Final formatted summary is delivered to a Telegram chat via the bot. Chat ID issue was fixed after the Code Node restructuring. Outcome The workflow now guarantees a consistent, user-friendly summary regardless of urlscan.io failures. It leverages VirusTotal as the fallback source of truth. The Telegram bot provides real-time alerts with clear indications of scan success/failure. Prequisites Telegram In Telegram, start a chat with @BotFather. Send /newbot, pick a name and a unique username. Copy the HTTP API token BotFather returns (store securely) Start a DM with your bot and send any message. Call getUpdates and read the chat.id urlscan.io Create/log into your urlscan.io account. Go to Settings & API → New API key and generate a key. (Recommended) In Settings & API, set Default Scan Visibility to Unlisted to avoid exposing PII in public scans. Save the key securely (env var or n8n Credentials). Rate limits note: urlscan.io enforces per-minute/hour/day quotas; exceeding them returns HTTP 429. You can view your personal quotas on their dashboard/quotas endpoint Virustotal Sign up / sign in to VirusTotal Community. Open My API key (Profile menu) and copy your Public API key. Store it securely (env var or n8n Credentials). For a more reliable connection with VirusTotal and improved scanning results, enable the Header section in the node settings. Add a header parameter with a clear name (e.g., x-apikey), and then paste your API key into the Value field. Rate limits (Public API): 4 requests/minute, 500/day; not for commercial workflows. Consider Premium if you’ll exceed this. How to Customize the Workflow This workflow is designed to be highly customizable, allowing users to adapt it to their specific needs and use cases. For example, additional malicious website scanners can be integrated through HTTP Request nodes. To make this work, the user simply needs to update the Merge node so that all information flows correctly through the workflow. In addition, users can connect either Gmail or Outlook nodes to automatically test URLs, binary attachments, and other types of information received via email—helping them evaluate data before opening it. Users can also customize how they receive reports. For instance, results can be sent through Telegram (as in the default setup), Slack, Microsoft Teams, or even saved to Google Drive or a Google Sheet for recordkeeping and audit purposes. For consulting and support, or if you have questions, please feel free to connect with me on Linkedin or via email.

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 template from Intuz provides a complete and automated solution for creating and distributing sophisticated release notes. It connects to GitHub and JIRA to gather data from recent commits and completed tickets, using specific keywords or labels to identify key features for inclusion. This information is then processed by Google Gemini to automatically generate well-written, human-like release notes, which are then distributed via email to stakeholders, creating a complete, end-to-end communication pipeline for every new software release. This template is perfect for development teams looking to streamline their release process, ensure consistent communication, and eliminate the manual effort of writing release notes. How to use 1. Set up Credentials: GitHub JIRA (Software Cloud API) Google Gemini (or another PaLM/LLM provider) Your SMTP email server. 2. Configure the GitHub Trigger: Select the Github Trigger node. In the Repository Owner field, enter your GitHub username or organization name. In the Repository Name field, select the repository you want to monitor. 3. Verify the JIRA Integration: Important:** This workflow assumes your commit messages contain a JIRA key (e.g., "PROJ-123: Fix login bug"). Select the first Code node. It uses a regular expression ([A-Z]+-\\d+)/i to find JIRA keys. Adjust this expression if your team uses a different format. Select the Get an issue node and ensure your JIRA credentials are correctly configured. 4. Customize the AI Prompt: Select the Basic LLM Chain node. You can edit the prompt to change the tone, style, or structure of the generated HTML release note to match your company's standards. 5. Configure Email Notifications: Select the Send email node. Update the To Email field with the recipient's email address (e.g., a team distribution list or a stakeholder's email). Customize the From Email and Subject line as needed. 6. Activate Workflow: Save your changes and activate the workflow. Now, every push to your configured repository will trigger the automated generation and sending of release notes. Required Tools GitHub: To trigger the workflow on code pushes. JIRA: To fetch details about the tasks and bugs included in the release. Google Gemini: To intelligently generate the release note content. (You can swap this for another LLM supported by n8n). SMTP Provider: To send the final release note via email. 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 Worflow Automation Click here- Get Started

Icebreaker Generator powered with ChatGPT This n8n template crawls a company website, distills the content with AI, and produces a short, personalized icebreaker you can drop straight into your cold emails or CRM. Perfect for SDRs, founders, and agencies who want “real research” at scale. Good to know Works from a Google Sheet of leads (domain + LinkedIn, etc.). Handles common scrape failures gracefully and marks the lead’s Status as Error. Uses ChatGPT to summarize pages and craft one concise, non-generic opener. Output is written back to the same Google Sheet (IceBreaker, Status). You’ll need Google credentials (for Sheets) and OpenAI credentials (for GPT). How it works Step 1 — Discover internal pages Reads a lead’s website from Google Sheets. Scrapes the home page and extracts all links. A Code node cleans the list (removes emails/anchors/social/external domains, normalizes paths, de-duplicates) and returns unique internal URLs. If the home page is unreachable or no links are found, the lead is marked Error and the workflow moves on. Step 2 — Convert pages to text Visits each collected URL and converts the response into HTML/Markdown text for analysis. You can cap depth/amount with the Limit node. Step 3 — Summarize & generate the icebreaker A GPT node produces a two-paragraph abstract for each page (JSON output). An Aggregate node merges all abstracts for the company. Another GPT node turns the merged summary into a personalized, multi-line icebreaker (spartan tone, non-obvious details). The result is written back to Google Sheets (IceBreaker = ..., Status = Done). The workflow loops to the next lead. How to use Prepare your sheet Include at least: organization_website_url, linkedin_url, and any other lead fields you track. Keep an empty IceBreaker and Status column for the workflow to fill. Connect credentials Google Sheets: use the Google account that owns the sheet and link it in the nodes. OpenAI: add your API key to the GPT nodes (“Summarize Website Page”, “Generate Multiline Icebreaker”). Run the workflow Start with the Manual Trigger (or replace with a schedule/webhook). Adjust Limit if you want fewer/more pages per company. Watch Status (Done/Error) and IceBreaker populate in your sheet. Requirements n8n instance Google Sheets account & access to the leads sheet OpenAI API key (for summarization + icebreaker generation) Customizing this workflow Tone & format: tweak the prompts (both GPT nodes) to match your brand voice and structure. Depth: change the Limit node to scan more/less pages; add simple rules to prioritize certain paths (e.g., /about, /blog/*). Fields: write additional outputs (e.g., Company Summary, Key Products, Recent News) back to new sheet columns. Lead selection: filter rows by Status = "" (or custom flags) to only process untouched leads. Error handling: expand the Error branch to retry with www./HTTP→HTTPS or to log diagnostics in a separate tab. Tips Keep icebreakers short, specific, and free of clichés—small, non-obvious details from the site convert best. Start with a small batch to validate quality, then scale up. Consider adding a rate limit if target sites throttle requests. In short: Sheet → crawl internal pages → AI abstracts → single tailored icebreaker → write back to the sheet, then repeat for the next lead. This automation can work great with our automation for automated cold emailing.

Overview Transform your accounts payable department with this enterprise-grade invoice processing solution. This workflow automates the entire invoice lifecycle - from document ingestion through payment processing. It handles invoices from multiple sources (Google Drive, email attachments, API submissions), extracts data using AI, validates against purchase orders, routes for appropriate approvals based on amount thresholds, and integrates seamlessly with your ERP system. The solution includes vendor master data management, duplicate invoice detection, real-time spend analytics, and complete audit trails for compliance. What You Can Do This comprehensive workflow creates an intelligent invoice processing pipeline that monitors multiple input channels (Google Drive, email, webhooks) for new invoices and automatically extracts data from PDFs, images, and scanned documents using AI. It validates vendor information against your master database, matches invoices to purchase orders, and detects discrepancies. The workflow implements multi-level approval routing based on invoice amount and department, prevents duplicate payments through intelligent matching algorithms, and integrates with QuickBooks, SAP, or other ERP systems. Additionally, it generates real-time dashboards showing processing metrics and cash flow insights while sending automated reminders for pending approvals. Who It's For Perfect for medium to large businesses, accounting departments, and financial service providers processing more than 100 invoices monthly across multiple vendors. Ideal for organizations that need to enforce approval hierarchies and spending limits, require integration with existing ERP/accounting systems, want to reduce processing time from days to minutes, need audit trails and compliance reporting, and seek to eliminate manual data entry errors and duplicate payments. The Problem It Solves Manual invoice processing creates significant operational challenges including data entry errors (3-5% error rate), processing delays (8-10 days per invoice), duplicate payments (0.1-0.5% of invoices), approval bottlenecks causing late fees, lack of visibility into pending invoices and cash commitments, and compliance issues from missing audit trails. This workflow reduces processing time by 80%, eliminates data entry errors, prevents duplicate payments, and provides complete visibility into your payables process. Setup Instructions Google Drive Setup: Create dedicated folders for invoice intake and configure access permissions PDF Vector Configuration: Set up API credentials with appropriate rate limits for your volume Database Setup: Deploy the provided schema for vendor master and invoice tracking tables Email Integration: Configure IMAP credentials for invoice email monitoring (optional) ERP Connection: Set up API access to your accounting system (QuickBooks, SAP, etc.) Approval Rules: Define approval thresholds and routing rules in the configuration node Notification Setup: Configure Slack/email for approval notifications and alerts Key Features Multi-Channel Invoice Ingestion**: Automatically collect invoices from Google Drive, email attachments, and API uploads Advanced OCR and AI Extraction**: Process any invoice format including handwritten notes and poor quality scans Vendor Master Integration**: Validate and enrich vendor data, maintaining a clean vendor database 3-Way Matching**: Automatically match invoices to purchase orders and goods receipts Dynamic Approval Routing**: Route based on amount, department, vendor, or custom rules Duplicate Detection**: Prevent duplicate payments using fuzzy matching algorithms Real-Time Analytics**: Track KPIs like processing time, approval delays, and early payment discounts Exception Handling**: Intelligent routing of problematic invoices for manual review Audit Trail**: Complete tracking of all actions, approvals, and system modifications Payment Scheduling**: Optimize payment timing to capture discounts and manage cash flow Customization Options This workflow can be customized to add industry-specific extraction fields, implement GL coding rules based on vendor or amount, create department-specific approval workflows, add currency conversion for international invoices, integrate with additional systems (banks, expense management), configure custom dashboards and reporting, set up vendor portals for invoice status inquiries, and implement machine learning for automatic GL coding suggestions. Note: This workflow uses the PDF Vector community node. Make sure to install it from the n8n community nodes collection before using this template.