by Colton Randolph
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.
by Jitesh Dugar
Automate your social media marketing by instantly promoting new Shopify products. This workflow polls your store for new arrivals, generates AI-powered captions, and publishes them across Instagram, Facebook, and Twitter/X—while maintaining a deduplication log in Airtable. 🎯 What This Workflow Does This workflow acts as a 24/7 social media manager, ensuring every new product gets immediate visibility without manual effort. ⏱️ Step 1 — Poll, Fetch & Deduplicate Schedule Trigger:** Polls Shopify every 10 minutes for products published in the last 15 minutes Deduplication Logic:** Checks Airtable (ProductPostLog) to avoid reposting the same product 🖼️ Step 2 — Data Enrichment & Media Hosting Normalization:** Cleans and maps product fields (title, price, vendor) CDN Hosting:** Downloads product image and uploads via UploadToURL to generate a public HTTPS URL 🤖 Step 3 — Platform-Specific AI Captions Instagram:** Storytelling style, emojis, 10+ hashtags Facebook:** Conversational, CTA-driven, link preview optimized Twitter/X:** Short-form (under 260 chars), includes price and link 📤 Step 4 — Multi-Platform Publishing & Logging Instagram:** Create container → publish via Graph API Facebook:** Post image + caption to Page Twitter/X:** Publish tweet via native node Airtable Log:** Store status, timestamp, and image URL for tracking ✨ Key Features Intelligent Deduplication:** Prevents duplicate posts using Airtable log Sequential Processing:** Handles products one-by-one to avoid rate limits Custom AI Tones:** Tailored captions for each platform Reliable Media Hosting:** UploadToURL ensures valid public image URLs 🔧 Setup Requirements Required Integrations Shopify:** Admin API with read_products scope Airtable:** Base with ProductPostLog table OpenAI:** API credentials for caption generation Facebook & Instagram:** Page token with posting permissions Twitter/X:** OAuth1 credentials UploadToURL:** CDN hosting for images Environment Variables SHOPIFY_STORE_DOMAIN SHOPIFY_ACCESS_TOKEN IG_ACCOUNT_ID FB_ACCESS_TOKEN FB_PAGE_ID Ready to launch? Import this template and connect your Shopify store to turn every new product into a viral social media event!
by Rohit Dabra
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.
by WeblineIndia
Real-Time WooCommerce Return Surge Detection with Slack Alerts & Airtable Logging This n8n workflow monitors WooCommerce refund activity to detect unusual spikes in product returns at the SKU level. It compares return volumes across rolling 24-hour windows, alerts teams in Slack when defined thresholds are exceeded and logs all detected events into Airtable for tracking and analysis. 🚀 Quick Start – Get This Running Fast Import the workflow into n8n. Connect your WooCommerce API credentials. Configure Slack and Airtable credentials. Set your preferred schedule interval. Activate the workflow and start monitoring returns automatically. What It Does This workflow is designed to automatically detect abnormal return behavior in a WooCommerce store. On every scheduled run, it fetches recent orders and refunds directly from the WooCommerce REST API. Refund records are mapped back to their original orders to accurately identify affected SKUs. Using a rolling time-window comparison, the workflow calculates current versus previous return counts per SKU. It identifies significant increases—either large percentage spikes or unusually high absolute return volumes. This ensures early detection of potential product quality, packaging or fulfillment issues. When a return surge is detected, the workflow sends a structured alert to a Slack channel and stores the alert data in Airtable. This creates a searchable, historical log that supports investigations, trend analysis and operational decision-making. Who’s It For This workflow is ideal for: eCommerce operations teams. Quality assurance and product managers. Customer support leads. Supply chain and fulfillment teams. Store owners running WooCommerce at scale. Requirements to Use This Workflow To use this workflow, you will need: An active WooCommerce store with REST API access. WooCommerce API credentials** (Consumer Key & Secret). An active Slack workspace with permission to post messages. An Airtable base and table for logging alerts. An n8n instance (self-hosted or cloud). How It Works & How To Set Up Workflow Execution Flow Schedule Trigger runs the workflow at a fixed interval. Time Window node defines current and previous 24-hour comparison windows. HTTP Orders fetches recent WooCommerce orders. HTTP Refunds fetches refund records. Orders_Fetch (Code) maps refunds to parent orders and extracts SKU-level data. Refund_details (Code) aggregates returns, compares windows, and calculates increases. IF Node checks surge conditions: ≥100% increase OR ≥25 current returns Set Fields enriches data with status, run date, and cooldown key. Slack Node sends a formatted alert message. Code Node normalizes Slack output into structured fields. Airtable Node stores alert records for future reference. Setup Instructions Replace {your_woocommerce_domain} with your actual store domain. Verify WooCommerce API permissions allow order and refund access. Select the correct Slack channel in the Slack node. Ensure Airtable column names match the workflow mappings. How To Customize Nodes You can easily adapt this workflow by: Changing the schedule frequency in the Schedule Trigger. Adjusting WINDOW_HOURS in the Code nodes. Modifying alert thresholds in the IF node. Customizing the Slack message format. Adding or removing Airtable fields for reporting needs. Add-ons (Optional Enhancements) This workflow can be extended with: Email or Microsoft Teams notifications. Jira or Linear ticket creation. Product auto-pause for extreme return spikes. Dashboard reporting using BI tools. Cooldown logic to prevent repeated alerts per SKU. Use Case Examples Common use cases include: Detecting defective product batches early. Identifying packaging or shipping damage trends. Monitoring supplier quality issues. Supporting refund root-cause analysis. Improving customer satisfaction metrics. There can be many more operational and analytical use cases based on your business needs. Troubleshooting Guide | Issue | Possible Cause | Solution | |------|---------------|----------| | No Slack alerts | Threshold not met | Lower IF condition limits | | Empty SKU values | Missing SKU in WooCommerce | Use product name or ID fallback | | No data in Airtable | Column mismatch | Verify field names and types | | API errors | Invalid credentials | Re-authorize WooCommerce API | | Duplicate alerts | Frequent schedule | Add cooldown or deduplication logic | Need Help? Need assistance setting this up or customizing it for your business? WeblineIndia can help you implement, extend or build similar automation workflows tailored to your operational needs. Whether you want advanced alerting, deeper analytics or cross-system integrations, our team is ready to help you get the most out of n8n automation.
by Andrey
Overview This n8n workflow automates brand monitoring across social media platforms (Reddit, LinkedIn, X, and Instagram) using the AnySite API. It searches posts mentioning your defined keywords, stores results in n8n Data Tables, analyzes engagement and sentiment, and generates a detailed AI-powered social media report automatically sent to your email. Key Features Multi-Platform Monitoring:** Reddit, LinkedIn, X (Twitter), and Instagram Automated Post Collection:** Searches for new posts containing tracked keywords Data Persistence:** Saves all posts and comments in structured Data Tables AI-Powered Reporting:** Uses GPT (OpenAI API) to summarize and analyze trends, engagement, and risks Automated Email Delivery:** Sends comprehensive daily/weekly reports via Gmail Comment Extraction:** Collects and formats post comments for deeper sentiment analysis Scheduling Support:** Can be executed manually or automatically (e.g., every night) How It Works Triggers The workflow runs: Automatically (via Schedule Trigger) — e.g., once daily Manually (via Manual Trigger) — for testing or on-demand analysis Data Collection Process Keyword Loading: Reads all keywords from the Data Table “Brand Monitoring Words” Social Media Search: For each keyword, the workflow calls the AnySite API endpoints: api/reddit/search/posts api/linkedin/search/posts api/twitter/search/posts (X) api/instagram/search/posts Deduplication: Before saving, checks if a post already exists in the “Brand Monitoring Posts” table. Data Storage: Inserts new posts into the Data Table with fields like type, title, url, vote_count, comment_count, etc. Comments Enrichment: For Reddit and LinkedIn, retrieves and formats comments into JSON strings, then updates the record. AI Analysis & Report Generation: The AI Agent (OpenAI GPT model) aggregates posts, analyzes sentiment, engagement, risks, and generates a structured HTML email report. Email Sending: Sends the final report via Gmail using your connected account. Setup Instructions Requirements Self-hosted or cloud n8n instance AnySite API key** – https://AnySite.io OpenAI API key** (GPT-4o or later) Connected Gmail account (for report delivery) Installation Steps Import the workflow Import the provided file: Social Media Monitoring.json Configure credentials AnySite API: Add access-token header with your API key OpenAI: Add your OpenAI API key in the “OpenAI Chat Model” node Gmail: Connect your Gmail account (OAuth2) in the “Send a message in Gmail” node Create required Data Tables 1️⃣ Brand Monitoring Words | Field | Type | Description | |-------|------|-------------| | word | string | Keyword or brand name to monitor | > Each row represents a single keyword to be tracked. 2️⃣ Brand Monitoring Posts | Field | Type | Description | |-------|------|-------------| | type | string | Platform type (e.g., reddit, linkedin, x, instagram) | | title | string | Post title or headline | | url | string | Direct link to post | | created_at | string | Post creation date/time | | subreddit_id | string | (Reddit only) subreddit ID | | subreddit_alias | string | (Reddit only) subreddit alias | | subreddit_url | string | (Reddit only) subreddit URL | | subreddit_description | string | (Reddit only) subreddit description | | comment_count | number | Number of comments | | vote_count | number | Votes, likes, or reactions count | | subreddit_member_count | number | (Reddit only) member count | | post_id | string | Unique post identifier | | text | string | Post body text | | comments | string | Serialized comments (JSON string) | | word | string | Matched keyword that triggered capture | AI Reporting Logic Collects all posts gathered during the run Aggregates by keyword and platform Evaluates sentiment, engagement, and risk signals Summarizes findings with an executive summary and key metrics Sends the Social Media Intelligence Report to your configured email Customization Options Schedule:** Adjust the trigger frequency (daily, hourly, etc.) Keywords:* Add or remove keywords in the *Brand Monitoring Words** table Report Depth:** Modify system prompts in the “AI Agent” node to customize tone and analysis focus Email Recipient:** Change the target email address in the “Send a message in Gmail” node Troubleshooting | Issue | Solution | |-------|-----------| | No posts found | Check AnySite API key and keyword relevance | | Duplicate posts | Verify Data Table deduplication setup | | Report not sent | Confirm Gmail OAuth2 connection | | AI Agent error | Ensure OpenAI API key and model selection are correct | Best Practices Use specific brand or product names in keywords for better precision Run the workflow daily to maintain fresh insights Periodically review and clean Data Tables Adjust AI prompt parameters to refine analytical tone Review AI-generated reports to ensure data quality Author Notes Created for automated cross-platform brand reputation monitoring, enabling real-time insights into how your brand is discussed online.
by Takumi Oku
Who’s it for This template is designed for Print-on-Demand (POD) business owners, independent artists, and e-commerce managers who want to automate the process of turning raw design files into listed products without manual data entry. How it works This workflow acts as an automated merchandise factory that handles everything from image processing to marketing. Trigger: The workflow starts when a new design file is uploaded to a specific Google Drive folder. Analyze: OpenAI Vision analyzes the image to determine the subject, mood, and color palette, and assesses copyright risk. Process: The image background is removed using Remove.bg, and the clean asset is uploaded to Cloudinary. Mockup: The workflow generates realistic product mockups (e.g., T-shirts, Tote bags) by overlaying the design onto base product images using Cloudinary transformations. Copywriting: OpenAI writes an SEO-friendly product title, description, and tags based on the visual analysis. Draft: A draft product is created in Shopify with the generated details and mockup image. Approval: A message is sent to Slack with the product details and mockup. The workflow pauses and waits for a human to click "Approve" or "Reject". Publish & Promote: If approved, the product is published to Shopify and automatically posted to Instagram and Pinterest. If rejected, a notification is sent to Slack. How to set up Base Images: Upload your blank product images (e.g., a white t-shirt, a tote bag) to your Cloudinary account and note their Public IDs. Configuration: Open the Workflow Configuration node and fill in all the required fields, including your API keys and the Cloudinary Public IDs for your base products. Credentials: Configure the credentials for Google Drive, OpenAI, Shopify, Slack, Instagram, and Pinterest in their respective nodes. Folder ID: Update the Google Drive Trigger node with the ID of the folder you want to watch. Requirements n8n (Self-hosted or Cloud) Google Drive account OpenAI API key (Access to GPT-4o model recommended for Vision capabilities) Remove.bg API key Cloudinary account Shopify store Slack workspace Instagram Business account Pinterest account How to customize Mockups: You can modify the Code - Generate Mockup URLs node to add more product types (e.g., Hoodies, Mugs) by adding their Cloudinary Public IDs. Prompt Engineering: Adjust the system prompt in the OpenAI - SEO Copywriting node to match your brand voice or language style. Social Channels: Add or remove nodes to support other platforms like Twitter (X) or Facebook Pages.
by Yaron Been
Description This workflow automatically scans companies for signs of financial distress across filings, insolvency registers, and financial news. It helps procurement, credit, and risk teams detect early warning signals before a supplier or partner defaults. Overview This workflow uses Bright Data to scrape financial filings, insolvency registers, and news sources for distress signals like bankruptcy, restructuring, or payment defaults. AI classifies the type and severity of distress, applies probability weighting and confidence guardrails, then generates structured business decisions — including: Supplier Monitoring risk status Onboarding Approval recommendations Portfolio Exposure classifications All outputs are logged into Google Sheets for tracking and auditability. Tools Used n8n**: Automation platform orchestrating the workflow Bright Data**: Scrapes filings, insolvency registers, and financial news without getting blocked OpenRouter**: AI-powered distress classification, risk scoring, and business decision generation Google Sheets**: Logs supplier risk status, onboarding decisions, portfolio exposure, and errors How to Install 1. Import the Workflow Download the .json file and import it into your n8n instance. 2. Configure Bright Data Add your Bright Data API credentials to all Bright Data nodes. 3. Configure OpenRouter Add your OpenRouter API key for AI distress classification and decision generation. 4. Set Up Google Sheets Create a spreadsheet following the "Google Sheets Setup" sticky note inside the workflow. Connect each Google Sheets node to your document. 5. Customize Edit the configuration node to define: Target company Country Risk indicators Monitoring scope Use Cases Procurement Teams Monitor supplier financial health and get alerts before disruptions hit your supply chain. Credit Risk Analysts Screen new vendors or partners for bankruptcy signals and insolvency red flags. Onboarding Workflows Automate go/no-go decisions for new supplier or partner approvals. Portfolio Managers Track financial exposure across your vendor or investment portfolio. Finance Teams Detect early signs of distress in key business relationships before they become critical. Connect with Me Website: https://www.nofluff.online YouTube: https://www.youtube.com/@YaronBeen/videos LinkedIn: https://www.linkedin.com/in/yaronbeen/ Get Bright Data: https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) Tags #n8n #automation #brightdata #webscraping #creditrisk #financialdistress #riskmanagement #suppliermonitoring #supplychainrisk #insolvency #bankruptcy #duediligence #vendorscreening #portfoliorisk #financialanalysis #n8nworkflow #workflow #nocode #businessintelligence #riskassessment #creditanalysis #procurementautomation #supplierrisk #financialmonitoring #earlywarning
by shae
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
by PDF Vector
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.
by David Olusola
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
by Trung Tran
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.
by Mirai
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.