Workflow Templates

Tags: ESL, English Learning, Podcasts, RSS, AI Exercises, ElevenLabs Context Hi! I’m Samir, Supply Chain Engineer and Data Scientist based in Paris, and founder of the startup LogiGreen. I created this workflow for my mother, who is currently learning English, to turn the BBC 6 Minute English podcast into ready-to-use English lessons. The lesson includes vocabulary, exercises and discussion questions along with links to access the podcast content (audio and transcript). > Use this assistant to automatically share English lessons from a renowned podcast. 📬 For business inquiries, you can find me on LinkedIn Who is this template for? This template is designed for: ESL teachers** who want a fresh, structured lesson every week from real-life audio Independent learners** who want a guided way to study English with podcasts Language schools or content creators** who send regular English lessons by email What does this workflow do? This workflow acts as an AI-powered English lesson generator from podcast episodes. Runs every Sunday at 20:00 using a Schedule Trigger and reads the BBC 6 Minute English RSS feed Checks a Data Table of archived episodes and filters out those already sent (using their guid) Keeps the latest unsent episode and loads its web page content via HTTP Parses the HTML in a Code node to extract the episode description, full transcript and BBC vocabulary list Calls three AI nodes (OpenAI) to generate: a motivational email hook message fill-in-the-blank vocabulary exercises discussion questions related to the topic Combines all vocabulary words and sends them to ElevenLabs to generate a slow-paced audio track for listening practice Builds a prettify HTML email that includes: title, description, hook, vocabulary list, exercises, discussion questions and resource links Sends the final lesson by email via the Gmail node, with the vocabulary audio attached For example, this is the latest email generated by the workflow: P.S.: You can customise the footer to your school or company identity. 🎥 Tutorial I advise you to check the tutorial on my YouTube channel for the details on how to set up the nodes and customise the content: Next Steps Follow the stickers to set up all the nodes: Replace the Data Table reference with your own (storing at least guid, title, link, processed_date) Set up your OpenAI credentials in the three Model nodes Set up your ElevenLabs credentials and choose a voice in the audio node Configure your Gmail credentials and recipient email address in the Send Email node Adapt the RSS feed URL if you want to track another podcast or source Customise the HTML email (colours, logo, footer text) in the Prepare Email Code node Adjust the schedule (time or frequency) if you prefer another cadence Submitted: 18 November 2025 Template designed with n8n version 1.116.2

🛍️ 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).

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.

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.

Deep Multiline Icebreaker — AI-driven research + personalized cold outreach Deep Multiline Icebreaker automates high-quality, research-led outreach. Feed it a list of leads (emails + websites) and a short product brief via the built-in form; the workflow scrapes each company's site, extracts meaningful page content, uses GPT to produce concise page abstracts, aggregates insights, and then generates tailored, multi-line cold email bodies (JSON). Final outreach rows are appended automatically to a Google Sheet so you can review, sequence, or plug into your outreach stack. This template is built for SDRs, growth folks, and agencies who want dramatically better reply rates by replacing generic blasts with short, highly-specific icebreakers that reference subtle site signals. It’s opinionated (focuses on non-obvious details and concise, credible tone) but easy to tweak — prompts, output format, and the Google Sheet mapping are all editable inside n8n. How it works Form trigger — you submit product details, target designation, location, etc. Leads fetch — the workflow calls an external leads scraper (Apify act) to retrieve potential contacts. Filter & normalize — only rows with website + email proceed; links are normalized (relative/absolute handling). Scrape & convert — homepage and linked pages are fetched and converted to Markdown for clean input. Summarize (GPT) — each page is summarized into a two-paragraph abstract. Aggregate & generate — abstracts are aggregated and GPT generates a tailored multi-line icebreaker JSON (subject + body). Append to Google Sheets — resulting outreach content + lead metadata is appended to your sheet. Nodes of interest you can edit On form submission1 Leads Scraper1 Scrape Home1 Summarize Website Page1 Generate Multiline Icebreaker1 Add Row1 Quick Setup Guide 👉 Demo & Setup Video 👉 Sheet Template 👉 Course What you’ll need (credentials) OpenAI API key (used by Summarize Website Page1 and Generate Multiline Icebreaker1). Google Sheets OAuth (write access for Add Row1). Apify (or your leads-source) API token for Leads Scraper1 (the template calls an Apify act). Optional: outbound HTTP access from your n8n host to target websites. Recommended settings & best practices Limit batch sizes** (the template uses Limit1 set to 3 by default) — ramp the maxItems up slowly to respect rate limits and token costs. Prompt tweaks** — open the Generate Multiline Icebreaker1 prompt to tune tone, cost framing, or add product-specific selling points. Deduplication** — Remove Duplicate URLs1 is included; keep it ON to avoid repeated scraping. Privacy** — don’t store PII longer than necessary; if you store outreach drafts, ensure your Google Sheet access is restricted. Cost control** — set temperature lower (0–0.6) for more consistent outputs and monitor your OpenAI usage. Customization ideas Swap GPT model name or change prompt to produce shorter cold SMS or LinkedIn messages. Replace Apify with your own lead source (CSV upload, CRM query, or Airtable). Add an approval step (Slack/Email) before rows are appended to Google Sheets. Add a follow-up sequence generator that writes 2–3 follow-up messages per lead. Troubleshooting quick tips If pages return empty abstracts, check Request web page for URL1 and network access / user-agent restrictions. If outputs are malformed JSON, open the Generate Multiline Icebreaker1 node and validate the JSON output option. If Google Sheets fails, re-authorize the Google Sheets credential and ensure the sheet ID & sheet name are correct. Tags / Suggested listing fields outreach, lead-gen, sales-automation, openai, web-scraping, google-sheets

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.

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.

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.

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.

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

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

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.