Workflow Templates

Public Transport Delay Tracker with Microsoft Teams and Todoist ⚠️ COMMUNITY TEMPLATE DISCLAIMER: This is a community-contributed template that uses ScrapeGraphAI (a community node). Please ensure you have the ScrapeGraphAI community node installed in your n8n instance before using this template. This workflow continuously monitors public-transportation websites and apps for real-time schedule changes and delays, then posts an alert to a Microsoft Teams channel and creates a follow-up task in Todoist. It is ideal for commuters or travel coordinators who need instant, actionable updates about transit disruptions. Pre-conditions/Requirements Prerequisites An n8n instance (self-hosted or n8n cloud) ScrapeGraphAI community node installed Microsoft Teams account with permission to create an Incoming Webhook Todoist account with at least one project Access to target transit authority websites or APIs Required Credentials ScrapeGraphAI API Key** – Enables scraping of transit data Microsoft Teams Webhook URL** – Sends messages to a specific channel Todoist API Token** – Creates follow-up tasks (Optional) Transit API key if you are using a protected data source Specific Setup Requirements | Resource | What you need | |--------------------------|---------------------------------------------------------------| | Teams Channel | Create a channel → Add “Incoming Webhook” → copy the URL | | Todoist Project | Create “Transit Alerts” project and note its Project ID | | Transit URLs/APIs | Confirm the URLs/pages contain the schedule & delay elements | How it works This workflow continuously monitors public-transportation websites and apps for real-time schedule changes and delays, then posts an alert to a Microsoft Teams channel and creates a follow-up task in Todoist. It is ideal for commuters or travel coordinators who need instant, actionable updates about transit disruptions. Key Steps: Webhook (Trigger)**: Starts the workflow on a schedule or via HTTP call. Set Node**: Defines target transit URLs and parsing rules. ScrapeGraphAI Node**: Scrapes live schedule and delay data. Code Node**: Normalizes scraped data, converts times, and flags delays. IF Node**: Determines if a delay exceeds the user-defined threshold. Microsoft Teams Node**: Sends formatted alert message to the selected Teams channel. Todoist Node**: Creates a “Check alternate route” task with due date equal to the delayed departure time. Sticky Note Node**: Holds a blueprint-level explanation for future editors. Set up steps Setup Time: 15–20 minutes Install community node: In n8n, go to “Manage Nodes” → “Install” → search for “ScrapeGraphAI” → install and restart n8n. Create Teams webhook: In Microsoft Teams, open target channel → “Connectors” → “Incoming Webhook” → give it a name/icon → copy the URL. Create Todoist API token: Todoist → Settings → Integrations → copy your personal API token. Add credentials in n8n: Settings → Credentials → create new for ScrapeGraphAI, Microsoft Teams, and Todoist. Import workflow template: File → Import Workflow JSON → select this template. Configure Set node: Replace example transit URLs with those of your local transit authority. Adjust delay threshold: In the Code node, edit const MAX_DELAY_MINUTES = 5; as needed. Activate workflow: Toggle “Active”. Monitor executions to ensure messages and tasks are created. Node Descriptions Core Workflow Nodes: Webhook** – Triggers workflow on schedule or external HTTP request. Set** – Supplies list of URLs and scraping selectors. ScrapeGraphAI** – Scrapes timetable, status, and delay indicators. Code** – Parses results, converts to minutes, and builds payloads. IF** – Compares delay duration to threshold. Microsoft Teams** – Posts formatted adaptive-card-style message. Todoist** – Adds a task with priority and due date. Sticky Note** – Internal documentation inside the workflow canvas. Data Flow: Webhook → Set → ScrapeGraphAI → Code → IF a. IF (true branch) → Microsoft Teams → Todoist b. IF (false branch) → (workflow ends) Customization Examples Change alert message formatting // In the Code node const message = `⚠️ Delay Alert: Route: ${item.route} Expected: ${item.scheduled} New Time: ${item.newTime} Delay: ${item.delay} min Link: ${item.url}`; return [{ json: { message } }]; Post to multiple Teams channels // Duplicate the Microsoft Teams node and reference a different credential items.forEach(item => { item.json.webhookUrl = $node["Set"].json["secondaryChannelWebhook"]; }); return items; Data Output Format The workflow outputs structured JSON data: { "route": "Blue Line", "scheduled": "2024-12-01T14:25:00Z", "newTime": "2024-12-01T14:45:00Z", "delay": 20, "status": "Delayed", "url": "https://transit.example.com/blue-line/status" } Troubleshooting Common Issues Scraping returns empty data – Verify CSS selectors/XPath in the Set node and ensure the target site hasn’t changed its markup. Teams message not sent – Check that the stored webhook URL is correct and the connector is still active. Todoist task duplicated – Add a unique key (e.g., route + timestamp) to avoid inserting duplicates. Performance Tips Limit the number of URLs per execution when monitoring many routes. Cache previous scrape results to avoid hitting site rate limits. Pro Tips: Use n8n’s built-in Cron instead of Webhook if you only need periodic polling. Add a SplitInBatches node after scraping to process large route lists incrementally. Enable execution logging to an external database for detailed audit trails.

How it works A webhook receives a form submission with an email address The email is validated, then Lusha enriches the contact If phone or email is missing, a fallback provider fills the gaps via HTTP request Data from both sources is merged, upserted into HubSpot, and an SDR alert is sent to Slack The webhook returns the enriched lead as a JSON response Set up steps Install the Lusha community node Add your Lusha API, HubSpot, and Slack credentials Configure the fallback HTTP node with your secondary provider's API endpoint and key Point your form's action URL to the webhook endpoint

Template Description 📝 Template Title Analyze Amazon product reviews with Gemini and save to Google Sheets 📄 Description This workflow automates the process of analyzing customer feedback on Amazon products. Instead of manually reading through hundreds of reviews, this template scrapes reviews (specifically targeting negative feedback), uses Google Gemini (AI) to analyze the root causes of dissatisfaction, and generates specific improvement suggestions. The results are automatically logged into a Google Sheet for easy tracking, and a Slack notification is sent to keep your team updated. This tool is essential for understanding "Voice of Customer" data efficiently without manual data entry. 🧍 Who is this for Product Managers** looking for product improvement ideas. E-commerce Sellers (Amazon FBA, D2C)** monitoring brand reputation. Market Researchers** analyzing competitor weaknesses. Customer Support Teams** identifying recurring issues. ⚙️ How it works Data Collection: The workflow triggers the Apify actor (junglee/amazon-reviews-scraper) to fetch reviews from a specified Amazon product URL. It is currently configured to filter for 1 and 2-star reviews to focus on complaints. AI Analysis: It loops through each review and sends the content to Google Gemini. The AI determines a sentiment score (1-5), categorizes the issue (Quality, Design, Shipping, etc.), summarizes the complaint, and proposes a concrete improvement plan. Formatting: A Code node parses the AI's response to ensure it is in a clean JSON format. Storage: The structured data is appended as a new row in a Google Sheet. Notification: A Slack message is sent to your specified channel to confirm the batch analysis is complete. 🛠️ Requirements n8n** (Self-hosted or Cloud) Apify Account:** You need to rent the junglee/amazon-reviews-scraper actor. Google Cloud Account:** For accessing the Gemini (PaLM) API and Google Sheets API. Slack Account:** For receiving notifications. 🚀 How to set up Apify Config: Enter your Apify API token in the credentials. In the "Run an Actor" node, update the startUrls to the Amazon product page you want to analyze. Google Sheets: Create a new Google Sheet with the following header columns: sentiment_score, category, summary, improvement. Copy the Spreadsheet ID into the Google Sheets node. AI Prompt: The "Message a model" node contains the prompt. It is currently set to output results in Japanese. If you need English output, simply translate the prompt text inside this node. Slack: Select the channel where you want to receive notifications in the Slack node.

Submit a screen recording URL, customer name, and bug type through a simple web form. The workflow automatically scans the recording using WayinVideo AI to pinpoint the exact moment the bug occurs, then uses GPT-4o-mini to write a structured support ticket with priority, steps to reproduce, and a fix suggestion. The completed ticket is saved instantly as a new row in your Google Sheet — ready for your dev team. Built for support agents, QA teams, and SaaS companies who want to triage bugs faster without manual video scrubbing. What This Workflow Does AI bug detection** — Sends the screen recording to WayinVideo, which scans the video and finds the exact timestamp where the bug occurs Smart polling loop** — Automatically waits 45 seconds then checks for results, retrying until WayinVideo returns the bug moments Structured ticket generation** — GPT-4o-mini reads the bug moment data and writes a full support ticket with priority level, steps to reproduce, expected vs actual behaviour, and a suggested fix Auto-triage and assignment** — The AI decides severity (Critical to Low) and which team should own it (Backend, Frontend, QA, DevOps, or Product) Google Sheets logging** — Every ticket is saved with customer name, bug type, recording URL, timestamp, ticket content, status, and submission date Web form trigger** — A built-in form lets any support agent submit a bug report without touching n8n directly Setup Requirements Tools you'll need Active n8n instance (self-hosted or n8n Cloud) WayinVideo account + API key (for AI video bug detection) OpenAI API key (GPT-4o-mini for ticket generation) Google account with Google Sheets OAuth access Estimated Setup Time: 10–15 minutes Step-by-Step Setup Get your WayinVideo API key — Sign in to your WayinVideo account at WayinVideo, go to your API settings, and copy your key. Add the WayinVideo key to the Find Bug Moments step — Open the node called 2. WayinVideo — Find Bug Moments and replace YOUR_WAYINVIDEO_API_KEY in the Authorization header with your actual key. Add the WayinVideo key to the Get Bug Moments step — Open the node called 4. WayinVideo — Get Bug Moments and replace YOUR_WAYINVIDEO_API_KEY in the Authorization header with your actual key. > ⚠️ Your WayinVideo API key appears in two nodes — replace it in both 2. WayinVideo — Find Bug Moments and 4. WayinVideo — Get Bug Moments or the workflow will fail. Add your OpenAI API key — In n8n, go to Credentials and create a new OpenAI credential. Paste your API key there. Then connect that credential to the node called 6a. OpenAI — Chat Model (GPT-4o-mini). Create your Google Sheet — Make a new Google Sheet with a tab named exactly Bug Tickets. Add these column headers in row 1: | Customer Name | Bug Type | Recording URL | Bug Moments Found | Top Bug Timestamp | Bug Ticket | Status | Date Submitted | Connect your Google account — In n8n, create a Google Sheets OAuth2 credential and connect your Google account. Apply that credential to the node called 7. Google Sheets — Save Bug Ticket. Add your Google Sheet ID — Open the node 7. Google Sheets — Save Bug Ticket and replace YOUR_GOOGLE_SHEET_ID with your actual Sheet ID. You can find this in the Google Sheet URL — it is the long string of characters between /d/ and /edit. Activate the workflow — Toggle the workflow to Active. Open the form URL from the 1. Form — Bug Recording + Details node and submit a test bug report to confirm everything is working. How It Works (Step by Step) Step 1 — Web Form (Bug Recording + Details) A support agent opens a web form and fills in three fields: the screen recording URL, the customer's name, and the type of bug (for example: Login Error, Payment Failure, or App Crash). Submitting the form kicks off the entire workflow automatically. Step 2 — WayinVideo — Find Bug Moments The recording URL is sent to the WayinVideo API with an instruction to search for moments matching the reported bug type. WayinVideo scans the video using AI and starts building a list of the most relevant bug moments, including timestamps and relevance scores. The API returns a job ID that is used in the next steps. Step 3 — Wait 45 Seconds The workflow pauses for 45 seconds to give WayinVideo time to process the video before checking for results. Step 4 — WayinVideo — Get Bug Moments Using the job ID from Step 2, the workflow requests the results from WayinVideo. This returns a list of clips, each with a title, description, start and end timestamp, and a relevance score. Step 5 — Check: Bug Moments Found? The workflow checks whether WayinVideo has returned any bug moment clips yet. If yes** — it moves forward to generate the ticket. If no** — it loops back to Step 3, waits another 45 seconds, and checks again. > ⚠️ If WayinVideo never returns results (for example, if the URL is broken or the video format is unsupported), this loop will repeat indefinitely. Consider adding a retry limit to avoid runaway executions. Step 6 — AI Agent — Generate Bug Ticket GPT-4o-mini receives the customer details from the form and the bug moment data from WayinVideo. It writes a complete structured support ticket covering: a one-sentence bug summary, priority level, bug category, exact video timestamp, steps to reproduce, expected vs actual behaviour, which team to assign it to, and a suggested fix. Step 7 — Google Sheets — Save Bug Ticket The completed ticket is appended as a new row in your Google Sheet. The row includes the customer name, bug type, recording URL, number of bug moments found, the top bug timestamp, the full ticket text, a status of "Open", and the submission date and time. Key Features ✅ Exact bug timestamp detection — WayinVideo pinpoints the precise moment in the recording where the bug occurs, so your dev team doesn't have to watch the whole video ✅ Auto-priority assignment — GPT-4o-mini assigns Critical, High, Medium, or Low priority based on the type of bug reported ✅ Auto-team routing — The AI decides whether the ticket belongs to Backend Dev, Frontend Dev, QA, DevOps, or Product — no manual triage needed ✅ Smart retry loop — The workflow polls WayinVideo automatically every 45 seconds until results are ready, with no manual intervention required ✅ Structured ticket format — Every ticket follows the same format with all required fields, making it consistent and ready to import into any project management tool ✅ Zero-code form — Support agents submit bug reports through a hosted web form — no n8n access needed ✅ Full audit trail in Sheets — Every ticket is logged with submission date, recording URL, and status so nothing falls through the cracks Customisation Options Capture more bug moments — In the node 2. WayinVideo — Find Bug Moments, change "limit": 3 to "limit": 5 to detect up to five bug moments per recording instead of three. Use a more powerful AI model — In the node 6a. OpenAI — Chat Model (GPT-4o-mini), switch from gpt-4o-mini to gpt-4o for higher-quality ticket writing on complex or ambiguous bugs. Send instant Slack alerts — Add a Slack node after 7. Google Sheets — Save Bug Ticket to notify your dev channel as soon as a new ticket is saved, including the priority level and timestamp. Add a max-retry counter — To prevent the polling loop from running forever, add a counter variable that increments each loop and an extra condition in 5. If — Bug Moments Found? to stop after a set number of attempts (for example, 10 retries). Push tickets to Jira or Linear — Replace or add after the Google Sheets node an HTTP Request node that calls the Jira or Linear API to create an issue automatically from the generated ticket content. Support multiple languages — Change "target_lang": "en" in 2. WayinVideo — Find Bug Moments to another language code (for example "fr" or "de") to handle recordings in other languages. Support Need help setting this up or want a custom version built for your team or agency? 📧 Email: info@isawow.com 🌐 Website: https://isawow.com/

🤖 Automated Multi-lingual News Curator & Archiver Overview This workflow automates news monitoring by fetching RSS feeds, rewriting content using AI, translating it (EN/ZH/KO), and archiving it. Who is this for? Content Curators, Localization Teams, and Travel Bloggers. How it works Fetch & Filter: Pulls NHK RSS and filters for keywords (e.g., "Tokyo"). AI Processing: Google Gemini rewrites articles, extracts locations, and translates text. Archive & Notify: Saves structured data to Google Sheets and alerts Slack. Setup Requirements Credentials: Google Gemini, Google Sheets, Slack. Google Sheet: Create headers: title, summary, location, en, zh, ko, url. Slack: Configure Channel IDs. Customization RSS Read:** Change feed URL. If Node:** Update filter keywords. AI Agent:** Adjust system prompts for tone. 1. Fetch & Filter Runs on a schedule to fetch the latest RSS items. Filters articles based on specific keywords (e.g., "Tokyo" or "Season") before processing. 2. AI Analysis & Parsing Uses Google Gemini to rewrite the news, extract specific locations, and translate content. The Code node cleans the JSON output for the database. 3. Archive & Notify Appends the structured data to Google Sheets and sends a formatted notification to Slack (or alerts if an article was skipped). Output Example (JSON) The translation agent outputs data in this format: { "en": "Tokyo Tower is...", "zh": "东京塔是...", "ko": "도쿄 타워는..." }

Who is this for? Marketing teams who need quick video ads without a production crew E-commerce sellers promoting products on social media Freelancers and agencies producing ad creatives for clients Anyone who wants to turn a product description into a video ad in minutes What problem does this solve? Producing a video ad typically requires a designer for the visuals, a motion artist for animation, and hours of back-and-forth. This workflow replaces that entire pipeline — fill out a form, and get a ready-to-use video ad delivered to your inbox. What this workflow does Collects product name, description, visual style, and recipient email through a web form AI Agent analyzes the product and uses both deAPI Image Prompt Booster and Video Prompt Booster tools to create optimized prompts for image and video generation Generates a 1280x720 landscape product hero image using deAPI Animates the hero image into a short video ad using deAPI image-to-video generation Emails the video ad link to the specified address via Gmail Setup Requirements n8n instance** (self-hosted or n8n Cloud) deAPI account for prompt boosting, image generation, and video generation Anthropic account for the AI Agent Gmail account for email delivery Installing the deAPI Node n8n Cloud: Go to **Settings → Community Nodes and toggle the "Verified Community Nodes" option Self-hosted: Go to **Settings → Community Nodes and install n8n-nodes-deapi Configuration Add your deAPI credentials (API key + webhook secret) Add your Anthropic credentials (API key) Add your Gmail credentials (OAuth2) Ensure your n8n instance is on HTTPS How to customize this workflow Change the AI model**: Swap Anthropic for OpenAI, Google Gemini, or any other LLM provider Adjust the creative direction**: Modify the AI Agent system message to target different ad styles (product demo, lifestyle, teaser, etc.) Change the delivery method**: Replace Gmail with Slack, Microsoft Teams, or upload directly to Google Drive / S3 Change the aspect ratio**: Switch from landscape to square or portrait for Instagram Stories or TikTok Add background removal**: Insert a deAPI Remove Background node before video generation for a clean product cutout Batch processing**: Replace the Form Trigger with a Google Sheets or Airtable trigger to generate ads for a product catalog

This workflow automates the creation of user-generated-content-style product videos by combining Gemini's image generation with OpenAI's SORA 2 video generation. It accepts webhook requests with product descriptions, generates images and videos, stores them in Google Drive, and logs all outputs to Google Sheets for easy tracking. Main Use Cases Automate product video creation for e-commerce catalogs and social media. Generate UGC-style content at scale without manual design work. Create engaging video content from simple text prompts for marketing campaigns. Build a centralized library of product videos with automated tracking and storage. How it works The workflow operates as a webhook-triggered process, organized into these stages: Webhook Trigger & Input Accepts POST requests to the /create-ugc-video endpoint. Required payload includes: product prompt, video prompt, Gemini API key, and OpenAI API key. Image Generation (Gemini) Sends the product prompt to Google's Gemini 2.5 Flash Image model. Generates a product image based on the description provided. Data Extraction Code node extracts the base64 image data from Gemini's response. Preserves all prompts and API keys for subsequent steps. Video Generation (SORA 2) Sends the video prompt to OpenAI's SORA 2 API. Initiates video generation with specifications: 720x1280 resolution, 8 seconds duration. Returns a video generation job ID for polling. Video Status Polling Continuously checks video generation status via OpenAI API. If status is "completed": proceeds to download. If status is still processing: waits 1 minute and retries (polling loop). Video Download & Storage Downloads the completed video file from OpenAI. Uploads the MP4 file to Google Drive (root folder). Generates a shareable Google Drive link. Logging to Google Sheets Records all generation details in a tracking spreadsheet: Product description Video URL (Google Drive link) Generation status Timestamp Summary Flow: Webhook Request → Generate Product Image (Gemini) → Extract Image Data → Generate Video (SORA 2) → Poll Status → If Complete: Download Video → Upload to Google Drive → Log to Google Sheets → Return Response If Not Complete: Wait 1 Minute → Poll Status Again Benefits: Fully automated video creation pipeline from text to finished product. Scalable solution for generating multiple product videos on demand. Combines cutting-edge AI models (Gemini + SORA 2) for high-quality output. Centralized storage in Google Drive with automatic logging in Google Sheets. Flexible webhook interface allows integration with any application or service. Retry mechanism ensures videos are captured even with longer processing times. Created by Daniel Shashko

📄Template Creator How it works This workflow accepts any uploaded document (PDF or DOCX) via webhook and automatically converts it into a reusable fill-in-the-blank template. Step 1 — Identify: GPT-4o first reads the document and determines the document type (e.g., Employment Contract, Invoice, NDA, Lease Agreement, Project Proposal) and the specific variable fields that type of document typically contains. Step 2 — Templatize: A second AI pass uses the identified document type and field list to replace all variable content with clearly labeled [BRACKET] placeholders while preserving all static boilerplate and structure verbatim. Step 3 — Deliver: The cleaned template is rendered to PDF via Gotenberg, uploaded to Google Drive, made publicly accessible, and a JSON response with file URLs is returned to the caller. Setup Configure the Webhook path if needed (default: general-template-creator) Set your OpenAI credential on both LLM nodes Set your Google Drive credential and confirm the target folder ID in the Upload node Confirm the Gotenberg URL matches your self-hosted instance Install the community node n8n-nodes-word2text (see ⚠️ warning sticky) Customization Swap GPT-4o for GPT-4.1 or GPT-4.1-mini on the Identify node to reduce cost on the lighter classification task Add a Switch node after identification to route different document types to type-specific prompts Modify the Drive folder ID to sort templates into subfolders by document type Document accepts input from a form such as the one found here: Sample Form

This n8n template builds an automated health monitoring dashboard for your homelab Docker host. It SSHs into your server, collects 30+ system and container metrics, analyzes trends with AI, and delivers a structured multi-embed dashboard to Discord -- plus real-time critical alerts when things go wrong. Stop SSHing into your server every morning to check if everything's still running. AI reads your metrics and tells you exactly what needs attention, with copy-paste fix commands. Good to know Estimated cost is ~$0.003 per daily run using GPT-4o-mini. Compatible with Claude or any OpenAI-compatible LLM -- swap the model sub-node to switch providers. See the setup notes inside the workflow for Claude configuration. Uses Google Sheets for 7-day metric history and trend analysis. A one-click setup trigger auto-creates a formatted tracking spreadsheet with frozen headers and conditional formatting. The critical alert path runs every 5 minutes with a lightweight check (configurable). The daily digest runs once in the morning. Both schedules are adjustable. How it works Daily schedule trigger SSHs into your Docker host and collects system metrics (real CPU % from /proc/stat, memory, all filesystems, swap, network I/O, top processes, zombie processes, failed services) and Docker metrics (container status, CPU, memory, restarts, health checks, disk usage, dangling images) in ~2 seconds A 100-point health score is calculated from weighted metrics across CPU, memory, disk, swap, containers, and system health 7 days of historical data is loaded from Google Sheets for trend comparison AI analyzes current vs. historical metrics and returns structured JSON with severity-tagged findings, CLI fix commands, trend analysis, and a top recommendation A 4-embed Discord dashboard is delivered: status header with inline metrics, actionable findings, Docker ecosystem overview with trends, and a footer with timing and API cost Today's metrics are stored in Google Sheets for future trend tracking A separate lightweight path runs every 5 minutes checking critical thresholds (disk > 90%, memory > 95%, inodes > 90%, containers down) and fires immediate alerts How to use Click "Test workflow" on the first-time setup trigger to auto-create your Google Sheets tracking dashboard Copy the Sheet ID into the configuration node, add your Discord webhook URL, wire your SSH and OpenAI credentials, and activate Full setup guides linked inside the workflow for SSH keys, API keys, and Discord webhooks Requirements SSH access to a Linux Docker host (key-based authentication) (ssh key setup) OpenAI API key or Anthropic API key (OpenAI setup guide | Claude setup guide) Google Sheets OAuth2 credential (n8n docs) Discord webhook URL (setup guide) Customizing this workflow Adjust alert thresholds in the configuration node (disk warning/critical, memory warning/critical, inode critical, restart threshold) Change the daily digest and critical alert schedules in the trigger nodes Swap OpenAI for Claude or Ollama by replacing the LLM sub-node Replace Discord with Slack, Telegram, or ntfy by modifying the webhook payload format Add additional SSH metrics by editing the collection commands

How It Works This workflow provides automated Chinese text translation with high-quality audio synthesis for language learning platforms, content creators, and international communication teams. It addresses the challenge of converting Chinese text into accurate multilingual translations with natural-sounding voiceovers. The system receives Chinese text via webhook, validates input formatting, and processes it through an AI translation agent that generates multiple language versions. Each translation is converted to speech using ElevenLabs' neural voice models, then formatted into professional audio responses. A quality review agent evaluates translation accuracy, cultural appropriateness, and audio clarity against predefined criteria. High-scoring outputs are returned via webhook for immediate use, while low-quality results trigger review processes, ensuring consistent delivery of publication-ready multilingual audio content. Setup Steps Obtain OpenAI API key and configure in "Translation Agent" Set up ElevenLabs account, generate API key Configure webhook URL and update in source applications to trigger workflow Customize target languages and voice settings in translation and ElevenLabs nodes Adjust quality thresholds in "Check Quality Score" Update output webhook endpoint in "Return Audio Files" node Prerequisites Active accounts: OpenAI API access, ElevenLabs subscription. Use Cases Chinese language learning apps, international marketing content localization Customization Add additional target languages, modify voice characteristics and speaking rates Benefits Automates 95% of translation workflow, delivers publication-ready audio in minutes

🧩 Template Description IP Enrichment & Country Attribution is a lightweight cybersecurity automation that enriches IP addresses with geographic and network intelligence. It validates incoming IPs, filters out private or invalid addresses, and enriches public IPs using an open-source IP enrichment service. 🔄 How It Works Receives an IP address via webhook (API or Slack). Validates the IP format and rejects invalid input. Checks for private or internal IP ranges. Ignores private IPs with a clear response. Enriches public IPs using an open-source IP intelligence service. Normalizes country, ISP, and ASN data and applies a severity label. Slack notifications are sent for enriched public IPs. Returns a structured JSON response. ⚙️ Setup Steps Import & Activate Workflow Import the JSON template into n8n Actvate the workflow Set Up Webhook Copy the webhook URL Send a POST request with the IP in the body, e.g.: { "text" : "8.8.8.8" } Using curl: `curl -X POST https://YOUR_N8N_WEBHOOK_URL \ -H "Content-Type: application/json" \ -d '{"text":"8.8.8.8"}'` Configure Slack (Slack Alert) Create or select Slack credentials in n8n Make sure the bot is in your target channel Update the Slack node with correct channel. Slack Slash Command Setup (Optional) Enable Slash Commands and create new command (for example /ip-enrich). Set the Request URL to your n8n webhook endpoint. Choose POST as the request method. Install the app to your workspace. Usage example: /ip-enrich 8.8.8.8 🎛️ Customization Options Enrichment source: Replace or extend the IP intelligence API with additional providers (for example reputation or abuse scoring). Slack formatting: Customize the Slack message text, emojis, or use threads for better alert grouping. Input sources: Reuse the webhook for other integrations such as SIEM alerts or security tools.

AI-Powered Flyer & Video Generator with Airtable, Klie.ai, and n8n Who is this for? This template is perfect for e-commerce entrepreneurs, marketers, agencies, and creative teams who want to turn simple product photos and short descriptions into professional flyers or product videos—automatically and at scale. If you want to generate polished marketing assets without relying on designers or editors, this is for you. What problem is this workflow solving? Creating product ads, flyers, or videos usually involves multiple tools and manual steps: Collecting and cleaning product photos Writing ad copy or descriptions Designing flyers or visuals for campaigns Producing animations or video ads Managing multiple revisions and approvals This workflow automates the entire pipeline. Upload a raw product image into Airtable, type a quick description, and receive back a flyer or video animation tailored to your brand and context—ready to use for ads, websites, or campaigns. What this workflow does Uses Airtable as the central interface where you upload raw product photos and enter descriptions Processes the content automatically via n8n Generates flyers and visuals using OpenAI Image 1 Produces custom product videos with Google’s VEO3 Runs through Klie.ai to unify the image + video generation process Sends the final creative assets back into Airtable for review and download Setup Download n8n files and connect your Airtable token to n8n Duplicate the Airtable base and make sure you’re on an Airtable Team plan Add your API key on the Airtable interface under API setup Create your agency inside the interface Start generating concept images and videos instantly How to customize this workflow to your needs Edit the prompts to match your brand voice and ad style Extend Airtable fields to include more creative parameters (colors, layout, target audience) Add approval steps via email, Slack, or Airtable statuses before finalizing Integrate with publishing platforms (social media, e-commerce CMS) for auto-posting Track generated assets inside Airtable for team collaboration 🎥 Demo Video: Demo Video