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By Kai Hölters

Classify YouTube Trends and Generate Email Summaries with GPT-4 and Gmail Monitor YouTube channels, fetch stats, classify videos as viral (≥ 1000 likes) or normal, and auto‑generate LinkedIn/email summaries with GPT‑4. Deliver via Gmail or SMTP. Clear node names, examples, and auditable fields. 🎯 Overview This template monitors YouTube channels via RSS or the YouTube Data API, retrieves video stats, classifies each video as viral (≥ 1000 likes) or normal, and produces concise LinkedIn/email summaries with OpenAI (GPT‑4 family). It can send a compact weekly briefing via Gmail (OAuth2) or SMTP. Built for creators, marketing teams, and agencies who want automated trend alerts and ready‑to‑use content. This screenshot shows the Gmail-ready weekly briefing generated by the Generate Weekly Briefing (HTML) node in my YouTube Trend Detector workflow, confirming the end-to-end pipeline: RSS/API → stats → like-based classification (≥ 1000 = viral) → LLM summaries → HTML email. 🧭 How It Works (Node Map) Manual Run – ad‑hoc execution Set Channel IDs – provide one or more YouTube channelId values Split Channels – process channels one by one Fetch Latest Videos (RSS) – pull recent uploads via channel RSS Filter: Published in Last 72h – only recent items are kept Get Video Stats (YouTube API) – request snippet,statistics for likes and details Classify by Likes (Code) – sets classification to viral or normal Branch: Normal / Branch: Viral – separate LLM prompts per relevance Write Post (Normal / Viral) – generate LinkedIn‑style notes via OpenAI Aggregate Posts for Briefing – merge all texts into one block Generate Weekly Briefing (HTML) – produce a Gmail‑robust HTML email via GPT Send Weekly Briefing (Gmail/SMTP) – deliver briefing (you set recipients) ⚙️ Quick Start (≈ 3 minutes) Import the sanitized JSON into n8n (Menu → Import). Create credentials (use exact names): YouTube_API_Key — Generic credential (field: apiKey) OpenAi account — OpenAI API Key Gmail account (OAuth2) or SMTP_Default (SMTP) Configure channels: In Set Channel IDs, list your YouTube channelId values (e.g., UC…). Set recipients: In Send Weekly Briefing, add your target email(s). Test: Run Execute Workflow and review outputs from the LLM and send nodes. 🔑 Required Credentials YouTube_API_Key** — YouTube Data API v3 key (field apiKey) OpenAi account** — OpenAI API key for LLM nodes Gmail account* (OAuth2, recommended) *or* *SMTP_Default** (server/port/TLS + app password if 2FA) 🧩 Key Parameters & Adjustments Viral threshold:** In Classify by Likes (Code) → const THRESHOLD = 1000; YouTube API parts:** Use part=snippet,statistics to obtain likeCount Time window:* The filter keeps videos from the *last 72 hours** 🧪 Troubleshooting Missing likeCount / classification = "unknown"** → ensure part=statistics and a valid API key credential. Gmail OAuth redirect_mismatch / access_denied** → redirect must be https://<your-n8n-host>/rest/oauth2-credential/callback and test users added if restricted. SMTP auth issues** → set correct server/port/TLS and use an app password when 2FA is enabled. Empty LLM output** → verify OpenAI key/quota and inspect node logs. 🧾 Example Outputs 1) Classification (single video) { "videoId": "abc123XYZ", "title": "How to Ship an n8n Workflow with OpenAI", "likeCount": 1587, "classification": "viral", "needsStatsFetch": false } 2) LinkedIn draft (viral) Did you know how much faster prompt workflows get with structured inputs? • Setup: n8n + YouTube API + OpenAI for auto-briefs • Tip: include part=statistics for reliable like counts Useful for teams tracking trending how-to content. What’s your best “viral” signal besides likes? #n8n #YouTubeAPI #OpenAI #Automation #Growth 3) Plain‑text email preview Subject: Weekly AI Briefing — YouTube Trend Highlights Hi team, Highlights from our tracked channels: • Viral: “How to Ship an n8n Workflow with OpenAI” (1.6k likes) • Normal: “RSS vs API: What’s Best for Monitoring?” Generated via n8n + GPT‑4. ✅ Submission Checklist (meets the guidelines) Title clarity:* Mentions *GPT‑4* and *Gmail** Language:* Entire document in *English** Node naming:** Descriptive, non‑generic labels HTML → Markdown:* No HTML in this description; badges are *Markdown images** Examples:** Included (JSON, LinkedIn draft, email) Security:** No secrets in JSON; uses credentials by name 📸 Suggested Screenshots (optional) Full canvas overview (entire workflow) LLM output (expanded) showing generated summary Send‑node result with messageId/status Optional: aggregated briefing preview 📜 License & Support License: MIT Support/Contact: kaihoelters@yahoo.de. An n8n automation workflow template by Kai Hölters.

By Vigh Sandor

SETUP INSTRUCTIONS 1. Configure Kubeconfig Open the "Kubeconfig Setup" node Paste your entire kubeconfig file content into the kubeconfigContent variable Set your target namespace in the namespace variable (default: 'production') Example kubeconfig format: apiVersion: v1 kind: Config clusters: cluster: certificate-authority-data: LS0tLS1CRUd... server: https://your-cluster.example.com:6443 name: your-cluster contexts: context: cluster: your-cluster user: your-user name: your-context current-context: your-context users: name: your-user user: token: eyJhbGciOiJSUzI1... 2. Telegram Configuration Create a Telegram bot via @BotFather Get your bot token and add it as a credential in n8n (Telegram API) Find your chat ID: Message your bot Visit: https://api.telegram.org/bot<YourBotToken>/getUpdates Look for "chat":{"id":...} Open the "Send Telegram Alert" node Replace YOUR_TELEGRAM_CHAT_ID with your actual chat ID Select your Telegram API credential 3. Schedule Configuration Open the "Schedule Trigger" node Default: runs every 1 minute Adjust the interval based on your monitoring needs: Every 5 minutes: Change field to minutes and set minutesInterval to 5 Every hour: Change field to hours and set hoursInterval to 1 Cron expression: Use custom cron schedule 4. kubectl Installation The workflow automatically downloads kubectl (v1.34.0) during execution No pre-installation required on the n8n host kubectl is downloaded and used temporarily for each execution HOW IT WORKS Workflow Steps Schedule Trigger Runs automatically based on configured interval Initiates the monitoring cycle Kubeconfig Setup Loads the kubeconfig and namespace configuration Passes credentials to kubectl commands Parallel Data Collection Get Pods: Fetches all pods from the specified namespace Get Deployments: Fetches all deployments from the specified namespace Both commands run in parallel for efficiency Process & Generate Report Parses pod and deployment data Groups pods by their owner (Deployment, DaemonSet, StatefulSet, or Node) Calculates readiness statistics for each workload Detects alerts: workloads with 0 ready pods Generates a comprehensive Markdown report including: Deployments with replica counts and pod details Other workloads (DaemonSets, StatefulSets, Static Pods) Standalone pods (if any) Pod-level details: status, node, restart count Has Alerts? Checks if any workloads have 0 ready pods Routes to appropriate action Send Telegram Alert (if alerts exist) Sends formatted alert message to Telegram Includes: Namespace information List of problematic workloads Full status report Save Report Saves the Markdown report to a file Filename format: k8s-report-YYYY-MM-DD-HHmmss.md Always executes, regardless of alert status Security Features Temporary kubectl**: Downloaded and used only during execution Temporary kubeconfig**: Written to /tmp/kubeconfig-<random>.yaml Automatic cleanup**: Kubeconfig file is deleted after each kubectl command No persistent credentials**: Nothing stored on disk between executions Alert Logic Alerts are triggered when any workload has zero ready pods: Deployments with readyReplicas < 1 DaemonSets with numberReady < 1 StatefulSets with readyReplicas < 1 Static Pods (Node-owned) with no ready instances Report Sections Deployments: All Deployment-managed pods (via ReplicaSets) Other Workloads: DaemonSets, StatefulSets, and Static Pods (kube-system components) Standalone Pods: Pods without recognized owners (rare) Alerts: Summary of workloads requiring attention KEY FEATURES Automatic kubectl management** - No pre-installation needed Multi-workload support** - Deployments, DaemonSets, StatefulSets, Static Pods Smart pod grouping** - Uses Kubernetes ownerReferences Conditional alerting** - Only notifies when issues detected Detailed reporting** - Pod-level status, node placement, restart counts Secure credential handling** - Temporary files, automatic cleanup Markdown format** - Easy to read and store TROUBLESHOOTING Issue: "Cannot read properties of undefined" Ensure both "Get Pods" and "Get Deployments" nodes execute successfully Check that kubectl can access your cluster with the provided kubeconfig Issue: No alerts when there should be Verify the namespace contains deployments or workloads Check that pods are actually not ready (use kubectl get pods -n <namespace>) Issue: Telegram message not sent Verify Telegram API credential is configured correctly Confirm chat ID is correct and the bot has permission to message you Check that the bot was started (send /start to the bot) Issue: kubectl download fails Check internet connectivity from n8n host Verify access to dl.k8s.io domain Consider pre-installing kubectl on the host and removing the download commands CUSTOMIZATION Change Alert Threshold Edit the Process & Generate Report node to change when alerts trigger: // Change from "< 1" to your desired threshold if (readyReplicas < 2) { // Alert if less than 2 ready pods alerts.push({...}); } Monitor Multiple Namespaces Duplicate the workflow for each namespace Or modify "Kubeconfig Setup" to loop through multiple namespaces Custom Report Format Edit the markdown generation in Process & Generate Report node to customize: Section order Information displayed Formatting style Additional Notification Channels Add nodes after "Has Alerts?" to send notifications via: Email (SMTP node) Slack (Slack node) Discord (Discord node) Webhook (HTTP Request node). An n8n automation workflow template by Vigh Sandor.

By automedia

Monitor RSS Feeds, Extract Full Articles, and Save to Supabase Overview This workflow solves a common problem with RSS feeds: they often only provide a short summary or snippet of the full article. This template automatically monitors a list of your favorite blog RSS feeds, filters for new content, visits the article page to extract the entire blog post, and then saves the structured data into a Supabase database. It's designed for content creators, marketers, researchers, and anyone who needs to build a personal knowledge base, conduct competitive analysis, or power a content aggregation system without manual copy-pasting. Use Cases Content Curation: Automatically gather full-text articles for a newsletter or social media content. Personal Knowledge Base: Create a searchable archive of articles from experts in your field. Competitive Analysis: Track what competitors are publishing without visiting their blogs every day. AI Model Training: Collect a clean, structured dataset of full-text articles to fine-tune an AI model. How It Works Scheduled Trigger: The workflow runs automatically on a set schedule (default is once per day). Fetch RSS Feeds: It takes a list of RSS feed URLs you provide in the "blogs to track" node. Filter for New Posts: It checks the publication date of each article and only continues if the article is newer than a specified age (e.g., published within the last 60 days). Extract Full Content: For each new article, the workflow uses the Jina AI Reader URL (https://r.jina.ai/)) to scrape the full, clean text from the blog post's webpage. This is a free and powerful way to get past the RSS snippet limit. Save to Supabase: Finally, it organizes the extracted data and saves it to your chosen Supabase table. The following data is saved by default: title source_url (the link to the original article) content_snippet (the full extracted article text) published_date creator (the author) status (a static value you can set, e.g., "new") content_type (a static value you can set, e.g., "blog") Setup Instructions You can get this template running in about 10-15 minutes. Set Up Your RSS Feed List: Navigate to the "blogs to track" Set node. In the source_identifier field, replace the example URLs with the RSS feed URLs for the blogs you want to monitor. You can add as many as you like. Tip: The best way to find a site's RSS feed is to use a tool like Perplexity or a web-browsing enabled LLM. // Example list of RSS feeds ['https://blog.n8n.io/rss', 'https://zapier.com/blog/feeds/latest/'] Configure the Content Age Filter: Go to the "max\_content\_age\_days" Set node. Change the value from the default 60 to your desired timeframe (e.g., 7 to only get articles from the last week). Connect Your Storage Destination: The template uses the "Save Blog Data to Database" Supabase node. First, ensure you have a table in your Supabase project with columns to match the data (e.g., title, source_url, content_snippet, published_date, creator, etc.). In the n8n node, create new credentials using your Supabase Project URL and Service Role Key. Select your table from the list and map the data fields from the workflow to your table columns. Want to use something else? You can easily replace the Supabase node with a Google Sheets, Airtable, or the built-in n8n Table node. Just drag the final connection to your new node and configure the field mapping. Set Your Schedule: Click on the first node, "Schedule Trigger". Adjust the trigger interval to your needs. The default is every day at noon. Activate Workflow: Click the "Save" button, then toggle the workflow to Active. You're all set\!. An n8n automation workflow template by automedia.

By automedia

Automated Blog Monitoring System with RSS Feeds and Time-Based Filtering Overview This workflow provides a powerful yet simple foundation for monitoring blogs using RSS feeds. It automatically fetches articles from a list of your favorite blogs and filters them based on their publication date, separating new content from old. It is the perfect starting point for anyone looking to build a custom content aggregation or notification system without needing any API keys. This template is designed for developers, hobbyists, and marketers who want a reliable way to track new blog posts and then decide what to do with them. Instead of including a specific final step, this workflow intentionally ends with a filter, giving you complete freedom to add your own integrations. Use Cases Why would you need to monitor and filter blog posts? Build a Custom News Feed: Send new articles that match your interests directly to a Discord channel, Slack, or Telegram chat. Power a Newsletter: Automatically collect links and summaries from industry blogs to curate your weekly newsletter content. Create a Social Media Queue: Add new, relevant blog posts to a content calendar or social media scheduling tool like Buffer or Hootsuite. Archive Content: Save new articles to a personal database like Airtable, Notion, or Google Sheets to build a searchable knowledge base. How It Works Manual Trigger: The workflow starts when you click "Execute Workflow". You can easily swap this for a Schedule Trigger to run it automatically. Fetch RSS Feeds: It reads a list of RSS feed URLs that you provide in the "blogs to track" node. Process Each Feed: The workflow loops through each RSS feed individually. Filter by Date: It checks the publication date of every article and compares it to a timeframe you set (default is 60 days). Split New from Old: New articles are sent down the true path of the "Filter Out Old Blogs" node. Old articles are sent down the false path. This workflow leaves the true path empty so you can add your desired next steps. Setup and Customization This workflow requires minimal setup and is designed for easy customization. Add Your Blog Feeds: Find the "blogs to track" node. In the source_identifier field, replace the example URLs with the RSS feeds you want to monitor. // Add your target RSS feed URLs in this array ['https://blog.n8n.io/rss', 'https://zapier.com/blog/feeds/latest/'] Set the Time Filter: Go to the "max\_content\_age\_days" node. Change the value from the default 60 to your desired number of days. For example, use 7 to only get articles published in the last week. Customize Your Output (Required Next Step): This is the most important part\! Drag a new node and connect it to the true output of the "Filter Out Old Blogs" node. Example Idea: To save new articles to a Google Sheet, add a Split In Batches node followed by a Google Sheets node to append each new article as a new row. An n8n automation workflow template by automedia.

By Pawan

Who's it for? This template is perfect for educational institutions, coaching centers (like UPSC, GMAT, or specialized technical training), internal corporate knowledge bases, and SaaS companies that need to provide instant, accurate, and source-grounded answers based on proprietary documents. It's designed for users who want to leverage Google Gemini's powerful reasoning but ensure its answers are strictly factual and based only on their verified knowledge repository. How it works / What it does This workflow establishes a Retrieval-Augmented Generation (RAG) pipeline to build a secure, fact-based AI Agent. It operates in two main phases: 1. Knowledge Ingestion: When a new document (e.g., a PDF, lecture notes, or policy manual) is uploaded via a form or Google Drive, the Embeddings Google Gemini node converts the content into numerical vectors. These vectors are then stored in a secure MongoDB Atlas Vector Store, creating a private knowledge base. 2. AI Query & Response: A user asks a question via Telegram. The AI Agent uses the question to perform a semantic search on the MongoDB Vector Store, retrieving the most relevant, source-specific passages. It then feeds this retrieved context to the Google Gemini Chat Model to generate a precise, factual answer, which is sent back to the user on Telegram. This process ensures the agent never "hallucinates" or uses general internet knowledge, making the responses accurate and trustworthy. Requirements To use this template, you will need the following accounts and credentials: n8n Account Google Gemini API Key: For generating vector embeddings and powering the AI Agent. MongoDB Atlas Cluster: A free-tier cluster is sufficient, configured with a Vector Search index. Telegram Bot: A bot created via BotFather and a Chat ID where the bot will listen for and send messages. Google Drive Credentials (if using the Google Drive ingestion path). How to set up Set up MongoDB Atlas:** Create a free cluster and a database. Create a Vector Search Index on your collection to enable efficient searching. Configure Ingestion Path:** Set up the Webhook trigger for your "On form submission" or connect your Google Drive credentials. Configure the Embeddings Google Gemini node with your API Key. Connect the MongoDB Atlas Vector Store node with your database credentials, collection name, and index name. Configure Chat Path:** Set up the Telegram Trigger with your Bot Token to listen for incoming messages. Configure the Google Gemini Chat Model with your API Key. Connect the MongoDB Atlas Vector Store 1 node as a Tool within the AI Agent. Ensure it points to the same vector store as the ingestion path. Final Step:* Configure the Send a text message node with your *Telegram Bot Token and the Chat ID**. How to customize the workflow Change Knowledge Source:** Replace the Google Drive nodes with nodes for Notion, SharePoint, Zendesk, or another document source. Change Chat Platform:** Replace the Telegram nodes with a Slack, Discord, or WhatsApp Cloud trigger and response node. Refine the Agent's Persona:** Open the AI Agent node and edit the System Instruction to give the bot a specific role (e.g., "You are a senior UPSC coach. Answer questions politely and cite sources."). 💡 Example Use Case An UPSC/JEE/NEET coaching uploads NCERT summaries and previous year notes to Google Drive. Students ask questions in the Telegram group — the bot instantly replies with contextually accurate answers from the uploaded materials. The same agent can generate daily quizzes or concise notes from this curated content automatically. An n8n automation workflow template by Pawan.

By Dart

Automatically turn incoming support emails into categorized, prioritized tasks in Dart—complete with AI-generated summaries, tags, and sender context. What It Does This workflow captures emails from Gmail, uses an AI model to classify them into one of seven categories (e.g., Bug Report, Billing, Feature Request), and creates a structured task in Dart. Each task includes: Title**: The email subject Tag**: Based on the detected category Priority**: Set by the AI based on content analysis Description**: Includes confidence level, rationale, summary, and the cleaned full email body Comment**: Automatically adds the sender’s name and email for easy reference The workflow also parses and cleans the raw HTML email content, ensuring all data is readable and workflow-ready. Who's It For This template is built for support and operations teams using Dart who want to streamline how incoming emails are sorted and turned into actionable tasks. It’s ideal for organizations managing multiple types of requests and updates from clients, partners, or systems. How to Set Up Import the workflow into n8n Connect your Gmail and Dart accounts Replace the dummy Dartboard ID with your actual board ID Choose your preferred AI model (results may vary depending on model quality) If your target email address is in a google group, use the Filter: "Sender" in the Gmail trigger Requirements n8n account Connected Gmail and Dart account How to Customize the Workflow Modify the category list to match your team’s taxonomy Adjust the AI classification prompt to fine-tune tagging and prioritization Choose your preferred AI model. An n8n automation workflow template by Dart.

By s3110

Who’s it for Traders, operations teams, and finance-minded founders who want a low-maintenance USD/JPY monitor that blends live pricing with short, news-aware AI commentary—delivered straight to email on a reliable cadence. How it works / What it does On a fixed schedule (every 4 hours), the workflow fetches the latest USD→JPY spot rate, enriches it with recent market context via a search tool, and asks an AI agent to produce a concise, structured take (trend, key drivers, and a buy/sell/neutral stance with rationale). The final summary is sent by email so stakeholders can skim, log, or forward without opening n8n. The design favors clarity (renamed nodes, sticky notes) and safety (no hardcoded secrets). How to set up Open Set (Fields) — Configure me and enter your Tavily API key and notification email. In Send results via Gmail, attach your email credential (or swap to SMTP/another provider). (Optional) Point LLM provider (configure) to your preferred model/vendor. Enable the schedule or adjust the interval to match your cadence. Requirements Tavily (or compatible) Search API key Email credential in n8n (Gmail or SMTP) An n8n instance with internet access How to customize the workflow Change the schedule frequency or trading window. Swap the rate source, add indicators (MA/RSI), or log to Sheets/DB. Extend the AI prompt and output schema for risk flags or position sizing. Add Slack/Telegram delivery or dashboards for team visibility. Disclaimer (community nodes) If you use community/experimental nodes, publish as self-hosted only and include a static workflow image at the top of your listing. An n8n automation workflow template by s3110.

By Roshan Ramani

Generate Personalized & Aggregate Survey Reports with Jotform and Gemini AI Overview Automatically transform Jotform survey responses into intelligent, professional reports. This workflow generates personalized insights for each respondent and statistical summaries for administrator, all hands-free. Who Should Use This Survey managers needing automated report generation Market researchers analyzing response data Product teams collecting customer feedback Organizations using Jotform without built-in analytics What It Does Two-Part Report System: Personal Reports (Instant) Triggers immediately when respondent submits survey AI analyzes their individual responses using Google Gemini Generates customized insights and recommendations Sends professional HTML report to respondent's email Weekly Aggregate Reports (Scheduled) Runs automatically every week Collects all survey submissions Calculates statistics, percentages, and trends Identifies patterns across all respondents Sends comprehensive analysis to admin Key Features ✓ Real-time personal report generation ✓ Intelligent AI-powered analysis (Google Gemini) ✓ Professional HTML email formatting ✓ Automatic weekly summaries ✓ Statistical analysis and trend identification ✓ Zero manual processing required ✓ Fully customizable prompts and styling ✓ Works with any Jotform survey structure Setup Requirements Jotform** account with active survey form Get Jotform from here n8n** instance (cloud or self-hosted) Google Gemini API** key Gmail** account (for sending reports) Jotform API** key What You Get in Reports Personal Reports Include: Respondent Profile** – Auto-extracted demographics (age, role, location, email) Key Insights** – 3-4 AI-generated insights specific to their responses Personalized Recommendations** – 3-4 actionable suggestions based on their answers Professional Formatting** – HTML-styled email with your branding colors Mobile Responsive** – Looks great on all devices Fully Customizable: Edit the AI prompt to generate different types of insights Change HTML styling (colors, fonts, layout) Add/remove sections (logos, footers, additional analysis) Adjust the tone (professional, casual, technical, etc.) Include custom branding and messaging Aggregate Reports Include: Total Respondents Count** – How many submissions in the period Demographic Breakdown** – Distribution of respondent profiles Response Statistics** – Percentages and frequencies for each question Answer Distribution** – Most popular choices across all responses Trend Analysis** – Patterns and correlations in the data Key Findings** – Top 5-7 insights from all responses combined Statistical Metrics** – Averages, frequencies, comparisons Fully Customizable: Choose which statistics to calculate and display Change how data is visualized and presented Customize report styling and branding Adjust analysis depth and metrics focus Add custom sections for your specific needs Modify HTML layout and design How Reports Look Personal Report Structure (Email): Header: Professional gradient background with thank you message Section 1: Respondent Details (extracted from survey) Section 2: Key Insights (AI-generated from their responses) Section 3: Recommendations (personalized suggestions) Footer: Thank you message and company info Aggregate Report Structure (Email): Header: Report title and date range Section 1: Total respondent count and demographics Section 2: Question-by-question response breakdown Section 3: Statistical analysis and trends Section 4: Key findings and patterns discovered Section 5: Actionable insights for decision-makers Footer: Next report date and company branding Quick Start Get your Jotform Form ID and API key Enable Google Gemini API and create API key Set up Gmail OAuth2 credentials in n8n Import this workflow Add your credentials to the nodes Test with a sample survey submission Complete setup instructions are included in the workflow as an expandable sticky note. Workflow Logic PERSONAL REPORTS: Survey Submission ↓ Collect Response Data ↓ AI Analysis & Insights Generation ↓ Create Styled HTML Report ↓ Send to Respondent Email AGGREGATE REPORTS: Weekly Schedule Triggers ↓ Fetch All Submissions ↓ Statistical Analysis & Trend Detection ↓ Generate Insights from All Data ↓ Create Summary HTML Report ↓ Send to Admin Email Use Cases Customer Feedback Surveys** – Analyze responses, send personalized insights Product Research** – Track trends across respondents weekly Market Research** – Automated statistical reporting Employee Surveys** – Personalized feedback + company trends Event Feedback** – Instant attendee insights + organizer summary Customer Satisfaction (NPS)** – Personalized follow-ups + trend analysis Lead Qualification** – Auto-analyze prospect responses and route accordingly. An n8n automation workflow template by Roshan Ramani.

By KlickTipp

Community Node Disclaimer: This workflow uses KlickTipp community nodes. Introduction This workflow monitors orders and customers in Adobe Commerce, automatically creating or updating contacts in KlickTipp, enriching profiles for segmentation and automated messaging. Tags are applied dynamically: high-value orders (≥100) receive a "Premium Customer" tag, and purchases with certain SKUs (e.g., clothing) are assigned product-based tags. Perfect for e-commerce businesses, online retailers, and digital shops that want to eliminate manual data entry and ensure every buyer and customer receives the right messages. Setup Instructions KlickTipp Preparation Prepare custom fields Payment ID Total Receipt URL Products Prepare tags: Premium customer Clothing buyer Credential Configuration Connect your Magento account using an Access Token/Base URL from the Magento Admin Dashboard (System → Extensions → Integrations). Authenticate your KlickTipp connection with username/password credentials (API access required). Customization Trigger options:* If your Commerce edition supports *webhooks, you can replace polling with a **Webhook trigger. Cadence & overlap:** 1–30 min are typical; a 1–2 min overlap in the filter to avoid gaps. Routing variants:** Change the SKU list, switch to category checks, or add more value tiers. An n8n automation workflow template by KlickTipp.

By Roshan Ramani

AI Powered All Purpose Appointment System via JotForm What This Workflow Does This template automates the entire appointment request lifecycle using AI. When someone submits an appointment request through JotForm, the system automatically sends details for approval, generates personalized confirmation or rejection emails using OpenAI, and maintains records—all without manual intervention. 👉 Get JotForm here Whether you're running a clinic, consulting business, training center, or any service-based operation, this workflow eliminates repetitive email writing and ensures consistent, professional communication. It's fully customizable to work with any appointment form structure. Who's It For Service providers (consultants, trainers, coaches) Healthcare professionals Educational institutions Salon and wellness businesses Event coordinators Any business handling appointment requests at scale How It Works Form Submission – Appointment request arrives via JotForm Data Extraction – System pulls name, email, phone, date, time, and visit type Approval Request – Details are sent to Telegram for review and approval AI Email Generation – OpenAI creates personalized confirmation or rejection email based on approval status Smart Routing – If approved: records in Google Sheets and sends confirmation. If rejected: removes from system and sends reschedule notice Automated Follow-up – Requester receives professional email instantly Getting Started (Quick Setup) Step 1: Choose Your JotForm Select any existing appointment form or create a new one in JotForm The workflow works with any form structure Step 2: Map Your Form Fields Identify the field names in your JotForm (name, email, phone, appointment date, time, etc.) Update the "Parse: Extract Appointment Details" node with your exact field names This ensures the workflow reads data correctly from your specific form Step 3: Follow Full Setup Steps Connect JotForm – Copy the Form ID and API Key Configure Google Sheets – Create a sheet for appointment records and copy the spreadsheet ID Setup Telegram – Create a bot via BotFather for approval notifications Add OpenAI Credentials – Generate an API key at platform.openai.com Authorize Gmail – Enable Gmail API in Google Cloud Console Why This Is Customizable The workflow is built to be flexible from the start. Whether your form collects appointment type, service category, special requests, or any other field, you can easily map those fields into the flow. Just identify what data your form collects and tell the workflow where to find it. Requirements JotForm account with an appointment form Google Sheets for record keeping Telegram account and bot (for approvals) OpenAI API key (paid account recommended) Gmail account for sending emails n8n instance (self-hosted or cloud) How to Customize Change Approval Channel** – Replace Telegram with Slack, Discord, or email by swapping the notification node Modify Email Templates** – Edit the AI prompt in "Generate: Appointment Response Email" to match your tone and branding Add More Fields** – Update the Set node to capture additional information from your JotForm like appointment type, service category, or special requests Adjust Routing Logic** – Modify the conditional node to add approval stages or auto-confirm certain appointment types Connect CRM** – Add steps to automatically create contacts in HubSpot, Pipedrive, or Salesforce Enable Reminders** – Use Gmail or SMS nodes to send appointment reminders 24 hours before scheduled time Extend Data Collection** – Map any custom fields from your JotForm by updating the extraction node to include them. An n8n automation workflow template by Roshan Ramani.

By Roshan Ramani

Smart Lead Qualification for JotForm Contact Forms Automatically classify and manage contact form submissions using AI-powered lead scoring. This workflow analyzes JotForm submissions in real-time, categorizes them as hot leads, cold leads, or spam, and takes intelligent actions—sending Telegram notifications for hot leads, ignoring irrelevant inquiries, and automatically deleting spam. Who's It For This template is perfect for: Businesses receiving high volumes of contact form submissions** who need to prioritize responses Marketing and sales teams** wanting to focus on qualified leads immediately Agencies and consultants** offering AI/automation services who want to filter out noise Anyone struggling with spam** or low-quality form submissions What It Does The workflow uses Google Gemini AI to intelligently classify each JotForm submission into three categories: Hot Lead (1)**: Genuine inquiries about your services, collaboration requests, or project proposals → Sends Telegram notification + Flags in JotForm Cold Lead (0)**: Legitimate but irrelevant inquiries (job applications, unrelated business queries) → No action taken Garbage/Spam (2)**: Test submissions, bots, gibberish, or fake data → Automatically deleted from JotForm How It Works JotForm trigger captures new contact form submissions Submission data is extracted and formatted Google Gemini AI analyzes the content and classifies the lead A switch routes the submission based on classification: Hot leads trigger Telegram notifications and get flagged Cold leads are ignored Spam submissions are automatically deleted Requirements n8n instance** (cloud or self-hosted) JotForm account** with a contact form (Get JotForm here) Google Gemini API key** (free tier available) Telegram account** for notifications How to Set Up 📋 Detailed setup instructions are included inside the workflow in sticky notes. Quick setup overview: Create your contact form in JotForm using the "Contact Form with Fancy Header and Footer" template Get your JotForm API key and form ID Obtain a Google Gemini API key from Google AI Studio Create a Telegram bot via @BotFather and get your chat ID Configure all credentials in the respective nodes Update the HTTP request nodes with your JotForm API key Test the workflow with sample submissions The workflow includes comprehensive sticky notes with step-by-step instructions, including how to get your Telegram chat ID and configure all integrations. How to Customize Adjust classification criteria**: Modify the AI Agent's system prompt to match your business type and lead qualification criteria Change notification format**: Edit the Telegram message template to include/exclude specific fields Add more actions**: Extend hot lead handling with additional nodes (e.g., add to CRM, send email, create task) Modify form fields**: Update field references if your JotForm uses different field names Multi-channel notifications**: Add Slack, Discord, or email notifications alongside Telegram Note All API keys and credentials shown in the workflow are placeholders. You'll need to replace them with your own credentials during setup. An n8n automation workflow template by Roshan Ramani.

By Jay Emp0

Automatically turns trending Reddit posts into punchy, first-person tweets powered by Google Gemini AI, Reddit, and Twitter API, with Google Sheets logging. 🧩 Overview This workflow repurposes Reddit content into original tweets every few hours. It’s perfect for creators, marketers, or founders who want to automate content inspiration while keeping tweets sounding human, edgy, and fresh. Core automation loop: Fetch trending Reddit posts from selected subreddits. Use Gemini AI to write a short, first-person tweet. Check your Google Sheet to avoid reusing the same Reddit post. Publish to Twitter automatically. Log tweet + Reddit reference in Google Sheets. 🧠 Workflow Diagram 🪄 How It Works 1️⃣ Every 2 hours → the workflow triggers automatically. 2️⃣ It picks a subreddit (like r/automation, r/n8n, r/SaaS). 3️⃣ Gemini AI analyzes a rising Reddit post and writes a fresh, short tweet. 4️⃣ The system checks your Google Sheet to ensure it hasn’t used that Reddit post before. 5️⃣ Once validated, the tweet is published via Twitter API and logged. 🧠 Example Tweet Output 📊 Logged Data (Google Sheets) Each tweet is automatically logged for version control and duplication checks. | Date | Subreddit | Post ID | Tweet Text | |------|------------|----------|-------------| | 08/10/2025 | n8n_ai_agents | 1o16ome | Just saw a wild n8n workflow on Reddit... | ⚙️ Key Components | Node | Function | |------|-----------| | Schedule Trigger | Runs every 2 hours to generate a new tweet. | | Code (Randomly Decide Subreddit) | Picks one subreddit randomly from your preset list. | | Gemini Chat Model | Generates tweet text in first person tone using custom prompt rules. | | Reddit Tool | Fetches top or rising posts from the chosen subreddit. | | Google Sheets (read database) | Keeps a record of already-used Reddit posts. | | Structured Output Parser | Ensures consistent tweet formatting (tweet text, subreddit, post ID). | | Twitter Node | Publishes the AI-generated tweet. | | Append Row in Sheet | Logs the tweet with date, subreddit, and post ID. | 🧩 Setup Tutorial 1️⃣ Prerequisites | Tool | Purpose | |------|----------| | n8n Cloud or Self-Host | Workflow execution | | Google Gemini API Key | For tweet generation | | Reddit OAuth2 API | To fetch posts | | Twitter (X) API OAuth2 | To publish tweets | | Google Sheets API | For logging and duplication tracking | 2️⃣ Import the Workflow Download Reddit Twitter Automation.json. In n8n, click Import Workflow → From File. Connect your credentials: Gemini → Gemini Reddit → Reddit account Twitter → X Google Sheets → Gsheet 3️⃣ Configure Google Sheet Your sheet must include these columns: | Column | Description | |--------|--------------| | PAST TWEETS | The tweet text | | Date | Auto-generated date | | subreddit | Reddit source | | post_id | Reddit post reference | 4️⃣ Customize Subreddits In the Code Node, update this array to choose which subreddits to monitor: const subreddits = [ "n8n", "microsaas", "SaaS", "automation", "n8n_ai_agents" ];. An n8n automation workflow template by Jay Emp0.

By Jay Emp0

🤖 Reddit Auto-Comment Assistant (AI-Driven Marketing Workflow) Automate how you reply to Reddit posts using AI-generated, first-person comments that sound human, follow subreddit rules, and (optionally) promote your own links or products. 🧩 Overview This workflow monitors Reddit mentions (via F5Bot Gmail alerts) and automatically: Fetches the relevant Reddit post. Checks the subreddit’s rules for self-promotion. Generates a comment using GPT-5 style prompting (human-like tone, <255 chars). Optionally promotes your chosen product from Google Sheets. Posts the comment automatically It’s ideal for creators, marketers, or founders who want to grow awareness organically and authentically on Reddit — without sounding like a bot. 🧠 Workflow Diagram 🚀 Key Features | Feature | Description | |----------|--------------| | AI-Generated Reddit Replies | Uses GPT-powered reasoning and prompt structure that mimics a senior marketing pro typing casually. | | Rule-Aware Posting | Reads subreddit rules and adapts tone — no promo where it’s not allowed. | | Product Integration | Pulls product name + URL from your Google Sheet automatically. | | Full Automation Loop | From Gmail → Gsheet → Reddit | | Evaluation Metrics | Logs tool usage, link presence, and formatting to ensure output quality. | 🧰 Setup Guide 1️⃣ Prerequisites | Tool | Purpose | |------|----------| | n8n Cloud or Self-Host | Workflow automation environment | | OpenAI API key | For comment generation | | Reddit OAuth2 credentials | To post comments | | Google Sheets API | To fetch and evaluate products | | Gmail API | To read F5Bot alerts | 2️⃣ Import the Workflow Download Reddit Assistant.json In n8n, click Import Workflow → From File Paste your credentials in the corresponding nodes: Reddit account Gmail account Gsheet account OpenAI API 3️⃣ Connect Your Google Sheets You’ll need two Google Sheets: | Sheet | Purpose | Example Tab | |--------|----------|-------------| | Product List | Contains all your product names, URLs, goals, and CTAs | promo | | Reddit Evaluations | Logs AI performance metrics and tool usage | reddit evaluations | 4️⃣ Set Up Gmail Trigger (F5Bot) Subscribe to F5Bot alerts for keywords like "blog automation" or your brand name. Configure Gmail Trigger to only pull from sender: admin@f5bot.com. 5️⃣ Configure AI Agent Prompt The built-in prompt follows a GPT-5-style structured reasoning chain: Reads the Reddit post + rules. Determines if promotion is allowed. Fetches product data from Google Sheets. Writes a short, human comment (<255 chars). Avoids buzzwords and fake enthusiasm. 📊 Workflow Evaluations The workflow includes automatic evaluation nodes to track: | Metric | Description | |--------|--------------| | contains link | Checks if comment includes a URL | | contains dash | Detects format breaks | | Tools Used | Logs which AI tools were used in reasoning | | executionTime | Monitors average latency | 💡 Why This Workflow Has Value | Value | Explanation | |--------|--------------| | Saves time | Automates Reddit marketing without manual engagement. | | Feels human | AI comments use a fast-typing, casual tone (e.g., “u,” “ur,” “idk”). | | Follows rules | Respects subreddits where promo is banned. | | Data-driven | Logs performance across 10 test cases for validation. | | Monetizable | Can promote Gumroad, YouTube, or SaaS products safely. | ⚙️ Example Use Case > “I used this automation to pull $1.4k by replying to Reddit posts about blog automation. > Each comment felt natural and directed users to my n8n workflow.”. An n8n automation workflow template by Jay Emp0.

By Barbora Svobodova

Sora 2 Video Generation: Prompt-to-Video Automation with OpenAI API Who’s it for This template is ideal for content creators, marketers, developers, or anyone needing automated AI video creation from text prompts. Perfect for bulk generation, marketing assets, or rapid prototyping using OpenAI's Sora 2 API. Example use cases: E-commerce sellers creating product showcase videos for multiple items without hiring videographers or renting studios Social media managers generating daily content like travel vlogs, lifestyle videos, or brand stories from simple text descriptions Marketing teams producing promotional videos for campaigns, events, or product launches in minutes instead of days How it works / What it does Submit a text prompt using a form or input node. Workflow sends your prompt to the Sora 2 API endpoint to start video generation. It polls the API to check if the video is still processing or completed. When ready, it retrieves the finished video's download link and automatically saves the file. All actions—prompt submission, status checks, and video retrieval—run without manual oversight. How to set up Use your existing OpenAI API key or create a new one at https://platform.openai.com/api-keys Replace Your_API_Key in the following nodes with your OpenAI API key: Sora 2Video, Get Video, Download Video Adjust the Wait node for Video node intervals if needed — video generation typically takes several minutes Enter your video prompt into the Text Prompt trigger form to start the workflow Requirements OpenAI account & OpenAI API key n8n instance (cloud or self-hosted) A form, webhook, or manual trigger for prompt submission How to customize the workflow Connect the prompt input to external forms, bots, or databases. Add post-processing steps like uploading videos to cloud storage or social platforms. Adjust polling intervals for efficient status checking. Limitations and Usage Tips Prompt Clarity: For optimal video generation results, ensure that prompts are clear, concise, and well-structured. Avoid ambiguity and overly complex language to improve AI interpretation. Processing Duration: Video creation may take several minutes depending on prompt complexity and system load. Users should anticipate this delay and design workflows accordingly. Polling Interval Configuration: Adjust polling intervals thoughtfully to balance prompt responsiveness with API rate limits, optimizing both performance and resource usage. API Dependency: This workflow relies on the availability and quota limits of OpenAI’s Sora 2 API. Users should monitor their API usage to avoid interruptions and service constraints. An n8n automation workflow template by Barbora Svobodova.

By Fabian Perez

This workflow automates the process of scraping, analyzing, and storing real estate data from Zillow using Apify, OpenAI, and Google Sheets. It begins by running an Apify Actor that extracts live property details such as price, location, and key features. The data is then cleaned and processed before being analyzed by an AI model that assigns an investment potential score (1–10). To maintain reliable results, the AI only scores properties that include all required fields — for example, listings missing price or description data are automatically skipped. This ensures that only complete and accurate information is evaluated. Finally, all valid results are appended or updated in a Google Sheet, creating a central, always-up-to-date property database for future analysis. Ideal for real estate investors, analysts, and data-driven agencies, this template provides a fully automated loop for property collection, evaluation, and reporting — all in one flow. Tools used: Apify, OpenAI, Google Sheets, n8n. An n8n automation workflow template by Fabian Perez.

By Maxim Osipovs

This n8n workflow template implements a dual-path architecture for AI customer support, based on the principles outlined in the research paper "A Locally Executable AI System for Improving Preoperative Patient Communication: A Multi-Domain Clinical Evaluation" (Sato et al.). The system, named LENOHA (Low Energy, No Hallucination, Leave No One Behind Architecture), uses a high-precision classifier to differentiate between high-stakes queries and casual conversation. Queries matching a known FAQ are answered with a pre-approved, verbatim response, structurally eliminating hallucination risk. All other queries are routed to a standard generative LLM for conversational flexibility. This template provides a practical ++blueprint++ for building safer, more reliable, and cost-efficient AI agents, particularly in regulated or high-stakes domains where factual accuracy is critical. What This Template Does (Step-by-Step) Loads an expert-curated FAQ from Google Sheets and creates a searchable vector store from the questions during a one-time setup flow. Receives incoming user queries in real-time via a chat trigger. Classifies user intent by converting the query to an embedding and searching the vector store for the most semantically similar FAQ question. Routes the query down one of two paths based on a configurable similarity score threshold. Responds with a verbatim, pre-approved answer if a match is found (safe path), or generates a conversational reply via an LLM if no match is found (casual path). Important Note for Production Use This template uses an in-memory Simple Vector Store for demonstration purposes. For a production application, this should be replaced with a persistent vector database (e.g., Pinecone, Chroma, Weaviate, Supabase) to store your embeddings permanently. Required Integrations: Google Sheets (for the FAQ knowledge base) Hugging Face API (for creating embeddings) An LLM provider (e.g., OpenAI, Anthropic, Mistral) (Recommended) A persistent Vector Store integration. Best For: 🏦 Organizations in regulated industries (finance, healthcare) requiring high accuracy. 💰 Applications where reducing LLM operational costs is a priority. ⚙️ Technical support agents that must provide precise, unchanging information. 🔒 Systems where auditability and deterministic responses for known issues are required. Key Benefits: ✅ Structurally eliminates hallucination risk for known topics. ✅ Reduces reliance on expensive generative models for common queries. ✅ Ensures deterministic, accurate, and consistent answers for your FAQ. ✅ Provides high-speed classification via vector search. ✅ Implements a research-backed architecture for building safer AI systems. An n8n automation workflow template by Maxim Osipovs.

By Jitesh Dugar

Streamline your manufacturing quality control process with automated inspection tracking, compliance documentation, and real-time alerts. This workflow eliminates manual QC paperwork while ensuring ISO compliance and instant visibility into product quality. 🎯 Use Case Perfect for manufacturing facilities that need to: Document quality inspections for compliance audits Track product defects and non-conformities Generate certificates of compliance automatically Alert teams instantly when products fail inspection Maintain ISO 9001:2015 documentation requirements ✨ Key Features Automated Data Collection Accepts inspection data from web forms (Typeform) or Google Sheets Processes measurements against predefined specifications Calculates PASS/FAIL status automatically Smart Documentation Stores all inspection records in Google Drive Maintains searchable tracking spreadsheet Generates HTML compliance certificates Creates audit-ready documentation trail Real-Time Alerts Instant Slack notifications for failed inspections Detailed non-conformity reporting Escalation to quality managers Daily Analytics Automated daily quality summaries at 8 AM Pass rate calculations and trend analysis Product and inspector performance metrics 🔧 Setup Requirements Google Workspace - For Sheets and Drive storage Slack - For team notifications Jotform (optional) - For web-based inspection forms Email (SMTP) - For sending compliance certificates 📝 Customization Tips Modify specifications in the "Process Inspection Data" node to match your products Add custom fields for industry-specific requirements Adjust alert thresholds and notification channels Extend certificate templates with your company branding 🏭 Industries Ideal for: Electronics, Automotive Parts, Medical Devices, Consumer Goods, Food & Beverage, Aerospace Components 💡 Example Scenario A electronics manufacturer uses this workflow to inspect PCB assemblies. When an inspector submits measurements via Jotform, the workflow automatically checks if dimensions and weight meet specifications, stores the report, and generates a certificate. If any board fails, the quality manager receives an immediate Slack alert with details. Time Saved: ~2 hours daily on documentation and reporting Error Reduction: 90% fewer data entry mistakes Compliance: 100% audit-ready documentation. An n8n automation workflow template by Jitesh Dugar.

By Jitesh Dugar

Transform chaotic training requests into strategic skill development - achieving 100% completion tracking, 30% cost reduction through intelligent planning, and data-driven L&D decisions. What This Workflow Does Revolutionizes corporate training management with AI-driven course recommendations and automated approval workflows: 📝 Training Request Capture - Jotform collects skill gaps, business justification, and training needs 💰 Budget Intelligence - Real-time department budget checking and utilization tracking 🤖 AI Course Recommendations - Matches requests to training catalog with 0-100% scoring 📊 ROI Analysis - AI assesses business impact, urgency, and return on investment ✅ Smart Approval Routing - Auto-approves within budget or routes to manager with AI insights 🎯 Skill Development Paths - Creates personalized learning journeys from current to desired levels 👥 Team Impact Assessment - Identifies knowledge sharing opportunities and additional attendees ⚠️ Risk Analysis - Evaluates delays risks and over-investment concerns 📧 Automated Notifications - Sends detailed approvals to managers and confirmations to employees 📈 Complete Tracking - Logs all requests with AI insights for L&D analytics Key Features AI Training Advisor: GPT-4 analyzes requests across 10+ dimensions including needs assessment, ROI, and implementation planning Course Catalog Matching: AI scores courses 0-100% based on skill level, topic relevance, and outcomes alignment Budget Management: Real-time tracking of department budgets with utilization percentages Preventability Scoring: Identifies skill gaps that could have been addressed earlier Alternative Options: AI suggests cost-effective alternatives (online courses, mentoring, job shadowing) Skill Development Pathways: Maps progression from current to desired skill level with timeframes Team Multiplier Effect: Identifies how training one person benefits entire team Manager Guidance: Provides key considerations, questions to ask, and approval criteria Implementation Planning: Suggests timeline, preparation needed, and post-training actions Success Metrics: Defines measurable outcomes for training effectiveness Risk Assessment: Flags delay risks and over-investment concerns Cost Optimization: Recommends ways to reduce costs while maintaining quality Perfect For Growing Tech Companies: 50-500 employees with high skill development needs Enterprise Organizations: Large corporations managing 1000+ training requests annually Professional Services: Consulting, legal, accounting firms requiring continuous upskilling Healthcare Systems: Medical organizations with compliance and clinical training requirements Manufacturing Companies: Technical skills training for operations and quality teams Sales Organizations: Sales enablement and product training at scale Financial Services: Compliance training and professional certification tracking What You'll Need Required Integrations Jotform - Training request form (free tier works) Create your form for free on Jotform using this link OpenAI API - GPT-4 for AI training analysis (~$0.30-0.60 per request) Gmail - Automated notifications to employees, managers, and HR Google Sheets - Training request database and L&D analytics Quick Start Import Template - Copy JSON and import into n8n Add OpenAI Credentials - Set up OpenAI API key (GPT-4 recommended) Create Jotform Training Request Configure Gmail - Add Gmail OAuth2 credentials Setup Google Sheets: Create spreadsheet with "Training_Requests" sheet Replace YOUR_GOOGLE_SHEET_ID in workflow Columns auto-populate on first submission Customize Training Catalog: Edit "Check Training Budget" node Update training catalog with your actual courses, providers, and costs Add your company's preferred vendors Customization Options Custom Training Catalog: Replace sample catalog with your company's actual training offerings Budget Rules: Adjust approval thresholds (e.g., auto-approve under $500) AI Prompt Tuning: Customize analysis criteria for your industry and culture Multi-Level Approvals: Add VP or director approval for high-cost training Compliance Training: Flag required certifications and regulatory training Vendor Management: Track preferred training vendors and volume discounts Learning Paths: Create role-specific career development tracks Certification Tracking: Monitor professional certifications and renewal dates Training Calendar: Integrate with company calendar for session visibility Waitlist Management: Queue employees when sessions are full Pre/Post Assessments: Add skill testing before and after training Knowledge Sharing: Schedule lunch-and-learns for employees to share learnings Expected Results 100% completion tracking - Digital trail from request to certificate 30% cost reduction - Strategic planning prevents redundant/unnecessary training 95% manager response rate - Automated reminders and clear AI guidance 50% faster approvals - AI pre-analysis speeds manager decisions 40% better course matching - AI recommendations vs manual course selection 60% reduction in budget overruns - Real-time budget visibility 3x increase in skill development velocity - Streamlined process removes friction 85% employee satisfaction - Clear process and fast responses Data-driven L&D strategy - Analytics identify trending skill gaps 25% increase in training ROI - Better targeting and follow-through Use Cases Tech Startup (150 Engineers) Engineer requests "Advanced Kubernetes" training. AI identifies skill gap as "high severity" due to upcoming cloud migration project. Checks department budget ($22K remaining of $50K), recommends $1,800 4-day course with 92% match score. Auto-routes to engineering manager with business impact analysis. Manager approves in 2 hours. Training scheduled for next month. Post-training, engineer leads internal workshop, multiplying impact across 10-person team. Migration completes 3 weeks early, saving $50K. Enterprise Sales Org (500 Reps) Sales rep requests "Negotiation Mastery" after losing 3 deals. AI assesses urgency as "justified" based on revenue impact. Recommends $1,100 2-day course but also suggests lower-cost alternative: internal mentoring from top performer ($0). Manager sees both options, chooses mentoring first. Rep closes next deal with new techniques. Training budget preserved for broader team enablement. ROI: $200K deal closed with $0 training spend. Healthcare System (2,000 Nurses) Nurse requests ACLS recertification. AI flags as "compliance-critical" with "immediate" urgency (expiring in 30 days). Checks budget, finds sufficient funds. Auto-approves and schedules next available session. Sends pre-training materials 1 week before. Tracks attendance, generates certificate upon completion. Updates nurse's credential profile in HRIS. Compliance maintained, no manual intervention needed. Financial Services Firm Analyst requests CFA Level 1 prep course ($2,500). AI assesses as "high ROI" but identifies budget constraint (department at 95% utilization). Recommends deferring to next quarter when new budget allocated. Suggests free Khan Academy courses as interim solution. Manager sees complete analysis, approves deferral, adds analyst to Q2 priority list. Transparent communication maintains morale despite delay. Manufacturing Company Maintenance tech requests PLC programming training. AI identifies 5 other techs with same skill gap. Recommends group training session ($1,200 per person vs $2,000 individual). Calculates team multiplier effect: 6 techs trained = reduced downtime across 3 shifts. Manager approves group session, saving $4,800. All 6 techs complete training together, creating peer support network. Equipment downtime reduced 40%. Pro Tips Quarterly Planning: Use Google Sheets data to identify trending skill gaps and plan group training Budget Forecasting: Track monthly utilization to predict Q4 budget needs Course Ratings: Add post-training feedback to improve AI recommendations over time Internal Experts: Build database of employees who can provide mentoring (free alternative) Learning Paths: Create role-based tracks (e.g., "Junior Dev → Senior Dev" pathway) Compliance Flagging: Auto-identify regulatory/certification requirements Vendor Relationships: Track volume with vendors to negotiate discounts Knowledge Retention: Require post-training presentations to reinforce learning Manager Training: Educate managers on how to evaluate AI recommendations Budget Reallocation: Monthly reviews to move unused budget between departments Early Bird Discounts: AI can suggest booking 60+ days out for savings Continuous Learning: Supplement formal training with Udemy/LinkedIn Learning subscriptions Learning Resources This workflow demonstrates advanced automation: AI Agents with complex analysis across multiple decision dimensions Budget management algorithms with real-time calculations Course recommendation engines with scoring and matching Multi-criteria approval routing based on AI confidence Skill progression modeling from current to desired states ROI analysis balancing cost, impact, and urgency Alternative suggestion algorithms for cost optimization Team impact modeling for knowledge multiplication Risk assessment frameworks for training decisions Real-Time Budget Tracking: Live department budget visibility prevents overspending Audit Trail: Complete history for finance audits and compliance reviews Approval Documentation: Timestamped manager approvals for governance Cost Allocation: Track training costs by department, employee, category ROI Measurement: Compare training investment to business outcomes Compliance Monitoring: Flag required certifications and regulatory training Vendor Management: Track spending with training providers Ready to transform your corporate training? Import this template and turn training chaos into strategic skill development with AI-powered insights and automation! 📚✨ Questions or customization? The workflow includes detailed sticky notes explaining each AI analysis component. An n8n automation workflow template by Jitesh Dugar.

By Jitesh Dugar

Transform chaotic employee departures into secure, insightful offboarding experiences - achieving zero security breaches, 100% equipment recovery, and actionable retention insights from every exit interview. What This Workflow Does Revolutionizes employee offboarding with AI-driven exit interview analysis and automated task orchestration: 📝 Exit Interview Capture - Jotform collects resignation details, ratings, feedback, and equipment inventory 🤖 AI Sentiment Analysis - Advanced AI analyzes exit interviews for retention insights, red flags, and patterns ⚠️ Red Flag Detection - Automatically identifies serious issues (harassment, discrimination, ethics) for immediate escalation 👤 Manager Intelligence - Flags management issues and provides coaching recommendations 🔐 Access Revocation - Schedules automatic system access removal on last working day 📦 Equipment Tracking - Generates personalized equipment return checklist for each employee 📚 Knowledge Transfer - Assesses knowledge transfer risk and creates handover plan 💰 Retention Analytics - Identifies preventable departures and competitive intelligence 📧 Automated Notifications - Sends checklists to employees, action items to managers, IT requests 📊 Boomerang Prediction - Calculates likelihood of rehire and maintains alumni relationships Key Features AI Exit Interview Analysis: GPT-4 provides 2+ analytical dimensions including sentiment, preventability, and red flags Preventability Scoring: AI calculates 0-100% score on whether departure was preventable Red Flag Escalation: Automatic detection of harassment, discrimination, ethics, or legal concerns Manager Performance Insights: Identifies management issues requiring coaching or intervention Sentiment Analysis: Analyzes tone, emotions, and overall sentiment from qualitative feedback Competitive Intelligence: Tracks where employees go and what competitors offer Knowledge Transfer Risk Assessment: Evaluates complexity and criticality of knowledge handover Boomerang Probability: Predicts likelihood (0-100%) of employee returning in future Department Trend Analysis: Identifies systemic issues in specific teams or departments Compensation Benchmarking: Flags compensation competitiveness issues Retention Recommendations: AI-generated actionable improvements prioritized by impact Equipment Tracking: Automatic inventory of laptops, phones, cards, and other company property Perfect For Growing Companies: 50-5,000 employees with monthly turnover requiring structured offboarding Tech Companies: Protecting IP and system access with departing engineers and developers Healthcare Organizations: Compliance-critical offboarding with HIPAA and patient data access Financial Services: Regulated industries requiring audit trails and secure access revocation Professional Services: Knowledge-intensive businesses where brain drain is costly Retail & Hospitality: High-turnover environments needing efficient, consistent offboarding Remote-First Companies: Distributed teams requiring coordinated equipment recovery What You'll Need Required Integrations Jotform - Exit interview and resignation form (free tier works) Create your form for free on Jotform using this link OpenAI API - GPT-4 for AI exit interview analysis (~$0.20-0.50 per exit interview) Gmail - Automated notifications to employees, managers, IT, and HR Google Sheets - Exit interview database and retention analytics Quick Start Import Template - Copy JSON and import into n8n Add OpenAI Credentials - Set up OpenAI API key (GPT-4 for best insights) Create Jotform Exit Interview - Build comprehensive form with these sections: Configure Gmail - Add Gmail OAuth2 credentials Setup Google Sheets: Create spreadsheet with "Exit_Interviews" sheet Replace YOUR_GOOGLE_SHEET_ID in workflow Columns will auto-populate on first submission Customization Options AI Prompt Refinement: Tailor analysis for your industry, company culture, and specific concerns Red Flag Categories: Customize what constitutes a red flag for your organization Equipment Types: Add specialized equipment (tools, uniforms, parking passes) Access Systems: Integrate with your specific IT systems for automated revocation Knowledge Transfer Templates: Create role-specific handover checklists Manager Notifications: Add more details based on department or seniority Exit Interview Questions: Add industry-specific or company-specific questions Retention Focus Areas: Adjust AI to focus on specific retention priorities Rehire Workflows: Add automatic alumni network invitations for boomerang candidates Severance Processing: Add nodes for severance agreement generation and tracking Reference Check Process: Include reference policy notifications Benefits COBRA: Automate COBRA benefits notification workflows Expected Results Zero security breaches from lingering access - automated revocation on last day 100% equipment recovery - automated tracking and follow-up 3x faster offboarding - 30 minutes vs 2 hours of manual coordination 85% actionable insights from exit interviews vs 20% with manual reviews 60% improvement in identifying preventable turnover 90% manager compliance with knowledge transfer (vs 40% manual) 50% reduction in repeat management issues through coaching identification 40% increase in boomerang rehires through positive offboarding experience Complete audit trail for legal compliance and investigations Department-level insights identifying systemic retention issues Use Cases Tech Startup (100 Employees, High Growth) Engineer resigns to join competitor. AI detects compensation issue (40% below market), flags manager micromanagement concerns, and identifies preventable departure (preventability: 85%). HR immediately initiates compensation review for engineering team, schedules manager coaching, and retains 3 other engineers considering leaving. Access to codebase revoked automatically on last day. Boomerang probability: 70% - maintains relationship for future recruiting. Healthcare System (500 Nurses) Nurse leaves citing burnout. AI identifies systemic staffing issues in ER department affecting 15% of departures. Flags potential HIPAA violation concern requiring investigation. Automatically revokes EHR access on final day. Equipment recovery (badge, pager, scrubs) tracked with 100% success. Exit insights lead to ER staffing model changes, reducing nurse turnover by 30%. Financial Services Firm Compliance officer departs. AI red flags potential ethics concern requiring immediate investigation. Legal team notified within minutes. Knowledge transfer flagged as "critical risk" due to regulatory expertise. Detailed 30-day handover plan auto-generated. All system access revoked immediately. Complete audit trail maintained for regulatory review. Investigation reveals process gap, not ethical issue, preventing regulatory exposure. Retail Chain (2,000 Employees) Store manager exits. AI aggregates insights across 50 recent retail departures, identifying district manager as common thread (manager rating consistently 2/5). Regional HR intervenes with district manager coaching. Equipment return (keys, registers codes, uniforms) automated via checklist. 95% equipment recovery vs previous 60%. Sentiment trends show seasonal staff prefer flexible scheduling - policy updated chain-wide. Remote Software Company Developer in different timezone resigns. Automated offboarding coordinates across 3 time zones: access revoked at EOD local time, equipment return label emailed internationally, knowledge transfer scheduled with overlap hours. AI detects "career growth" as preventable issue - company implements career ladder framework, reducing senior developer attrition by 45%. Pro Tips Timing Matters: Send Jotform link 1 week before last day for honest feedback (not on exit day) Anonymity Option: Consider anonymous feedback for more candid responses (separate form) Benchmark Scoring: After 50+ exits, calculate your company's average preventability score Manager Patterns: Track exits by manager to identify coaching needs early Department Trends: Monthly reviews of AI insights by department for systemic issues Compensation Data: Cross-reference "compensation issue" flags with market data Boomerang Program: Create formal alumni network for high-probability boomerang candidates Equipment Deposits: Consider requiring deposits for easier equipment recovery Exit Interview Training: Train managers on how to act on AI insights constructively Legal Review: Have legal team review red flag escalation categories quarterly Continuous Improvement: Use AI recommendations to create quarterly retention action plans Stay Interviews: Use exit interview insights to inform "stay interview" questions for current employees Learning Resources This workflow demonstrates advanced n8n automation patterns: AI Agents with complex structured output for multi-dimensional analysis, Sentiment analysis and natural language processing Conditional escalation based on severity and red flags Multi-stakeholder notifications with role-specific messaging Risk assessment algorithms for knowledge transfer and preventability Pattern recognition across qualitative feedback Equipment inventory management with dynamic list generation Compliance automation for access revocation scheduling Predictive analytics for boomerang probability Perfect for learning AI-powered HR automation and organizational analytics! 📊 Workflow Architecture 📝 Jotform Exit Interview Submission ↓ 🧾 Parse Offboarding Data ↓ 🤖 AI Exit Interview Analysis (GPT-4) │ ├─ Retention analysis (preventability scoring) │ ├─ Sentiment analysis (tone, emotions) │ ├─ Manager performance evaluation │ ├─ Department insights │ ├─ Compensation benchmarking │ ├─ Knowledge transfer risk assessment │ ├─ Competitor intelligence │ ├─ Red flag detection │ ├─ Boomerang probability │ └─ Action item generation ↓ 🔗 Extract AI Analysis (JSON) ↓ 🧩 Merge Exit Analysis with Data │ ├─ Calculate days until last day │ ├─ Build equipment checklist │ └─ Assess urgency levels ↓ ⚠️ Has Red Flags? ├─ TRUE → 🚨 Send Red Flag Alert (HR Director/Legal) │ ↓ └─ FALSE → 📧 Send Manager Action Items ↓ ✉️ Send Employee Checklist ↓ 🔐 Send IT Offboarding Request ↓ 📊 Log to Google Sheets Ready to transform employee offboarding? Import this template and turn departures into retention insights while maintaining security and professionalism. Every exit becomes a learning opportunity! 🚪✨ Questions or customization needs? The workflow includes detailed sticky notes explaining each AI analysis component and routing decision. An n8n automation workflow template by Jitesh Dugar.

By Jitesh Dugar

Transform your fleet operations from paper-based chaos to intelligent automation - achieving 40% reduction in breakdowns, 100% inspection compliance, and predictive maintenance that saves thousands in repair costs. What This Workflow Does Revolutionizes fleet management with AI-driven vehicle inspections and predictive maintenance: 📝 Digital Inspections - Jotform captures daily vehicle checks with photos, mileage, and comprehensive checklists 🤖 AI Condition Analysis - Advanced AI Agent evaluates vehicle condition, safety ratings, and maintenance needs ⚠️ Smart Prioritization - Automatically flags critical issues (brakes, safety concerns, DOT compliance) 🔧 Maintenance Routing - Routes issues to appropriate shop teams with detailed work orders 📊 Predictive Maintenance - Tracks mileage thresholds and predicts upcoming service needs ✉️ Automated Notifications - Sends alerts to maintenance teams and confirmation to drivers 📈 Compliance Tracking - Monitors DOT inspections, registrations, and annual certifications 💰 Cost Management - Estimates repair costs and tracks downtime to optimize fleet budget 📋 Complete Documentation - Logs all inspections to Google Sheets for audits and analytics Key Features AI-Powered Vehicle Assessment: GPT-4 analyzes inspection data across 10+ components with safety ratings (0-100) Critical Issue Detection: Automatic identification of safety concerns, DOT violations, and immediate action items Mileage-Based Scheduling: Tracks oil changes, tire rotations, brake inspections with automated reminders Compliance Management: Monitors annual inspections, DOT certifications, and registration expiries Work Order Generation: Creates detailed maintenance orders with instructions, parts needed, and cost estimates Driver Performance Tracking: Evaluates vehicle care quality and identifies training needs Predictive Analytics: Forecasts upcoming maintenance based on usage patterns and vehicle age Emergency Routing: Critical issues trigger immediate alerts to maintenance supervisors Photo Documentation: Captures damage and odometer photos for insurance and warranty claims Real-Time Fleet Status: Tracks operational, out-of-service, and maintenance-required vehicles Cost Estimation: AI-generated repair cost ranges and downtime predictions DOT Audit Ready: Complete inspection logs formatted for regulatory compliance Perfect For Commercial Fleet Operators: Delivery companies, logistics firms managing 10-500+ vehicles Transportation Companies: Trucking fleets requiring DOT compliance and safety standards Service Businesses: Plumbing, HVAC, electrical companies with service vehicle fleets Government Fleets: Municipal vehicles, police departments, public works departments Rental Car Companies: Daily inspections and damage documentation for rental fleets Construction Companies: Heavy equipment and vehicle maintenance tracking Food Delivery Services: High-mileage vehicles requiring frequent inspections Ride-Share Fleet Managers: TNC vehicles needing daily safety checks What You'll Need Required Integrations Jotform - Digital inspection form with photo upload (free tier works) Create your form for free on Jotform using this link OpenAI API - GPT-4 for AI vehicle analysis (~$0.15-0.40 per inspection) Gmail - Automated notifications to maintenance teams and drivers Google Sheets - Inspection database, maintenance tracking, and compliance logs Optional Enhancements Twilio - SMS alerts for critical issues and driver notifications Google Calendar - Automated maintenance scheduling QuickBooks - Expense tracking and repair cost management Fleet Management Software - Integration with Geotab, Samsara, or Fleetio Zapier - Additional integration bridges for specialty systems Google Drive - Photo backup and document storage Maintenance Software - Connect to shop management systems Telematics Integration - Real-time mileage and diagnostics data Quick Start Import Template - Copy JSON and import into n8n Add OpenAI Credentials - Set up OpenAI API key (GPT-4 recommended for accuracy) Create Jotform - Build vehicle inspection form with these essential fields: Driver Info: Name, Email Vehicle Details: Vehicle ID, Make, Model, Year, License Plate Mileage: Current Odometer Reading Fuel Level: Dropdown (Full, 3/4, 1/2, 1/4, Empty) Inspection Checklist: Dropdowns for each component (Good, Fair, Poor, Needs Immediate Attention) Tires Brakes Lights (headlights, taillights, turn signals) Fluid Levels (oil, coolant, brake fluid) Engine Transmission Interior Condition Exterior Condition Issues: Yes/No dropdown + Long text for description Photos: File upload for damage photos and odometer photo Cleanliness Rating: 1-5 star rating Driver Notes: Textarea for additional comments Configure Gmail - Add Gmail OAuth2 credentials for notifications Setup Google Sheets: Create new spreadsheet for fleet tracking Add sheet named "Inspections" Replace YOUR_GOOGLE_SHEET_ID in the workflow Google Sheets will auto-populate columns on first run Customization Options AI Prompt Refinement: Tailor analysis for specific vehicle types (trucks, vans, sedans, heavy equipment) Custom Maintenance Intervals: Adjust service schedules based on manufacturer recommendations Multi-Location Support: Route work orders to different shop locations based on vehicle assignment Priority Escalation: Add manager approval workflows for expensive repairs Driver Training Module: Track recurring issues per driver and generate training recommendations Seasonal Adjustments: Different inspection criteria for winter/summer (tire tread, AC, heating) Vehicle Categories: Separate workflows for passenger vehicles, trucks, specialty equipment Cost Approval Thresholds: Require manager sign-off for repairs over $X amount Parts Inventory Integration: Check parts availability before scheduling maintenance Vendor Management: Route different issue types to specialized vendors Mobile Optimization: Design Jotform specifically for mobile/tablet use in vehicles Offline Mode: Enable Jotform offline submissions for areas with poor connectivity Expected Results 40% reduction in breakdowns - Predictive maintenance catches issues early 100% inspection compliance - Digital tracking eliminates missed checks 24-hour turnaround on maintenance scheduling vs days of manual coordination 30% cost savings - Preventive maintenance avoids expensive emergency repairs 60% faster inspections - Digital forms take 5 minutes vs 15+ for paper Zero lost paperwork - All inspections digitally stored and searchable 85% better DOT audit results - Complete, organized documentation 50% reduction in vehicle downtime - Proactive maintenance scheduling 95% driver compliance - Easy mobile forms increase participation Real-time fleet visibility - Instant status of all vehicles Pro Tips QR Code Access: Place QR codes in each vehicle linking directly to that vehicle's inspection form Pre-Fill Vehicle Data: Use Jotform conditional logic to auto-fill vehicle details when driver enters Vehicle ID Photo Requirements: Make damage and odometer photos mandatory for compliance Daily Reminders: Set up automated daily email/SMS reminders for drivers to complete inspections Seasonal Checklists: Adjust inspection criteria seasonally (winter: tire tread/battery; summer: AC/coolant) Benchmark Analysis: After 100+ inspections, analyze AI accuracy and refine the prompt with real examples Driver Training: Use AI driver performance ratings to identify training needs Telematics Integration: Connect to vehicle GPS/diagnostics for automatic mileage updates Parts Pre-Ordering: Use predictive maintenance to pre-order common parts before needed Maintenance History: Track vehicle-specific patterns (e.g., Vehicle #12 always needs brake work) Incentive Programs: Reward drivers with best vehicle care ratings Mobile-First Design: Ensure Jotform works perfectly on phones - most inspections done on mobile Learning Resources This workflow demonstrates advanced n8n automation: AI Agents with structured JSON output for reliable vehicle assessment Conditional routing based on criticality and safety ratings Database lookups for vehicle maintenance history Predictive analytics using mileage thresholds and time intervals Multi-recipient notifications with role-based messaging Compliance tracking with automatic deadline monitoring Cost estimation algorithms for budget planning Photo handling for documentation and insurance claims Error handling with fallback assessments Perfect for learning fleet operations automation and AI integration! 📊 Workflow Architecture 📝 Jotform Daily Inspection ↓ 🧾 Parse Inspection Data ↓ 📊 Get Vehicle History │ ├─ Last service dates │ ├─ Mileage calculations │ └─ Compliance deadlines ↓ 🤖 AI Fleet Analysis (GPT-4) │ ├─ Condition assessment │ ├─ Safety rating (0-100) │ ├─ Critical issue detection │ ├─ Maintenance recommendations │ ├─ Cost estimation │ ├─ DOT compliance check │ └─ Work order generation ↓ 🔗 Extract & Merge AI Analysis ↓ ⚡ Critical Issue Check ├─ TRUE → 🚨 Critical Alert Email (Maintenance) └─ FALSE → 📋 Routine Report Email (Maintenance) ↓ ✉️ Driver Confirmation Email │ ├─ Inspection received │ ├─ Vehicle status │ ├─ Maintenance scheduled │ └─ Safety notices ↓ 📊 Log to Google Sheets └─ Inspection database └─ Audit trail └─ Analytics data 🔐 Compliance & Security Ready to transform your fleet management? Import this template and eliminate breakdowns, ensure compliance, and save thousands in maintenance costs through AI-powered predictive maintenance! 🚗✨ Questions or customization needs? The workflow includes detailed sticky notes explaining each component and decision point. An n8n automation workflow template by Jitesh Dugar.

By Rahul Joshi

Description Keep your product and project teams perfectly aligned by automatically syncing task dependencies between Jira and Monday.com. This workflow ensures real-time visibility into cross-platform blockers and dependencies, allowing smoother delivery across multiple teams and tools. 🔄📅💼 What This Template Does Step 1: Trigger the workflow on a schedule or manual run. Step 2: Fetch project tasks and dependencies from Jira. Step 3: Retrieve matching items from Monday.com based on linked project IDs or issue keys. Step 4: Compare dependencies between both systems. Step 5: Identify mismatched or missing dependencies across platforms. Step 6: Send summarized reports to Slack or Gmail for team visibility. Step 7: Optionally update Monday.com or Jira items with dependency status tags. Key Benefits ✅ Maintain alignment across multiple projects and teams. ✅ Detect and resolve dependency conflicts before they cause delays. ✅ Automate visibility — no more manual cross-checking. ✅ Simplify multi-tool management for product and engineering leads. Features Integration between Jira Cloud and Monday.com API Cross-dependency comparison logic Scheduled or manual execution Slack/Gmail notifications for updates or conflicts Custom mapping for project and issue identifiers Requirements Jira Cloud account with API credentials Monday.com API key or OAuth2 token Optional: Slack or Gmail credentials for notifications n8n instance (cloud or self-hosted) Target Audience Product and Project Managers coordinating across tools 🧩 Engineering Leads overseeing multi-platform sprints ⚙️ PMOs managing dependencies across cross-functional teams 📊 Operations teams aiming for unified delivery visibility 📈 Step-by-Step Setup Instructions Connect your Jira and Monday.com credentials in n8n. Map project identifiers or keys between Jira and Monday.com. (Optional) Configure Slack or Gmail for daily status alerts. Adjust the cron expression to match your monitoring schedule. Run the workflow once manually to validate mappings. Activate the workflow for ongoing dependency tracking. ✅. An n8n automation workflow template by Rahul Joshi.

By Summer

Research for Upcoming Meeting Creator: Summer Chang Never walk into a meeting unprepared again! This workflow automatically researches your meeting contacts every morning and emails you the latest news and insights about the companies you're meeting with today. ✅ Step 1: Set Your Morning Briefing Time Open the Every morning @ 7 Schedule Trigger and adjust the time when you'd like to receive your daily meeting briefings. The default is set to 9 AM. ✅ Step 2: Connect Your Google Calendar Link your Google Calendar credentials to the Get meetings for today node. This allows the workflow to scan your calendar for external meetings. ✅ Step 3: Connect Your Tavily Research API Add your Tavily API key to the Research Company/Person node. This powers the intelligent research that finds recent news and insights about your meeting contacts. ✅ Step 4: Link Your Gmail Account Connect your Gmail credentials to the Send news node so your research briefings can be automatically delivered to your inbox each morning. ✅ Step 5: Customize Your Email Settings In the Send news node, update: Send To: Your email address Sender Name: Customize how the emails appear in your inbox ✅ Step 6: Activate the Workflow Once everything is connected, set the workflow to active so it runs automatically each morning and keeps you prepared. An n8n automation workflow template by Summer.

By Parag Javale

The AI Blog Creator with Gemini, Replicate Image, Supabase Publishing & Slack is a fully automated content generation and publishing workflow designed for modern marketing and SaaS teams. It automatically fetches the latest industry trends, generates SEO-optimized blogs using AI, creates a relevant featured image, publishes the post to your CMS (e.g., Supabase or custom API), and notifies your team via Slack all on a daily schedule. This workflow connects multiple services NewsAPI, Google Gemini, Replicate, Supabase, and Slack into one intelligent content pipeline that runs hands-free once set up. ✨ Features 📰 Fetch Trending Topics — pulls the latest news or updates from your selected industry (via NewsAPI). 🤖 AI Topic Generation — Gemini suggests trending blog topics relevant to AI, SaaS, and Automation. 📝 AI Blog Authoring — Gemini then writes a full 1200-1500 word SEO-optimized article in Markdown. 🧹 Smart JSON Cleaner — A resilient code node parses Gemini’s output and ensures clean, structured data. 🖼️ Auto-Generated Image — Replicate’s Ideogram model creates a blog cover image based on the content prompt. 🌐 Automatic Publishing — Posts are automatically published to your Supabase or custom backend. 💬 Slack Notification — Notifies your team with blog details and live URL. ⏰ Fully Scheduled — Runs automatically every day at your preferred time (default 10 AM IST). ⚙️ Workflow Structure | Step | Node | Purpose | | ---- | ----------------------------------- | ----------------------------------------------- | | 1 | Schedule Trigger | Runs daily at 10 AM | | 2 | Fetch Industry Trends (NewsAPI) | Retrieves trending articles | | 3 | Message a model (Gemini) | Generates trending topic ideas | | 4 | Message a model1 (Gemini) | Writes full SEO blog content | | 5 | Code in JavaScript | Cleans, validates, and normalizes Gemini output | | 6 | HTTP Request (Replicate) | Generates an image using Ideogram | | 7 | HTTP Request1 | Retrieves generated image URL | | 8 | Wait + If | Polls until image generation succeeds | | 9 | Edit Fields | Assembles blog fields into final JSON | | 10 | Publish to Supabase | Posts to your CMS | | 11 | Slack Notification | Sends message to your Slack channel | 🔧 Setup Instructions Import the Workflow in n8n and enable it. Create the following credentials: NewsAPI (Query Auth) — from https://newsapi.org Google Gemini (PaLM API) — use your Gemini API key Replicate (Bearer Auth) — API key from https://replicate.com/account Supabase (Header Auth) — endpoint to your /functions/v1/blog-api (set your key in header) Slack API — create a Slack App token with chat:write permission Edit the NewsAPI URL query parameter to match your industry (e.g., q=AI automation SaaS). Update the Supabase publish URL to your project endpoint if needed. Adjust the Slack Channel name under “Slack Notification”. (Optional) Change the Schedule Trigger time as per your timezone. 💡 Notes & Tips The Code in JavaScript node is robust against malformed or extra text in Gemini output — it sanitizes Markdown and reconstructs clean JSON safely. You can replace Supabase with any CMS or Webhook endpoint by editing the “Publish to Supabase” node. The Replicate model used is ideogram-ai/ideogram-v3-turbo — you can swap it with Stable Diffusion or another model for different aesthetics. Use the slug field in your blog URLs for SEO-friendly links. Test with one manual execution before activating scheduled runs. If Slack notification fails, verify the token scopes and channel permissions. 🧩 Tags #AI #Automation #ContentMarketing #BlogGenerator #n8n #Supabase #Gemini #Replicate #Slack #WorkflowAutomation. An n8n automation workflow template by Parag Javale.

By Bastian Diaz

🎯 Description Automatically generates, designs, stores, and logs complete Instagram carousel posts. It transforms a simple text prompt into a full post with copy, visuals, rendered images, Google Drive storage, and a record in Google Sheets. ⚙️ Use case / What it does This workflow enables creators, educators, or community managers to instantly produce polished, on-brand carousel assets for social media. It integrates OpenAI GPT-4.1, Pixabay, Templated.io, Google Drive, and Google Sheets into one continuous content-production chain. 💡 How it works 1️⃣ Form Trigger – Collects the user prompt via a simple web form. 2️⃣ OpenAI GPT-4.1 – Generates structured carousel JSON: titles, subtitles, topic, description, and visual keywords. 3️⃣ Code (Format content) – Parses the JSON output for downstream use. 4️⃣ Google Drive (Create Folder) – Creates a subfolder for the new carousel inside “RRSS”. 5️⃣ HTTP Request (Pixabay) – Searches for a relevant image using GPT’s visual suggestion. 6️⃣ Code (Get first result) – Extracts the top Pixabay result and image URL. 7️⃣ Templated.io – Fills the design template layers (titles/subtitles/topic/image). 8️⃣ HTTP Request (Download renders) – Downloads the rendered PNGs from Templated.io. 9️⃣ Google Drive (Upload) – Uploads the rendered images into the created folder. 10️⃣ Google Sheets (Save in DB) – Logs metadata (title, topic, folder link, description, timestamp, status). 🔗 Connectors used OpenAI GPT-4.1 (via n8n LangChain node) Templated.io API (design rendering) Pixabay API (stock image search) Google Drive (storage + folder management) Google Sheets (database / logging) Form Trigger (input collection) 🧱 Input / Output Input: User-submitted “Prompt” (text) via form Output: Generated carousel images stored in Google Drive Spreadsheet row in Google Sheets containing title, topic, description, Drive URL, status ⚠️ Requirements / Setup Valid credentials for: OpenAI API (GPT-4.1 access) Templated.io API key Pixabay API key Google Drive + Google Sheets OAuth connections Existing Google Drive folder ID for RRSS storage Spreadsheet with matching column headers (Created At, Title, Topic, Folder URL, Description, Status) Published form URL for user prompts 🌍 Example applications / extensions Educational themes (mental health, fitness, sustainability). Extend to auto-publish to Instagram Business via Meta API. Add Notion logging or automated email notifications. Integrate scheduling (Cron node) to batch-generate weekly carousels. An n8n automation workflow template by Bastian Diaz.

By Aadarsh Jain

Document Analyzer and Q&A Workflow AI-powered document and web page analysis using n8n and GPT model. Ask questions about any local file or web URL and get intelligent, formatted answers. Who's it for Perfect for researchers, developers, content analysts, students, and anyone who needs quick insights from documents or web pages without uploading files to external services. What it does Analyzes local files**: PDF, Markdown, Text, JSON, YAML, Word docs Fetches web content**: Documentation sites, blogs, articles Answers questions**: Using GPT model with structured, well-formatted responses Input format: path_or_url | your_question Examples: /Users/docs/readme.md | What are the installation steps? https://n8n.io | What is n8n? Setup Import workflow into n8n Add your OpenAI API key to credentials Link the credential to the "OpenAI Document Analyzer" node Activate the workflow Start chatting! Customize Change AI model → Edit "OpenAI Document Analyzer" node (switch to gpt-4o-mini for cost savings) Adjust content length → Modify maxLength in "Process Document Content" node (default: 15000 chars) Add file types → Update supportedTypes array in "Parse Document & Question" node Increase timeout → Change timeout value in "Fetch Web Content" node (default: 30s). An n8n automation workflow template by Aadarsh Jain.

By Jitesh Dugar

Tired of juggling maintenance calls, lost requests, and slow vendor responses? This workflow streamlines the entire property maintenance process — from tenant request to vendor dispatch — powered by AI categorization and automated communication. Cut resolution time from 5–7 days to under 24 hours and boost tenant satisfaction by 85% with zero manual follow-up. What This Workflow Does Transforms chaotic maintenance management into seamless automation: 📝 Captures Requests – Tenants submit issues via Jotform with unit number, issue description, urgency, and photos. 🤖 AI Categorization – OpenAI (GPT-4o-mini) analyzes and classifies issues (plumbing, HVAC, electrical, etc.). ⚙️ Smart Prioritization – Flags emergencies (leak, electrical failure) and assigns priority. 📬 Vendor Routing – Routes issue to the correct contractor or vendor based on AI category. 📧 Automated Communication – Sends acknowledgment to tenant and work order to vendor via Gmail. 📊 Audit Trail Logging – Optionally logs requests in Google Sheets for performance tracking and reporting. Key Features 🧠 AI-Powered Categorization – Intelligent issue type and priority detection. 🚨 Emergency Routing – Automatically escalates critical issues. 📤 Automated Work Orders – Sends detailed emails with property and tenant info. 📈 Google Sheets Logging – Transparent audit trail for compliance and analytics. 🔄 End-to-End Automation – From form submission to vendor dispatch in seconds. 💬 Sticky Notes Included – Every section annotated for easy understanding. Perfect For Property management companies Real estate agencies and facility teams Smart building operators Co-living and rental startups Maintenance coordinators managing 50–200+ requests monthly What You’ll Need Required Integrations: Jotform – Maintenance request form Create your form for free on Jotform using this link OpenAI (GPT-4o-mini) – Categorization and prioritization Gmail – Automated email notifications (Optional) Google Sheets – Logging and performance tracking Quick Start Import Template – Copy JSON into n8n and import. Create Jotform – Include fields: Tenant name, email, unit number, issue description, urgency, photo upload. Add Credentials – Configure Jotform, Gmail, and OpenAI credentials. Set Vendor Emails – Update “Send to Contractor” Gmail node with vendor email IDs. Test Workflow – Submit sample maintenance requests for AI categorization and routing. Activate Workflow – Go live and let your tenants submit maintenance issues. Expected Results ⏱️ 24-hour average resolution time (vs 5–7 days). 😀 85% higher tenant satisfaction with instant communication. 📉 Zero lost requests – every issue logged automatically. 🧠 AI-driven prioritization ensures critical issues handled first. 🕒 10+ hours saved weekly for property managers. Pro Tips 🧾 Add Google Sheets logging for a complete audit trail. 🔔 Include keywords like “leak,” “no power,” or “urgent” in AI prompts for faster emergency detection. 🧰 Expand vendor list dynamically using a Google Sheet lookup. 🧑‍🔧 Add follow-up automation to verify task completion from vendors. 📊 Create dashboards for monthly maintenance insights. Learning Resources This workflow demonstrates: AI categorization using OpenAI’s Chat Model (GPT-4o-mini) Multi-path routing logic (emergency vs. normal) Automated communication via Gmail Optional data logging in Google Sheets Annotated workflow with Sticky Notes for learning clarity. An n8n automation workflow template by Jitesh Dugar.

By Emilio Loewenstein

Description Save hours of manual reporting with this end-to-end automation. This workflow pulls campaign performance data (demo or live), generates a clear AI-powered executive summary, and compiles everything into a polished weekly report. The report is formatted in Markdown, automatically stored in Google Docs, and instantly shared with your team via Slack — no spreadsheets, no copy-paste, no delays. What it does ⏰ Runs on a schedule (e.g. every Monday morning) 📊 Collects performance metrics (Google Ads, Meta, TikTok, YouTube – demo data included) 🤖 Uses AI to summarize wins, issues, and recommendations 📝 Builds a structured Markdown report (totals, channel performance, top campaigns) 📄 Creates and updates a Google Doc with the report 💬 Notifies your team in Slack with topline numbers + direct report link 📧 Optionally email the report to stakeholders or clients Why it’s valuable Saves time** – no manual data aggregation Standardizes reporting** – same format and quality every week Adds insights** – AI highlights what matters most Improves transparency** – instant access via Docs, Slack, or Email Scales easily** – adapt to multiple clients or campaigns Professional delivery** – branded, polished reports on autopilot 💡 Extra recommendation: Connect to a Google Docs template to give your reports a professional, branded look. An n8n automation workflow template by Emilio Loewenstein.

By Daniel Nkencho

Secure your n8n automations with this comprehensive template that automates periodic backups to Telegram for instant access while enabling flexible restores from Google Drive links or direct file uploads—ensuring quick recovery without data loss. 📋 What This Template Does This dual-branch workflow handles full n8n instance backups and restores seamlessly. The backup arm runs every 3 days, fetching all workflows via the n8n API, aggregating them into a JSON array, converting to a text file, and sending it to Telegram for offsite storage and sharing. The restore arm supports two entry points: manual execution to pull a backup from Google Drive or form-based upload for local files, then parses the JSON, cleans workflows for compatibility, and loops to create missing ones or update existing by name—handling batches efficiently to respect API limits. Scheduled backups with Telegram delivery for easy stakeholder access Dual restore paths: Drive download or direct file upload via form Intelligent create-or-update logic with data sanitization to avoid conflicts Looped processing with existence checks and error continuation 🔧 Prerequisites n8n instance with API enabled (self-hosted or cloud) Telegram account for bot setup Google Drive account (optional, for Drive-based restores) 🔑 Required Credentials n8n API Setup In n8n, navigate to Settings → n8n API Enable the API and generate a new key Add to n8n as "n8n API" credential type, pasting the key in the API Key field Telegram API Setup Message @BotFather on Telegram to create a new bot and get your token Find your chat ID by messaging @userinfobot Add to n8n as "Telegram API" credential type, entering the Bot Token Google Drive OAuth2 API Setup In Google Cloud Console, go to APIs & Services → Credentials Create an OAuth 2.0 Client ID for Web application, enable Drive API Add redirect URI: [your-n8n-instance-url]/rest/oauth2-credential/callback Add to n8n as "Google Drive OAuth2 API" credential type and authorize ⚙️ Configuration Steps Import the workflow JSON into your n8n instance Assign the n8n API, Telegram API, and Google Drive credentials to their nodes Update the Telegram chat ID in the "Send Backup to Telegram" node Set the Google Drive file ID in the "Download Backup from Drive" node (from file URL) Activate the workflow and test backup by executing the Schedule node manually Test restore: Run manual trigger for Drive or use the form for upload 🎯 Use Cases Dev teams backing up staging workflows to Telegram for rapid production restores during deployments Solo automators uploading local backups via form to sync across devices after n8n migrations Agencies sharing client workflow archives via Drive links for secure, collaborative restores Educational setups scheduling exports to Telegram for student template distribution and recovery ⚠️ Troubleshooting Backup file empty: Verify n8n API permissions include read access to workflows Restore parse errors: Check JSON validity in backup file; adjust Code node property reference if needed API rate limits hit: Increase Wait node duration or reduce batch size in Loop Form upload fails: Ensure file is valid JSON text; test with small backup first. An n8n automation workflow template by Daniel Nkencho.

By AppUnits AI

Generate Invoices for Customers with Jotform and QuickBooks This workflow automates the entire process of receiving a product/service order, checking or creating a customer in QuickBooks Online (QBO), generating an invoice, and emailing it — all triggered by a form submission (via Jotform). How It Works Receive Submission Triggered when a user submits a form. Collects data like customer details, selected product/service, etc. Check If Customer Exists Searches QBO to determine if the customer already exists. If Customer Exists:* *Update** customer details (e.g., billing address). If Customer Doesn’t Exist:* *Create** a new customer in QBO. Get The Item Retrieves the selected product or service from QBO. Create The Invoice Generates a new invoice for the customer using the item selected. Send The Invoice Automatically sends the invoice via email to the customer. Who Can Benefit from This Workflow? Freelancers** Service Providers** Consultants & Coaches** Small Businesses** E-commerce or Custom Product Sellers** Requirements Jotform webhook setup, more info here QuickBooks Online credentials, more info here. An n8n automation workflow template by AppUnits AI.

By Asfandyar Malik

Short Description: Automatically collect and analyze your competitor’s YouTube performance. This workflow extracts video titles, views, likes, and descriptions from any YouTube channel and saves the data to Google Sheets — helping creators spot viral trends and plan content that performs. Who’s it for For content creators, YouTubers, and marketing teams who want to track what’s working for their competitors — without manually checking their channels every day. How it works This workflow automatically collects data from any YouTube channel you enter. You just write the channel name in the form — n8n fetches the channel ID, gets all recent video IDs, and extracts each video’s title, views, likes, and description. Finally, all the information is saved neatly into a connected Google Sheet for analysis. How to set up Create a Google Sheet with columns for Title, Views, Likes, Description, and URL. Connect your Google account to n8n. Add your YouTube Data API key inside the HTTP Request nodes (use n8n credentials, not hardcoded keys). Update your form submission or trigger node to match your input method. Execute the workflow once to test and verify that data is flowing into your sheet. Requirements YouTube Data API key Google Sheets account n8n cloud or self-hosted instance How to customize You can modify the JavaScript code node to include more metrics (like comments or publish date), filter by keywords, or change the output destination (e.g., Airtable or Notion). An n8n automation workflow template by Asfandyar Malik.

By Yusei Miyakoshi

Who’s it for Teams that start their day in Slack and want a concise, automated summary of yesterday’s emails—ops leads, PMs, founders, and anyone handling busy inboxes without writing code. What it does / How it works Runs every morning at 08:00 (cron 0 0 8 * * ), fetches all emails received *yesterday, and routes the result: if none were found, it posts a polite “no emails” notice; if emails exist, it aggregates them and asks an AI agent to produce a structured digest, then formats and posts to your chosen Slack channel. The flow uses **Gmail → If → Aggregate (Item Lists) → AI Agent (OpenRouter model with structured output) → Code (Slack formatter) → Slack. A set of sticky notes on the canvas explains each step and required inputs. How to set up Connect Gmail (OAuth2) and keep the default date window (yesterday → today at 00:00). Connect Slack (OAuth2) and select your target channel. Add OpenRouter credentials and pick a compact model (e.g., gpt-4o-mini). Keep the provided structured-output schema and formatter code. Adjust the schedule/timezone if needed (the fallback message includes an Asia/Tokyo example). Paste this description into the yellow sticky note at the top of the canvas. Requirements Gmail & Slack accounts with appropriate scopes OpenRouter API key stored in Credentials (no hard-coded keys) n8n Cloud or self-host with LangChain agent nodes enabled How to customize the workflow Narrow Gmail results with label/search filters (e.g., from:, subject:). Change the digest sections or tone in the AI Agent system prompt. Swap the model for cost/quality needs and tweak temperature/max tokens. Localize dates/timezones in the formatter code and Slack messages. Branch the output to email, Google Docs, or Sheets for archival. Security & publishing tips Rename all nodes clearly, do not hardcode API keys, remove real channel IDs/emails before sharing, and group end-user variables in a Set (Fields) node. Keep the sticky notes—they’re mandatory for reviewers. An n8n automation workflow template by Yusei Miyakoshi.

By Anatoly

AI-Powered Lead Generation: Personalized Icebreakers with Perplexity Research & Claude Sonnet 4.5 This production-ready workflow transforms your lead generation by automatically researching prospects and generating genuinely personalized icebreakers that feel human-written. What normally takes 10-15 minutes per lead now happens in under a minute, at scale. 🎯 What It Does: Pulls lead data from Google Sheets, conducts real-time AI research on each prospect, and generates custom cold email opening lines that reference actual company achievements and recent news. The workflow processes leads in batches, updates your spreadsheet automatically, and maintains context throughout the entire process. Automated Research**: Perplexity Sonar searches the web for current information about each prospect and their company Company Name Standardization**: GPT-4o-mini cleans up corporate names to sound natural ("Sharp Guys Web Design Agency" becomes "Sharp Guys") Personalized Icebreakers**: Claude Sonnet 4 crafts opening lines that reference real achievements in a casual, bar-conversation tone Smart Processing**: Filters already-processed leads, handles batches of 25, and safely updates your spreadsheet Cost Effective**: Approximately $0.02 per lead with typical 2-3x response rate improvement 💡 Use Cases & Results: Perfect for: B2B sales teams, marketing agencies, business development, recruiters, freelancers, startup founders doing cold outreach. Expected results: 2-3x response rate improvement ~$0.02 per lead cost 10-15 min → 30-60 sec per lead Why it works: Icebreakers reference real, current information vs generic templates. Prospects notice the personalization. 🔧 How It Works: The workflow follows a six-step process. First, it retrieves lead data from your Google Sheets and filters out any leads that already have icebreakers to avoid reprocessing. Then it processes leads in manageable batches of 25 to respect API rate limits while maintaining efficiency. For each lead, the system standardizes the company name by removing corporate suffixes like "Agency," "Inc.," or "Group" to make icebreakers sound more natural. Next, Perplexity Sonar conducts real-time web research on the prospect, finding recent company news, achievements, funding rounds, and relevant background information. Claude Sonnet 4 then analyzes this research and generates a personalized icebreaker that sounds genuinely human-written. The prompt instructs Claude to use a casual, spartan tone and to look for plausible connections without stretching the truth. Each icebreaker follows a proven format: "Hey [FirstName], [specific observation about their company], I wanted to share something that could be relevant for [Company]." Finally, the workflow updates your spreadsheet with both the cleaned company name and the personalized icebreaker, then loops back to process the next batch until all unprocessed leads are complete. ✨ Key Features: Real-time research**: Perplexity Sonar accesses current web data for the most relevant, up-to-date information Natural language**: Icebreakers reference real achievements in conversational tone, not corporate speak Batch processing**: Handles 25 leads at a time with automatic looping for any volume Smart filtering**: Skips leads that already have icebreakers, enabling easy reruns with new data JSON output**: Structured format ready for integration with cold email tools Resume capability**: Can stop and restart anytime without losing progress Quality assurance**: AI models are specifically chosen for their strengths (speed, research, writing) 📋 Requirements: Google Sheets with lead data (columns: id, first_name, last_name, title, organization_name, Icebreaker, company_name_cleanup) OpenAI API key (for GPT-4o-mini company name cleanup) OpenRouter account with credits (for Perplexity Sonar and Claude Sonnet 4 access) n8n Cloud or self-hosted instance ⚡ Quick Setup: Prepare your Google Sheets spreadsheet with the required columns and fill in your lead data. Connect your Google Sheets, OpenAI, and OpenRouter credentials to n8n. Configure the "Get Leads" and "Update Icebreaker" nodes to point to your spreadsheet. Test with a couple of leads first to ensure everything works, then run the full workflow. The workflow includes comprehensive documentation via sticky notes covering data structure, AI model selection rationale, customization options, cost analysis. 🎁 What You Get: Complete end-to-end automation with detailed sticky note documentation explaining each step, customizable prompts for adjusting tone and style, batch processing logic that respects API limits, error handling and retry mechanisms, cost optimization using the right AI model for each task (GPT-4o-mini for simple transformations, Perplexity for research, Claude for writing), and security best practices for handling lead data responsibly. 💰 Expected Results: At approximately $0.02 per lead, this workflow typically delivers response rate improvements of 2-3x compared to generic templates. For a hundred leads, you invest about $2 and save over fifteen hours of manual research and writing time. The icebreakers sound genuinely human because they reference real, current information rather than generic templates. Many users report that prospects often respond positively to the personalized opening, commenting that it doesn't feel like a mass email. 🔄 Integration Ready: The output format is designed to integrate seamlessly with popular cold email tools like Instantly, Lemlist, Smartlead, and others. Simply export your updated spreadsheet and import the icebreakers into your outreach sequences. The casual tone and specific details make these icebreakers perfect for relationship-building campaigns where authenticity matters. Icebreaker Examples: https://docs.google.com/spreadsheets/d/1_oxNW4l54fVjxq6Y62xR_yqqQK6O3gCsmqmBhO2ei1Y/edit?usp=sharing. An n8n automation workflow template by Anatoly.

By Toshiya Minami

Who’s it for Teams building health/fitness apps, coaches running check-ins in chat, and anyone who needs quick, structured nutrition insights from food photos—without manual logging. What it does / How it works This workflow accepts a food image (URL or Base64), uses a vision-capable LLM to infer likely ingredients and rough gram amounts, estimates per-ingredient calories, and returns a strict JSON summary with total calories and a short nutrition note. It normalizes different payloads (e.g., Telegram/LINE/Webhook) into a common format, handles transient errors with retries, and avoids hardcoded secrets by using credentials/env vars. Requirements Vision-capable LLM credentials (e.g., gpt-4o or equivalent) One input channel (Webhook, Telegram, or LINE) Environment variables for model name/temperature and optional request validation How to set up Connect your input channel and enable the Webhook (copy the test URL). Add LLM credentials and set LLM_MODEL and LLM_TEMPERATURE (e.g., 0.3). Turn on the workflow, send a sample payload with imageUrl, and confirm the strict JSON output. (Optional) Configure a reply node (Telegram/Slack or HTTP Response) and a logger (Google Sheets/Notion). How to customize the workflow Outputs**: Add macros (protein/fat/carb) or micronutrient fields. Units**: Convert portion descriptions (piece/slice) to grams with your own mapping. Languages**: Toggle multilingual output (ja/en). Policies**: Tighten validation (reject low-confidence parses) or add manual review steps. Security**: Use signed/temporary URLs for private images; mask PII in logs. Data model (strict JSON) { "dishName": "string", "ingredients": [{ "name": "string", "amount": 0, "calories": 0 }], "totalCalories": 0, "nutritionEvaluation": "string" } Notes Rename all nodes clearly, include sticky notes explaining the setup, and never commit real IDs, tokens, or API keys. An n8n automation workflow template by Toshiya Minami.

By WeblineIndia

IPA Size Tracker with Trend Alerts – Automated iOS Apps Size Monitoring This workflow runs on a daily schedule and monitors IPA file sizes from configured URLs. It stores historical size data in Google Sheets, compares current vs. previous builds and sends email alerts only when significant size changes occur (default: ±10%). A DRY_RUN toggle allows safe testing before real notifications go out. Who’s it for iOS developers tracking app binary size growth over time. DevOps teams monitoring build artifacts and deployment sizes. Product managers ensuring app size budgets remain acceptable. QA teams detecting unexpected size changes in release builds. Mobile app teams optimizing user experience by keeping apps lightweight. How it works Schedule Trigger (daily at 09:00 UTC) kicks off the workflow. Configuration: Define monitored apps with {name, version, build, ipa_url}. HTTP Request downloads the IPA file from its URL. Size Calculation: Compute file sizes in bytes, KB, MB and attach timestamp metadata. Google Sheets: Append size data to the IPA Size History sheet. Trend Analysis: Compare current vs. previous build sizes. Alert Logic: Evaluate thresholds (>10% increase or >10% decrease). Email Notification: Send formatted alerts with comparisons and trend indicators. Rate Limit: Space out notifications to avoid spamming recipients. How to set up 1. Spreadsheet Create a Google Sheet with a tab named IPA Size History containing: Date, Timestamp, App_Name, Version, Build_Number, Size_Bytes, Size_KB, Size_MB, IPA_URL 2. Credentials Google Sheets (OAuth)** → for reading/writing size history. Gmail** → for sending alert emails (use App Password if 2FA is enabled). 3. Open “Set: Configuration” node Define your workflow variables: APP_CONFIGS = array of monitored apps ({name, version, build, ipa_url}) SPREADSHEET_ID = Google Sheet ID SHEET_NAME = IPA Size History SMTP_FROM = sender email (e.g., devops@company.com) ALERT_RECIPIENTS = comma-separated emails SIZE_INCREASE_THRESHOLD = 0.10 (10%) SIZE_DECREASE_THRESHOLD = 0.10 (10%) LARGE_APP_WARNING = 300 (MB) SCHEDULE_TIME = 09:00 TIMEZONE = UTC DRY_RUN = false (set true to test without sending emails) 4. File Hosting Host IPA files on Google Drive, Dropbox or a web server. Ensure direct download URLs are used (not preview links). 5. Activate the workflow Once configured, it will run automatically at the scheduled time. Requirements Google Sheet with the IPA Size History tab. Accessible IPA file URLs. SMTP / gmail account (Gmail recommended). n8n (cloud or self-hosted) with Google Sheets + Email nodes. Sufficient local storage for IPA file downloads. How to customize the workflow Multiple apps**: Add more configs to APP_CONFIGS. Thresholds**: Adjust SIZE_INCREASE_THRESHOLD / SIZE_DECREASE_THRESHOLD. Notification templates**: Customize subject/body with variables: {{app_name}}, {{current_size}}, {{previous_size}}, {{change_percent}}, {{trend_status}}. Schedule**: Change Cron from daily to hourly, weekly, etc. Large app warnings**: Adjust LARGE_APP_WARNING. Trend analysis**: Extend beyond one build (7-day, 30-day averages). Storage backend**: Swap Google Sheets for CSV, DB or S3. Add-ons to level up Slack Notifications**: Add Slack webhook alerts with emojis & formatting. Size History Charts**: Generate trend graphs with Chart.js or Google Charts API. Environment separation**: Monitor dev/staging/prod builds separately. Regression detection**: Statistical anomaly checks. Build metadata**: Log bundle ID, SDK versions, architectures. Archive management**: Auto-clean old records to save space. Dashboards**: Connect to Grafana, DataDog or custom BI. CI/CD triggers**: Integrate with pipelines via webhook trigger. Common Troubleshooting No size data** → check URLs return binary IPA (not HTML error). Download failures** → confirm hosting permissions & direct links. Missing alerts** → ensure thresholds & prior history exist. Google Sheets errors** → check sheet/tab names & OAuth credentials. Email issues** → validate SMTP credentials, spam folder, sender reputation. Large file timeouts** → raise HTTP timeout for >100MB files. Trend errors** → make sure at least 2 builds exist. No runs** → confirm workflow is active and timezone is correct. Need Help? If you’d like this to customize this workflow to suit your app development process, then simply reach out to us here and we’ll help you customize the template to your exact use case. An n8n automation workflow template by WeblineIndia.

By Yasser Sami

Outlook & Notion Knowledge Base Builder for AI Agents This n8n template lets you automatically build and maintain an AI-ready knowledge base from Outlook emails and Notion pages. It stores both sources in a Pinecone vector database so your AI agent can reference them when generating answers, extracting information, or drafting context-aware emails. Who’s it for Teams using Outlook for client or customer communications. Businesses maintaining documentation or notes in Notion. Developers or AI builders who want to create custom knowledge bases for intelligent agents. How it works / What it does Outlook Integration: When you move an email or thread to a specific folder (e.g., “knowledgebase”), the workflow triggers automatically. It captures the entire conversation, removes duplicates, and stores it in Pinecone under a namespace called "emails". The AI agent later uses these stored emails to learn tone, structure, and context for drafting responses. Notion Integration: When a page is added to a designated Notion database, the workflow triggers. The page content is extracted and embedded into Pinecone under the "knowledgebase" namespace. This allows your agent to use your Notion pages as factual reference material when answering questions. AI Agent Setup: Uses two Pinecone tools — one to reference Notion content (knowledge base) and another for emails (style & tone). Equipped with Cohere embeddings for multilingual support and OpenAI for conversation or drafting tasks. When queried, the agent retrieves relevant knowledge from both namespaces to produce accurate, context-rich replies. How to set up Import this template into your n8n account. Connect your Outlook account and specify which folder to watch (e.g., “knowledgebase”). Connect your Notion account and select your target database. Connect your Pinecone, Cohere, and OpenAI credentials. Activate the workflow — new Notion pages and Outlook threads will automatically update your knowledge base. Requirements n8n account. Microsoft Outlook account. Notion account and database. Pinecone account for vector storage. Cohere API key for embeddings. OpenAI API key for AI model. How to customize the workflow Namespaces:** Rename or expand namespaces (e.g., “sales_emails”, “internal_docs”) to organize knowledge types. Embeddings Model:** Replace Cohere with OpenAI embeddings if preferred. Agent Behavior:** Adjust the agent’s system message to change its tone or purpose (e.g., “act as a sales assistant”). Extra Sources:** Extend this workflow to include PDFs, websites, or Slack messages. Sync Schedule:** Modify trigger intervals to control how frequently updates are captured. This workflow automatically builds a living, AI-powered knowledge base from your Outlook and Notion data — perfect for intelligent support, research, or content generation. An n8n automation workflow template by Yasser Sami.

By Toshiya Minami

Sort invoice PDFs from Gmail to Google Drive and Google Sheets Who’s it for Freelancers, finance teams, and small businesses that receive invoice PDFs by email and want them automatically saved to Google Drive and logged in Google Sheets—without manual downloading or copy-pasting. How it works / What it does This workflow watches your Gmail inbox for unread messages that match an invoice pattern (e.g., subject:invoice filename:pdf). For each email, it checks for attachments, uploads each PDF to a chosen Google Drive folder, and appends a new row to a Google Sheet with useful metadata: received time, sender, subject, filename, Drive link, and IDs. Finally, it marks the original email as read to avoid duplicates. How to set up Open the Config (Set) node and fill in: drive_folder_id (or leave blank for root) spreadsheet_id (from the Sheet URL) sheet_name (e.g., Invoices) Connect credentials for Gmail, Google Drive, and Google Sheets in each node. Adjust the Gmail search query if needed (language/vendor terms). Run once manually to verify data mapping, then activate. Requirements n8n with valid credentials for Gmail, Google Drive, and Google Sheets. A Google Sheet with appropriate headers (or let the workflow write new columns). How to customize the workflow Replace Gmail with IMAP or Microsoft Outlook if you don’t use Gmail; remove the “mark as read” step accordingly. Add parsing (e.g., extract invoice totals or vendor names via PDF/AI nodes) before the Sheets step. Route based on vendor: create subfolders dynamically in Drive and write to different tabs. Notify your team by adding Slack/Email nodes after logging to Sheets. An n8n automation workflow template by Toshiya Minami.

By Stephan Koning

Who it's for Construction and renovation businesses that need to generate detailed quotes from customer inquiries—plasterers, painters, contractors, renovation specialists, or any construction service provider handling quote requests through online forms. What it does Automatically transforms JotForm submissions into professional, itemized construction quotes with complete CRM tracking—no subscription needed (saving €200-500/year). When a customer fills your project request form (specifying wall/ceiling areas, finish types, ceiling heights, wet areas, prep work), the workflow extracts measurements, normalizes service selections, applies intelligent pricing rules from your Supabase catalog, calculates line items with material and labor costs plus proper VAT handling, stores everything in a structured CRM pipeline (customer → project deal → estimate), and generates a branded HTML email ready for delivery. This self-hosted pricing engine replaces paid invoicing software for quote generation, saving thousands over time while eliminating manual takeoffs and quote preparation— from 30-60 minutes to under 30 seconds. How it works Stage 1: JotForm webhook triggers → Parser extracts project data (m² measurements, service types, property details) → Normalize Dutch construction terms to database values → Save raw submission for audit trail Stage 2: Upsert customer record (idempotent on email) → Create project deal → Link to form submission Stage 3: Fetch active pricing rules → Calculate line items based on square meters, service type (smooth plaster vs decorative), ceiling height premiums, property status (new build vs renovation), wet area requirements → Apply conditional logic (high ceilings = price multiplier, prep work charges, finish level) → Group duplicate items → Save estimate header + individual lines Stage 4: Query optimized view (single call, all data) → Generate professional HTML email with logo, itemized services table (description, m², unit price, totals), VAT breakdown, CTA buttons, legal disclaimer Setup requirements Supabase account** (free tier sufficient) - Database for CRM + pricing catalog JotForm account** (free tier works) - Form builder with webhook support Email service** - Gmail, SendGrid, or similar (add your own email node) How to set up 1. Database setup (2 minutes): Run this workflow's "SQL Generator" node to output complete schema Copy output → Paste in Supabase SQL Editor → Click Run Creates 9 tables + 1 optimized view + sample construction services (plastering €21-32/m², painting €12-15/m², ornamental work, ceiling finishes) 2. Credentials: Add Supabase credentials to n8n (Project URL + Service Role Key from Supabase Settings → API) No JotForm credentials needed (uses webhook) 3. JotForm webhook: Clone demo construction form: [jotform stucco planet demo](https://form.jotform.com/252844786304060 )- Form fields: Property type, postcode, services needed, wall/ceiling m², finish level, ornament quantities, molding meters, wet areas, ceiling heights, prep removal, start date, customer contact Settings → Integrations → Webhooks → Add your n8n webhook URL Test with preview submission 4. Customize email: Update company info in "Generate Email HTML" node (logo, business address, contact details, Chamber of Commerce number, VAT number) Adjust colors/branding in HTML template Available in Dutch and English versions How to customize Add your construction services: Edit price_catalog table in Supabase (no code changes): INSERT INTO price_catalog (item_code, name, unit_price, vat_rate, unit_type) VALUES ('DRYWALL_INSTALL', 'Drywall Installation', 18.50, 9, 'm²');. An n8n automation workflow template by Stephan Koning.

By Geoffroy

Meta long-lived user tokens typically expire after ~60 days. If a token expires, any workflows that rely on it start failing. Manual renewal is easy to forget and time consuming. This template monitors the token you store in an n8n Data Table and refreshes it automatically before expiration, so your social automations keep running without surprises or late-night fire drills. Who’s it for Agencies, marketing team, creators managing Meta apps or scheduled social automations Anyone tired of “token expired” errors breaking flows at 2 a.m. How it works / What it does Triggers: scheduled every 10 days, plus a Manual Trigger for testing. Reads: pulls the current token row from your "Meta credential" Data Table (fields: token and expires_at). Decides: IF the token expires in ≤ 15 days, proceed to renewal; otherwise do nothing. Calls the Graph API to get a new access token Updates: computes the new ISO expires_at from expires_in and writes the fresh token + expires_at back to the Data Table. Note: Meta typically issues ~60-day long-lived tokens; confirm for your app. Requirements A Meta app with an initial (short-lived or long-lived) user access token n8n Data Tables enabled (you might need to update your instance to see the option) and a table named "Meta credential" with: ** token (string) ** expires_at (datetime) How to set up Create the data table: name it "Meta credential" with columns "token" and "expires_at". Insert one row with your current token and its expiration date. Configure the IF node "Needs renewal?": keep (or tweak) the 15-day threshold logic. Run once with the Manual Trigger to validate, then enable the Schedule Trigger (10-day cadence by default). How to customize the workflow Change the Schedule Trigger interval and hour. Notify on renewal: Add a Slack/Email node after "Update Record" to alert on token refreshes. An n8n automation workflow template by Geoffroy.

By Jugal

When I was applying for roles, I learned the hard way that a one-size-fits-all resume never wins. I obsessively tailored my resume for each posting, reflecting the exact scope, impact, and stack the team cared about. That’s when the callbacks really started landing from places like Google, Apple, Amazon, and other big tech teams. Personalization worked because recruiters saw immediate alignment: my bullets mirrored their needs. So I built a small automation that flips the script. Instead of you chasing listings, it collects them for you, scores the fit against your resume, drafts a tailored cover letter, and files everything neatly into a Google Sheet then pings you for the best ones. One daily run. No more “I’ll get to it later.” Just a short list of high-signal roles and a ready-to-edit draft. But tailoring takes time and the hardest part was upstream: finding roles that truly matched my skills and narrowing to the best-fit few worth customizing for. That’s why I built a lightweight n8n workflow that does the heavy lifting for me: it pulls fresh roles, scores each one against my resume, drafts a role-specific cover letter, and drops everything into a clean Google Sheet. Below is a quick guide to set it up end-to-end so you can spend less time hunting and more time sending targeted, high-quality applications. Tutorial - Full setup tutorial https://open.substack.com/pub/jugaldb/p/ultimate-job-search-workflow-with?r=18lxy5&utm_campaign=post&utm_medium=web&showWelcomeOnShare=false. An n8n automation workflow template by Jugal.

By Jitesh Dugar

Eliminate weeks of waiting and mountains of paperwork with intelligent expense automation that processes reimbursements in 72 hours instead of 2–3 weeks — delivering 90% reduction in manual processing time. What This Workflow Does Transforms your expense reimbursement process from bureaucratic nightmare to seamless automation: 📝 Captures Expenses – Jotform intake with receipt upload and expense details ⚙️ Policy Validation – Automatically validates against company rules (categories, amount limits) 🚦 Smart Routing – Intelligent approval workflow based on expense amount: < $100 → Auto-approve instantly (compliant expenses only) $100–$500 → Manager approval via Slack notification $500+ → Finance Director approval via Slack notification 🚫 Violation Detection – Flags policy violations with clear rejection reasons 📊 Audit Trail – Complete expense history logged to Google Sheets ✉️ Automated Communication – Professional approval/rejection emails automatically sent Key Features Policy Compliance Engine – Configurable rules for expense categories and amount limits Three-Tier Approval System – Auto-approve, manager review, and director approval paths Real-Time Violation Flagging – Instant detection of non-compliant expenses Comprehensive Audit Logging – Every expense tracked with timestamps and approver details Professional Email Templates – Branded communication for every outcome Slack Integration – Real-time notifications with expense context for quick decisions Zero Manual Processing – Seamless automation from submission to reimbursement Perfect For Finance Teams – Processing 50–200+ expense reports monthly Growing Startups – Scaling operations without adding finance headcount Remote-First Companies – Distributed teams needing async approval workflows Compliance-Focused Organizations – Requiring complete audit trails and policy enforcement SMBs & Enterprises – Companies spending 10–20 hours/week on manual expense processing What You’ll Need Required Integrations Jotform – Expense submission form (free tier works) Create your form for free on Jotform using this link Google Sheets – Audit trail and expense database Gmail – Automated approval/rejection email communication Slack – Manager and Director approval notifications Optional Enhancements QuickBooks/Xero – Automatic expense posting for approved items Google Cloud Vision – OCR for automatic receipt data extraction OpenAI – AI-powered receipt parsing and merchant detection Payment APIs – Direct deposit or check issuance automation Quick Start Import Template – Copy JSON and import into n8n Create Jotform – Build form with fields: Employee name, email, ID, amount, category, merchant, date, description, receipt upload Add Credentials – Jotform, Google Sheets, Gmail, Slack Configure Google Sheet – Replace YOUR_GOOGLE_SHEET_ID with your spreadsheet ID Set Slack Channels – Update manager and director channel IDs in Slack nodes Customize Policies – Edit “Validate Policy” node with your company’s rules: Category limits (meals: $75, travel: $500, office supplies: $200, etc.) Auto-approve threshold (default: $100) Manager approval threshold (default: $500) Test Workflow – Submit test expenses for all scenarios (auto-approve, manager, director, rejection) Deploy & Share – Activate workflow and distribute Jotform link to employees Customization Options 1.Adjust Approval Thresholds – Modify auto-approve limits and escalation amounts 2.Add Approval Levels – Insert additional routing nodes for VP or C-suite approvals 3.Department-Based Routing – Route to different managers based on department 4.Receipt OCR Integration – Add Google Vision + OpenAI for receipt data extraction 5.Accounting System Sync – Connect QuickBooks/Xero for automatic expense posting 6.Duplicate Detection – Flag potential duplicate submissions 7.Budget Monitoring – Add monthly/quarterly budget checks 8.Multi-Currency Support – Add conversion & validation for international expenses 9.Mobile-Optimized Forms – Enhance Jotform for easy phone camera uploads 10.Custom Email Branding – Update templates with your company’s logo and styling Expected Results ⏱️ 72-hour reimbursement vs 2–3 weeks 📉 90% reduction in manual processing time 🧾 100% audit compliance with timestamps & approvers 🗂️ Zero lost receipts – all stored digitally 🧠 Instant policy enforcement – violations caught automatically 😀 Happier employees – fast and transparent reimbursement 🕒 10–15 hours saved weekly for finance teams 🏆 Use Cases 🧑‍💻 Technology Companies Process developer or engineering expenses (software, conferences) with auto-approval under $100. 💼 Sales Organizations Handle high-volume travel expenses — auto-approve meals under $75, route hotels/flights for approval, flag entertainment violations. 🧾 Consulting Firms Manage client reimbursables with project-based routing and full audit trails for client invoicing. 🏥 Healthcare Organizations Track medical reimbursements with department-specific approvals and compliance documentation. 🌍 Remote-First Teams Process global expenses 24/7 with async Slack approvals and instant notifications. Pro Tips Start Conservative – Begin with $50 auto-approve limit, raise later Monthly Policy Reviews – Adjust limits based on expense trends Employee Training – Include policy link in all automated emails Enhanced Slack Approvals – Use Block Kit for approve/reject buttons Receipt Quality Standards – Enforce minimum image resolution Backup Approvers – Add fallback if manager unavailable Executive Dashboard – Connect Sheets → Looker/Tableau Tax Categorization – Align with tax reporting for year-end Benchmark Data – Track average processing time & approval rates Learning Resources This workflow demonstrates: Multi-condition routing with nested IF nodes Policy enforcement using JavaScript logic Audit logging with Google Sheets append/update Async Slack approvals with messaging nodes Email automation using dynamic HTML templates Data normalization for varied Jotform inputs Error handling for invalid submissions Perfect for learning enterprise-grade n8n automation patterns 🎯 Workflow Structure Visualization 📝 Jotform Submission ↓ 🧾 Parse Form Data (Normalize fields) ↓ ⚙️ Validate Against Policy (Check rules) ↓ 🚫 Check Violations? ├─ YES → Set Rejection → Log to Sheets → 📧 Send Rejection Email └─ NO → Route Auto-Approve? ├─ YES (< $100) → ✅ Auto Approve → Log to Sheets → 📧 Send Approval Email └─ NO → Route Manager? ├─ YES ($100-$500) → 📱 Slack Manager → Log to Sheets → ⏳ Await Approval └─ NO ($500+) → 📱 Slack Director → Log to Sheets → ⏳ Await Approval Compliance & Security Features 🧾 Complete Audit Trail – Every expense logged with timestamps 🛡️ Policy Enforcement – Non-compliant submissions blocked early 🔒 Data Privacy – PII secured via n8n credential system ☁️ Receipt Storage – SOC 2–compliant Jotform cloud 👥 Role-Based Access – Slack channel permissions enforced ⚖️ Separation of Duties – Multi-level approval reduces fraud 🚀 Advanced Features to Add 🧠 Receipt OCR with AI – Google Vision + OpenAI for merchant/amount extraction 💵 Accounting Integration – QuickBooks/Xero for GL posting 🏦 Payment Automation – ACH/direct deposit API integration 📱 Mobile App Interface – On-the-go submissions 📈 Budget Monitoring – Real-time spending alerts 📊 Expense Analytics – Automated monthly summaries 🧾 Vendor Management – Flag new vendors for approval 🚗 Mileage Calculator – IRS-compliant reimbursement 💳 Corporate Card Sync – Match credit card transactions 🌐 Per Diem Automation – Geo-based per diem calculation Ready to Transform Your Expense Process? Import this template and start processing reimbursements in hours instead of weeks. Your finance team and employees will thank you! 🎉 Questions or customization needs? The workflow includes detailed sticky notes explaining each section and decision point. An n8n automation workflow template by Jitesh Dugar.

By Marth - Business Automation

Workflow Description: Automated YouTube Short Viral History (Blotato + GPT-4.1) This workflow is a powerful, self-sustaining end-to-end content automation pipeline designed to feed your YouTube Shorts channel with consistent, high-quality, and highly engaging videos focused on "What if history..." scenarios. This solution completely eliminates manual intervention across the creative, production, and publishing stages. It expertly links the creative power of a GPT-4o AI Agent with the video rendering capabilities of the Blotato API, all orchestrated by n8n. How It Works The automation runs through a five-step, scheduled process: Trigger and Idea Generation: The Schedule Trigger starts the workflow (default is 10:00 AM daily). The AI Agent (GPT-4o) acts as a copywriter/researcher, automatically brainstorming a random "What if history..." topic, researching relevant facts, and formulating a viral, hook-driven 60-second video script, along with a title and caption. Visual Production Request: The formatted script is sent to the Blotato API via the Create Video node. Blotato begins rendering the text-to-video short based on the pre-set style parameters (cinematic style, specific voice ID, and AI models). Status Check and Wait: The Wait node pauses the workflow, and the Get Video node continually checks the Blotato system until the video rendering status is confirmed as done. Media Upload: The completed video file is uploaded to the Blotato media library using an HTTP Request node, preparing it for publishing. Automated Publishing: The final YT Post node (another HTTP Request to the Blotato API) automatically publishes the video to your linked YouTube channel, using the video URL and the AI-generated title and short caption. Set Up Steps To activate and personalize this powerful content pipeline in n8n, follow these steps: OpenAI Credential: Ensure your OpenAI API key credential is created and connected to the Brainstorm Idea node (Language Model). The workflow uses GPT-4o by default. Blotato API Key: Obtain your Blotato API Key. Open the Prepare Video node and manually insert your Blotato API Key into the blotato_api_key field. YouTube Account ID: Find the Account ID (or Channel ID) for the YouTube channel you want to post to. Open the Prepare for Publish node and manually insert your YouTube Account ID into the youtube_id field. Customize Video Style (Optional): If desired, adjust the visual aesthetic by modifying parameters in the Prepare Video node, such as: voiceId: To change the video narrator. style: To change the visual theme (e.g., from cinematic to documentary). text_to_image_model and image_to_video_model: To change the underlying AI generation models. Activate Workflow: Save the workflow and toggle the main switch to Active. The first video will be created and published on the next scheduled run. An n8n automation workflow template by Marth - Business Automation.

By Marth - Business Automation

Automated Instagram Carousel Post (Blotato + GPT-4.1) This workflow is an end-to-end solution for automating the creation and publishing of highly engaging Instagram Carousel content on a recurring schedule. It leverages the intelligence of an AI Agent (GPT-4.1) for idea generation and sharp copywriting, combined with the visual rendering capabilities of Blotato, all orchestrated by the n8n automation platform. The core objective is to drastically cut content production time, enabling creators and marketing teams to consistently generate high-impact, scroll-stopping educational or inspirational content without manual intervention. How It Works The workflow executes in five automated phases: 1. Trigger and Idea Generation The workflow starts with the Schedule Trigger node, running at your specified time interval (e.g., daily). It takes the initial subject from the Topic node and feeds it to the Topic1 AI Agent. This agent is specifically prompted to create a short, viral hook/title (max. 6 words) in the style of confident, tactical copywriters (like Alex Hormozi), maximizing the content's initial draw. 2. Content Creation and Output Structuring The viral hook is then passed to the AI Agent Carousel Maker. This agent uses the GPT-4.1 model, following strict system instructions, to generate all necessary content elements in a structured JSON format: Punchy, concise text for each Carousel slide. A long, detailed Instagram Caption with explanations and a CTA. A short final title for internal reference. 3. Visual Rendering (Blotato Tool) The slide text output is sent to the Simple tweet cards monocolor (Blotato Tool) node. Blotato acts as a graphic generation API, rendering the text onto a chosen template to create a series of Carousel images (using the 4:5 aspect ratio). This replaces the need for manual design work in tools like Canva. 4. Status Check and Retry Mechanism Visual rendering takes time, so the workflow pauses: The Wait node holds the execution for 3 minutes. The Get carousel node retrieves the image generation status using the ID provided by the previous Blotato node. The If carousel ready node checks if the status is done. If not, the flow is routed back to the Wait node, implementing a built-in simple retry mechanism until the visuals are complete. 5. Final Posting Once the status is confirmed as done, the workflow proceeds to the final step: The Instagram [BLOTATO] node uses the media URLs retrieved from Blotato and the long caption from the AI Agent to automatically publish the entire Carousel post (multiple images plus text) to your linked Instagram account. Set Up Steps To successfully activate and personalize this n8n workflow, follow these steps: Step 1: Import and Connect Credentials Import Workflow: Import the provided JSON file (Automated Instagram Carousel Post with Blotato + Gpt 4.1.json) into your n8n instance. OpenAI Credentials: Ensure you have valid OpenAI API credentials connected to the OpenAI Chat Model node. Blotato Credentials: Ensure your valid Blotato API credentials are connected to all three Blotato-related nodes (Simple tweet cards monocolor, Get carousel, and Instagram [BLOTATO]). Step 2: Configure Workflow Inputs Set Topic: Open the Topic node. Change the default initial topic expression =Top ai tools for finance to any general subject matter you want your Carousels to cover. Set Schedule: Open the Schedule Trigger node and configure the Rule to define how often you want the content to be created and posted (e.g., set it to run Every Day at a specific time). Step 3: Personalize Content and Visuals Customize AI Persona: Open the AI Agent Carousel Maker node. Review and modify the long System Message to refine the AI's output: Adjust the # ROLE and # STYLE sections to match your brand's voice (e.g., change the Alex Hormozi style to a more formal, academic tone if needed). Do not change the structure defined in # OUTPUT as this JSON format is essential for downstream nodes. Personalize Visuals: Open the Simple tweet cards monocolor (Blotato Tool) node. Under templateInputs, customize fields like authorName, handle, and profileImage URLs to ensure the generated visuals are consistent with your personal or brand identity. Step 4: Final Posting Setup Select Instagram Account: Open the Instagram [BLOTATO] node. In the accountId parameter, use the dropdown list to select the specific Instagram account that is connected via your Blotato service. Activate: Once all steps are complete, save the workflow and toggle the main switch to Active to allow the Schedule Trigger to begin running the automation. An n8n automation workflow template by Marth - Business Automation.

By Daniel Nkencho

Transform any website into a structured knowledge repository with this intelligent crawler that extracts hyperlinks from the homepage, intelligently filters images and content pages, and aggregates full Markdown-formatted content—perfect for fueling AI agents or building comprehensive company dossiers without manual effort. 📋 What This Template Does This advanced workflow acts as a lightweight web crawler: it scrapes the homepage to discover all internal links (mimicking a sitemap extraction), deduplicates and validates them, separates image assets from textual pages, then fetches and converts non-image page content to clean Markdown. Results are seamlessly appended to Google Sheets for easy analysis, export, or integration into vector databases. Automatically discovers and processes subpage links from the homepage Filters out duplicates and non-HTTP links for efficient crawling Converts scraped content to Markdown for AI-ready formatting Categorizes and stores images, links, and full content in a single sheet row per site 🔧 Prerequisites Google account with Sheets access for data storage n8n instance (cloud or self-hosted) Basic understanding of URLs and web links 🔑 Required Credentials Google Sheets OAuth2 API Setup Go to console.cloud.google.com → APIs & Services → Credentials Click "Create Credentials" → Select "OAuth client ID" → Choose "Web application" Add authorized redirect URIs: https://your-n8n-instance.com/rest/oauth2-credential/callback (replace with your n8n URL) Download the client ID and secret, then add to n8n as "Google Sheets OAuth2 API" credential type During setup, grant access to Google Sheets scopes (e.g., spreadsheets) and test the connection by listing a sheet ⚙️ Configuration Steps Import the workflow JSON into your n8n instance In the "Set Website" node, update the website_url value to your target site (e.g., https://example.com) Assign your Google Sheets credential to the three "Add ... to Sheet" nodes Update the documentId and sheetName in those nodes to your target spreadsheet ID and sheet name/ID Ensure your sheet has columns: "Website", "Links", "Scraped Content", "Images" Activate the workflow and trigger manually to test scraping 🎯 Use Cases Knowledge base creation: Crawl a company's site to aggregate all content into Sheets, then export to Notion or a vector DB for internal wikis AI agent training: Extract structured Markdown from industry sites to fine-tune LLMs on domain-specific data like legal docs or tech blogs Competitor intelligence: Build dossiers by crawling rival websites, separating assets and text for SEO audits or market analysis Content archiving: Preserve dynamic sites (e.g., news portals) as static knowledge dumps for compliance or historical research ⚠️ Troubleshooting No links extracted: Verify the homepage has tags; test with a simple site like example.com and check HTTP response in executions Sheet update fails: Confirm column names match exactly (case-sensitive) and credential has edit permissions; try a new blank sheet Content truncated: Google Sheets limits cells to ~50k chars—adjust the .slice(0, 50000) in "Add Scraped Content to Sheet" or split into multiple rows Rate limiting errors: Add a "Wait" node after "Scrape Links" with 1-2s delay if the site blocks rapid requests. An n8n automation workflow template by Daniel Nkencho.

By Iternal Technologies

Blockify® Technical Manual Data Optimization Workflow Blockify Optimizes Data for Technical Manual RAG and Agents - Giving Structure to Unstructured Data for ~78X Accuracy, when pairing Blockify Ingest and Blockify Distill Learn more at https://iternal.ai/blockify Get Free Demo API Access here: https://console.blockify.ai/signup Read the Technical Whitepaper here: https://iternal.ai/blockify-results See example Accuracy Comparison here: https://iternal.ai/case-studies/medical-accuracy/ Blockify is a data optimization tool that takes messy, unstructured text, like hundreds of sales‑meeting transcripts or long proposals, and intelligently optimizes the data into small, easy‑to‑understand "IdeaBlocks." Each IdeaBlock is just a couple of sentences in length that capture one clear idea, plus a built‑in contextualized question and answer. With this approach, Blockify improves accuracy of LLMs (Large Language Models) by an average aggregate 78X, while shrinking the original mountain of text to about 2.5% of its size while keeping (and even improving) the important information. When Blockify's IdeaBlocks are compared with the usual method of breaking text into equal‑sized chunks, the results are dramatic. Answers pulled from the distilled IdeaBlocks are roughly 40X more accurate, and user searches return the right information about 52% more accurate. In short, Blockify lets you store less data, spend less on computing, and still get better answers- turning huge documents into a concise, high‑quality knowledge base that anyone can search quickly. Blockify works by processing chunks of text to create structured data from an unstructured data source. Blockify® replaces the traditional "dump‑and‑chunk" approach with an end‑to‑end pipeline that cleans and organizes content before it ever hits a vector store. Admins first define who should see what, then the system ingests any file type—Word, PDF, slides, images—inside public cloud, private cloud, or on‑prem. A ​context‑aware splitter finds natural breaks, and a series of specially developed Blockify LLM model turns each segment into a draft IdeaBlock. GenAI systems fed with this curated data return sharper answers, hallucinate far less, and comply with security policies out of the box. The result: higher trust, lower operating cost, and a clear path to enterprise‑scale RAG without the cleanup headaches that stall most AI rollouts. An n8n automation workflow template by Iternal Technologies.

By 8Automator

Automatically create and publish ready-to-post social media news updates — all powered by AI. This workflow turns any RSS feed into professional, branded posts, complete with visuals and captions. Use cases include automating news updates, sharing industry insights, or maintaining an active social presence without manual work. Good to know Fully automated end-to-end publishing — from RSS feed to social post Uses JsonCut for dynamic image composition (backgrounds, text overlays, logos) Publishes directly to Instagram (or other channels) via Blotato Utilizes OpenAI GPT-5 for post text and image prompt generation Polling mechanism checks job status every 3 seconds Setup time: under 10 minutes once credentials are in place How it works The RSS Trigger monitors any RSS feed for new content. OpenAI GPT-5 rewrites the headline and creates a short, social-friendly post caption. An AI image prompt is generated to match the article’s topic and mood. JsonCut combines the background, logo, and headline text into a branded image. Once the image is ready, Blotato uploads and publishes the post directly to Instagram (or other connected platforms). The process runs completely automatically — no human input required after setup. How to use Import the workflow into your n8n instance. Configure your RSS feed URL(s). Add your JsonCut, Blotato, and OpenAI credentials. Activate the workflow — it will automatically generate and post new content whenever your RSS source updates. Requirements Free account at jsoncut.com Account at blotato.com (paid service — can be replaced with any social media API or publishing platform) API keys for both services: JsonCut API Key via app.jsoncut.com Blotato API Key via www.blotato.com OpenAI credential** (GPT-5 or compatible model) RSS Feed URL** (e.g. from a news site, blog, or press page) Setup steps Sign up for a free account at app.jsoncut.com. If you use Blotato, create an account at blotato.com and generate an API key. In n8n, add: JsonCut API Key (HTTP Header Auth, header: x-api-key) Blotato API credential (optional — can be replaced) OpenAI credential for GPT-5 Replace the example RSS URL in the RSS Feed Trigger node with your own. Activate the workflow — it will start monitoring, generating, and posting automatically. Customising this workflow You can easily adjust: The image layout and branding (in the “Create JsonCut Job” node) The tone or length of social captions (in the “Create Instagram Text” node prompt) The publishing platform — replace Blotato with another integration (e.g. Buffer, Hootsuite, or native social API) Posting frequency via the RSS trigger interval For advanced customization, check out: JsonCut Documentation JsonCut Image Generation Examples Blotato Website n8n Documentation. An n8n automation workflow template by 8Automator.

By Cooper

DMARC Reporter Gmail and Yahoo send DMARC reports as .zip or .gz xml attachments that can be hard to read. This workflow unpacks them on a schedule, turns the data into a simple table, and emails you an easy-to-read report. DMARC insights at a glance: Confirm that your published policy is correct and consistent. Quickly spot unknown or suspicious IPs trying to send as you. Distinguish between legitimate high-volume senders (e.g. your ESP) and one-off or small-scale abuse. Makes it easy to confirm your legitimate servers are authenticating correctly, and to detect spoofed mail that fails DKIM/SPF. Who is this For? Email Marketing Team Mailchimp, Sensorpro, Omnisend users Compliance Team Customize: Adjust the Gmail node to include other DMARC reporters by changing the search parms. If not using Gmail you can use any of the n8n email nodes. To keep a record, add an Airtable node after the Set node. An n8n automation workflow template by Cooper.

By Jitesh Dugar

👤 Who’s it for This workflow is designed for employees who need to submit expense claims for business trips. It automates the process of extracting data from receipts/invoices, logging it to a Google Sheet, and notifying the finance team via email. Ideal users: Employees submitting business trip expense claims HR or Admins reviewing travel-related reimbursements Finance teams responsible for processing claims ⚙️ How it works / What it does Employee submits a form with trip information (name, department, purpose, dates) and uploads one or more receipts/invoices (PDF). Uploaded files are saved to Google Drive for record-keeping. Each PDF is passed to a DocClaim Assistant agent, which uses GPT-4o and a structured parser to extract structured invoice data. The data is transformed and formatted into a standard JSON structure. Two parallel paths are followed: Invoice records are appended to a Google Sheet for centralized tracking. A detailed HTML email summarizing the trip and expenses is generated and sent to the finance department for claim processing. 🛠 How to set up Create a form to capture: Employee Name Department Trip Purpose From Date / To Date Receipt/Invoice File Upload (multiple PDFs) Configure file upload node to store files in a specific Google Drive folder. Set up DocClaim Agent using: GPT-4o or any LLM with document analysis capability Output parser for standardizing extracted receipt data (e.g., vendor, total, tax, date) Transform extracted data into a structured claim record (Code Node). Path 1: Save records to a Google Sheet (one row per expense). Path 2: Format the employee + claim data into a dynamic HTML email Use Send Email node to notify the finance department (e.g., finance@yourcompany.com) ✅ Requirements Jotform account with expense form setup Sign up for free here n8n running with access to: Google Drive API (for file uploads) Google Sheets API (for logging expenses) Email node (SMTP or Gmail for sending) GPT-4o or equivalent LLM with document parsing ability PDF invoices with clear formatting Shared Google Sheet for claim tracking Optional: Shared inbox for finance team 🧩 How to customize the workflow Add approval steps**: route the email to a manager before finance Attach original PDFs**: include uploaded files in the email as attachments Localize for other languages**: adapt form labels, email content, or parser prompts Sync to ERP or accounting system**: replace Google Sheet with QuickBooks, Xero, etc. Set limits/validation**: enforce max claim per trip or required fields before submission Auto-tag expenses**: add categories (e.g., travel, accommodation) for better reporting. An n8n automation workflow template by Jitesh Dugar.

By Jitesh Dugar

Revolutionize university admissions with intelligent AI-driven application evaluation that analyzes student profiles, calculates eligibility scores, and automatically routes decisions - saving 2.5 hours per application and reducing decision time from weeks to hours. 🎯 What This Workflow Does Transforms your admissions process from manual application review to intelligent automation: 📝 Captures Applications - Jotform intake with student info, GPA, test scores, essay, extracurriculars 🤖 AI Holistic Evaluation - OpenAI analyzes academic strength, essay quality, extracurriculars, and fit 🎯 Intelligent Scoring - Evaluates students using 40% academics, 25% extracurriculars, 20% essay, 15% fit (0-100 scale) 🚦 Smart Routing - Automatically routes based on AI evaluation: Auto-Accept (95-100)**: Acceptance letter with scholarship details → Admin alert → Database Interview Required (70-94)**: Interview invitation with scheduling link → Admin alert → Database Reject (<70)**: Respectful rejection with improvement suggestions → Database 💰 Scholarship Automation - Calculates merit scholarships ($5k-$20k+) based on eligibility score 📊 Analytics Tracking - All applications logged to Google Sheets for admissions insights ✨ Key Features AI Holistic Evaluation: Comprehensive analysis weighing academics, extracurriculars, essays, and institutional fit Intelligent Scoring System: 0-100 eligibility score with automated categorization and scholarship determination Structured Output: Consistent JSON schema with academic strength, admission likelihood, and decision reasoning Automated Communication: Personalized acceptance, interview, and rejection letters for every applicant Fallback Scoring: Manual GPA/SAT scoring if AI fails - ensures zero downtime Admin Alerts: Instant email notifications for exceptional high-scoring applicants (95+) Comprehensive Analytics: Track acceptance rates, average scores, scholarship distribution, and applicant demographics Customizable Criteria: Easy prompt editing to match your institution's values and requirements 💼 Perfect For Universities & Colleges: Processing 500+ undergraduate applications per semester Graduate Programs: Screening master's and PhD applications with consistent evaluation Private Institutions: Scaling admissions without expanding admissions staff Community Colleges: Handling high-volume transfer and new student applications International Offices: Evaluating global applicants 24/7 across all timezones Scholarship Committees: Identifying merit scholarship candidates automatically 🔧 What You'll Need Required Integrations Jotform - Application form with student data collection (free tier works) Create your form for free on Jotform using this link Create your application form with fields: Name, Email, Phone, GPA, SAT Score, Major, Essay, Extracurriculars OpenAI API - GPT-4o-mini for cost-effective AI evaluation (~$0.01-0.05 per application) Gmail - Automated applicant communication (acceptance, interview, rejection letters) Google Sheets - Application database and admissions analytics Optional Integrations Slack - Real-time alerts for exceptional applicants Calendar APIs - Automated interview scheduling Student Information System (SIS) - Push accepted students to enrollment system Document Analysis Tools - OCR for transcript verification 🚀 Quick Start Import Template - Copy JSON and import into n8n (requires LangChain support) Create Jotform - Use provided field structure (Name, Email, GPA, SAT, Major, Essay, etc.) Add API Keys - OpenAI, Jotform, Gmail OAuth2, Google Sheets Customize AI Prompt - Edit admissions criteria with your university's specific requirements and values Set Score Thresholds - Adjust auto-accept (95+), interview (70-94), reject (<70) cutoffs if needed Personalize Emails - Update templates with your university branding, dates, and contact info Create Google Sheet - Set up columns: id, Name, Email, GPA, SAT Score, Major, Essay, Extracurriculars Test & Deploy - Submit test application with pinned data and verify all nodes execute correctly 🎨 Customization Options Adjust Evaluation Weights: Change academics (40%), extracurriculars (25%), essay (20%), fit (15%) percentages Multiple Programs: Clone workflow for different majors with unique evaluation criteria Add Document Analysis: Integrate OCR for transcript and recommendation letter verification Interview Scheduling: Connect Google Calendar or Calendly for automated booking SIS Integration: Push accepted students directly to Banner, Ellucian, or PeopleSoft Waitlist Management: Add conditional routing for borderline scores (65-69) Diversity Tracking: Include demographic fields and bias detection in AI evaluation Financial Aid Integration: Automatically calculate need-based aid eligibility alongside merit scholarships 📈 Expected Results 90% reduction in manual application review time (from 2.5 hours to 15 minutes per application) 24-48 hour decision turnaround time vs 4-6 weeks traditional process 40% higher yield rate - faster responses increase enrollment commitment 100% consistency - every applicant evaluated with identical criteria Zero missed applications - automated tracking ensures no application falls through cracks Data-driven admissions - comprehensive analytics on applicant pools and acceptance patterns Better applicant experience - professional, timely communication regardless of decision Defensible decisions - documented scoring criteria for accreditation and compliance 🏆 Use Cases Large Public Universities Screen 5,000+ applications per semester, identify top 20% for auto-admit, route borderline to committee review. Selective Private Colleges Evaluate 500+ highly competitive applications, calculate merit scholarships automatically, schedule interviews with top candidates. Graduate Programs Process master's and PhD applications with research experience weighting, flag candidates for faculty review, automate fellowship awards. Community Colleges Handle high-volume open enrollment while identifying honors program candidates and scholarship recipients instantly. International Admissions Evaluate global applicants 24/7, account for different GPA scales and testing systems, respond same-day regardless of timezone. Rolling Admissions Provide instant decisions for early applicants, fill classes strategically, optimize scholarship budget allocation. 💡 Pro Tips Calibrate Your AI: After 100+ applications, refine evaluation criteria based on enrolled student success A/B Test Thresholds: Experiment with score cutoffs (e.g., 93 vs 95 for auto-admit) to optimize yield Build Waitlist Pipeline: Keep 70-84 score candidates engaged for spring enrollment or next year Track Source Effectiveness: Add UTM parameters to measure which recruiting channels deliver best students Committee Review: Route 85-94 scores to human admissions committee for final review Bias Audits: Quarterly review of AI decisions by demographic groups to ensure fairness Parent Communication: Add parent/guardian emails for admitted students under 18 Financial Aid Coordination: Sync scholarship awards with financial aid office for packaging 🎓 Learning Resources This workflow demonstrates: AI Agents with structured output** - LangChain integration for consistent JSON responses Multi-stage conditional routing** - IF nodes for three-tier decision logic Holistic evaluation** - Weighted scoring across multiple dimensions Automated communication** - HTML email templates with dynamic content Real-time notifications** - Admin alerts for high-value applicants Analytics and data logging** - Google Sheets integration for reporting Fallback mechanisms** - Manual scoring when AI unavailable Perfect for learning advanced n8n automation patterns in educational technology! 🔐 Compliance & Ethics FERPA Compliance: Protects student data with secure credential handling Fair Admissions: Documented criteria eliminate unconscious bias Human Oversight: Committee review option for borderline cases Transparency: Applicants can request evaluation criteria Appeals Process: Structured workflow for decision reconsideration Data Retention: Configurable Google Sheets retention policies 📊 What Gets Tracked Application submission date and time Complete student profile (GPA, test scores, major, essay, activities) AI eligibility score (0-100) and decision category Academic strength rating (excellent/strong/average) Scholarship eligibility and amount ($0-$20,000+) Admission likelihood (high/medium/low) Decision outcome (accepted/interview/rejected) Email delivery status and open rates Time from application to decision Ready to transform your admissions process? Import this template and start evaluating applications intelligently in under 1 hour. Questions or customization needs? The workflow includes detailed sticky notes explaining each section and comprehensive fallback logic for reliability. An n8n automation workflow template by Jitesh Dugar.