Browse 13,012 Workflows

By Abdullah Alshiekh

What Problem Does it Solve This workflow automates the process of finding and collecting job postings from LinkedIn, eliminating the need for manual job searching. It’s designed to save time and ensure you don’t miss out on new opportunities by automatically populating a spreadsheet with key job details. Key Features Automated Data Collection:** The workflow pulls job posts from a LinkedIn search via an RSS feed. Intelligent Data Extraction:** It scrapes the full job description and uses AI to summarize the key benefits and job responsibilities into a concise format. Centralized Database:** All collected and processed information is automatically saved to a Google Sheet, providing a single source of truth for your job search. How It Works The workflow starts when manually triggered. It reads the job posts from a given RSS feed, processing each one individually. For each job, it fetches the full webpage content to extract structured data. This data is then cleaned and passed to an AI model, which generates a brief summary of the job and its benefits. Finally, a new row is either added or updated in a Google Sheet with all the collected details, including the job title, company name, and AI-generated summary. Configuration & Customization This workflow is highly customizable to fit your specific needs. RSS Feed:** To get started, you'll need to provide the RSS feed URL for your desired LinkedIn job search. We can help you set this up. AI Model:** The workflow uses Google Gemini by default, but it can be adjusted to work with other AI platforms. Data Destination:** The output is configured to a Google Sheet, but it can easily be changed to a different platform like Notion or a CRM. AI Prompting:** The AI's instructions are customizable, so you can tailor the output to extract different information or match a specific tone. If you need any help Get In Touch. An n8n automation workflow template by Abdullah Alshiekh.

By Issam AGGOUR

AI-Powered GitHub Issue to Jira Ticket Automation Bridge the gap between your development and project management workflows with this intelligent n8n template. This isn't just a simple sync; it uses an AI agent to analyze, classify, and intelligently route new GitHub issues into the correct Jira ticket type, saving you countless hours of manual triage. 🚀 Key Features AI-Powered Issue Classification:** Leverages an AI Agent (powered by OpenAI) to analyze the content of a new GitHub issue and determine its type (e.g., bug, task, improvement). Intelligent Routing:** Automatically creates the corresponding ticket type in Jira. Bugs in GitHub become Bugs in Jira; other issues become Tasks. Seamless Integration:** Triggers instantly when a new issue is created in your specified GitHub repository. Rich Data Transfer:** Migrates the issue title and body directly into the Jira ticket description for full context. Structured AI Output:** Uses a structured output parser to ensure the AI's classification is reliable and consistent. Beginner-Friendly & Educational:** The workflow is annotated with sticky notes, explaining each step of the process, making it a great tool for learning how to use AI in n8n. ⚙️ How It Works The workflow is designed for clarity and power, moving from issue creation to ticket generation in four automated steps. 1. Trigger: New GitHub Issue The GitHub Trigger node constantly listens for new issues being created in your designated repository. Once an issue is opened, the workflow springs into action. 2. Analyze: AI Classification The issue's title and body are passed to an AI Agent. Using a prompt designed for classification and an OpenAI Chat Model, the agent determines if the issue is a bug, task, or another category. A Structured Output Parser ensures the AI returns clean, usable JSON data (e.g., {"type": "bug"}). 3. Route: Conditional Logic An IF node checks the structured output from the AI agent. If the type is "bug," the workflow proceeds down the "bug" path. Otherwise, it follows the default path for "tasks." 4. Create: Jira Ticket Generation Depending on the route, the corresponding Jira node is activated. A new ticket is created in your specified Jira project with the appropriate issue type (Bug or Task) and includes the full context from the original GitHub issue. 🛠️ Setup Steps & Credentials To get this AI-powered workflow running, you'll need to configure a few credentials: GitHub: Create a GitHub credential in n8n. In the GitHub Trigger node, select your credential and specify the owner (your GitHub username or organization) and the repository you want to monitor. OpenAI: Obtain an API Key from platform.openai.com. Create an OpenAI credential in n8n. In the OpenAI Chat Model node, select your newly created credential. You can also experiment with different models like gpt-4.1-mini for speed or gpt-4o for higher accuracy. Jira: Create a Jira API token from your Atlassian account settings. Create a Jira credential in n8n using your email, API token, and Atlassian domain. In both the Create Jira Ticket (Bug) and Create Jira Ticket (Task) nodes, select your Jira credential and set your target project key. 💡 Customization & Learning This workflow is a powerful starting point. Here are a few ways you can customize it and learn more: Expand Classification:** Modify the AI Agent's prompt and the IF node to handle more issue types, like improvement, documentation, or feature-request. Add More Data:** Enhance the Jira nodes to include labels, assignees, or priority levels based on the AI's output or the original GitHub issue's properties. Swap AI Models:** Try different language models by replacing the OpenAI node with one for Google Gemini, Anthropic Claude, or others supported by n8n. Error Handling:** Add a path for what to do if the AI fails to classify an issue, such as sending a notification to a Slack channel for manual review. 📋 Requirements An active n8n instance. GitHub API credentials. OpenAI API credentials. Jira API credentials. An n8n automation workflow template by Issam AGGOUR.

By Artur

Who’s it for Problem: Your ads and GA4 often optimize to shallow web events (form fills), while the real value sits in Pipedrive (Qualified, Closed Won). That gap means bidding chases cheap leads instead of revenue. Solution: This template turns Pipedrive deal milestones into server-side GA4 events (via Measurement Protocol), matched to the original visitor by client_id—no external database. You mark them as Key events in GA4 and, when ready, import them into Google Ads. Business value: Ads can optimize on actual CRM outcomes with value (and currency), improving CAC/ROAS and reducing lead spam. Everything stays GA4-centric, consent-aware, and deduped with deterministic event_id, so you get reliable attribution without building a custom Ads integration. If you’re serious about scaling paid spend toward high-quality, high-value deals, this is the missing link. This is not plug-and-play. Expect \~2 hours of developer work to integrate: What it does On Deal Updated, the workflow checks for target stages (e.g., Qualified, Closed Won), fetches the linked Person’s client\_id, builds a GA4 Measurement Protocol event (with value, currency, deterministic event_id), and posts it server-side. Success updates deal-level dedupe flags; failures are logged to a Pipedrive Note. Credentials use n8n Credentials—no hardcoded secrets. How it works (high level) A Pipedrive trigger listens for stage changes → an eligibility check gates sends → a payload builder composes the GA4 event → an HTTP call posts to GA4. Sticky notes in the canvas explain the whole setup and what to edit. Requirements GA4 installed on your site; GA4 Measurement ID + API Secret (same data stream); Pipedrive Person field for client_id, optional consent_granted; Pipedrive Deal booleans for dedupe; n8n credentials configured (no secrets in nodes). How to customize the workflow Change which stages send events and the event names. Adjust value logic (e.g., margin- or probability-weighted). Choose skip-on-no-consent vs. non_personalized_ads: true. Add extra params (deal_id, pipeline_stage, etc.) to GA4 as custom dimensions (event-scoped). Troubleshooting & debugging If client_id is null: GA4 not initialized yet, consent denied, GTM var not firing, or adblockers—fix site capture first. If GA4 shows events in DebugView but Ads import is empty: events not marked as Key events, GA4↔Ads not linked/imported, or wrong stream/secret pairing. Use https://www.google-analytics.com/debug/mp/collect only for payload validation; it won’t verify your API secret. Final sends go to /mp/collect. An n8n automation workflow template by Artur.

By Dahiana

This template demonstrates how to build an AI-powered name generator that creates realistic names perfect for UX/UI designers, developers, and content creators. Use cases: User persona creation, mockup development, prototype testing, customer testimonials, team member listings, app interface examples, website content, accessibility testing, and any scenario requiring realistic placeholder names. How it works AI-Powered Generation:** Uses any LLM to generate names based on your specifications Customizable Parameters:** Accepts gender preferences, name count, and optional reference names for style matching UX/UI Optimized:** Names are specifically chosen to work well in design mockups and prototypes Smart Formatting:** Returns clean JSON arrays ready for integration with design tools and applications Reference Matching:** Can generate names similar in style to a provided reference name How to set up Replace "Dummy API" credentials with your preferred language model API key Update webhook path and authentication as needed for your application Test with different parameters: gender (masculine/feminine/neutral), count (1-20), reference_name (optional) Integrate webhook URL with your design tools, Bubble apps, or other platforms Requirements LLM API access (OpenAI, Claude, or other language model) n8n instance (cloud or self-hosted) Platform capable of making HTTP POST requests API Usage POST to webhook with JSON body: { "gender": "masculine", "count": 5, "reference_name": "Alex Chen" // optional } Response: { "success": true, "names": ["Marcus Johnson", "David Kim", "Sofia Rodriguez", "Chen Wei", "James Wilson"], "count": 5 } How to customize Modify AI prompt for specific naming styles or regions Add additional parameters (age, profession, cultural background) Connect to databases for persistent name storage Integrate with design tools APIs (Figma, Sketch, Adobe XD) Create batch processing for large mockup projects. An n8n automation workflow template by Dahiana.

By Dahiana

YouTube Transcript Extractor This n8n template demonstrates how to extract transcripts from YouTube videos using two different approaches: automated Google Sheets monitoring and direct webhook API calls. Use cases: Content creation, research, accessibility, meeting notes, content repurposing, SEO analysis, or building transcript databases for analysis. How it works Google Sheets Integration:** Monitor a sheet for new YouTube URLs and automatically extract transcripts Direct API Access:** Send YouTube URLs via webhook and get instant transcript responses Smart Parsing:** Extracts video ID from various YouTube URL formats (youtube.com, youtu.be, embed) Rich Metadata:** Returns video title, channel, publish date, duration, and category alongside transcript Fallback Handling:** Gracefully handles videos without available transcripts Two Workflow Paths Automated Sheet Processing: Add URLs to Google Sheet → Auto-extract → Save results to sheet Webhook API: Send POST request with video URL → Get instant transcript response How to set up Replace "Dummy YouTube Transcript API" credentials with your YouTube Transcript API key Create your own Google Sheet with columns: "url" (input sheet) and "video title", "transcript" (results sheet) Update Google Sheets credentials to connect your sheets Test each workflow path separately Customize the webhook path and authentication as needed Requirements YouTube Transcript API access (youtube-transcript.io or similar) Google Sheets API credentials (for automated workflow) n8n instance (cloud or self-hosted) YouTube videos How to customize Modify transcript processing in the Code nodes Add additional metadata extraction Connect to other storage solutions (databases, CMS) Add text analysis or summarization steps Set up notifications for new transcripts. An n8n automation workflow template by Dahiana.

By Oriol Seguí

This is an n8n workflow designed to implement an advanced AI chatbot with real-time conversation and search capabilities. Configured with a minimalist European design, this chatbot is ready to be integrated into any website. What Does This Workflow Do? The workflow uses a combination of nodes to create a complete chatbot: Chat Trigger: Starts the process when a user sends a message. The configuration includes a customized visual design (minimalist European CSS), welcome messages, and titles. AI Agent: Acts as the chatbot's brain. It coordinates interaction with the language model, memory, and tools to generate intelligent responses. Conversational Memory: Allows the chatbot to remember the context of the conversation, providing a smoother and more coherent experience. Language Model (GPT): Generates the chat responses. Search Tool: Enables the AI agent to search for information on the web and answer questions it doesn't already know. Respond to Chat: Sends the final response back to the user. Use Cases Customer Support**: Answers frequently asked questions and transfers complex conversations to a human agent. Virtual Assistant**: Provides information about products or services, helps users navigate your website, or completes simple tasks. Content Generator**: Serves as an assistant for generating ideas, writing drafts, or summarizing texts. Who Is This For? This workflow is ideal for: Businesses and developers** looking for a versatile and customizable chatbot solution without having to build it from scratch. Business owners** who want to improve customer service and user interaction in an automated way. Curious individuals** and AI enthusiasts who want to explore how chatbots are built and experiment with their own configurations. This workflow includes detailed documentation that explains how each node works and how to customize it for your needs. An n8n automation workflow template by Oriol Seguí.

By Jaruphat J.

⚠️ Note: All sensitive credentials should be set via n8n Credentials or environment variables. Do not hardcode API keys in nodes. Who’s it for Marketers, creators, and automation builders who want to generate UGC-style ad images and short videos automatically from a Google Sheet. Ideal for e‑commerce SKUs, agencies, or teams that need many variations quickly. What it does (Overview) This template turns a spreadsheet row into ad images and optionally 5–8s videos. Zone 0 — Image-only pipeline (Gemini/OpenRouter)**: Creates an ad image from a product link and prompt, uploads it to Drive, and updates the sheet (no video step). Zone 1 — Create image (Fal nano‑banana) + prepare for video**: Generates an image via Fal.ai, polls status, fetches URL, then analyzes the image with LLM to prepare scene prompts. Zone 2 — Generate video (WAN2.2 & Veo3)**: Uses the generated image + structured scene prompts to create short clips, uploads them to Drive, and writes the video URL back to the sheet. Requirements Fal.ai API key** (env: FAL_KEY) Google Sheets / Google Drive** OAuth2 credentials OpenAI / Gemini (via OpenRouter)** for image analysis or alternative image generation A Google Sheet with columns, e.g.: product | presenter | prompt | img_url | video_url Google Drive files set to Anyone with link → Viewer so APIs can fetch them How to set up Credentials: Add Google Sheets + Google Drive (OAuth2), Fal.ai (Header Auth with Authorization: Key {{$env.FAL_KEY}}), and OpenAI/OpenRouter. Google Sheet: Create the columns above. Paste product image Drive links (the workflow converts them to direct links automatically). Import the workflow: Use the provided JSON. Confirm node credentials resolve. Run: Start with Zone 0 to verify image-only flow, then test Zone 1 + Zone 2 for full image→video. Zone 0 — Create Ad Image (Image-only) This path is for creating just an image and stopping. It reads the Gemini tab in the Sheet, generates an image via OpenRouter/Gemini, converts base64 to a file, uploads to Drive, and writes back img_url. Key nodes Get Data1 (Google Sheets)** → reads Gemini tab setImgeURL (Set)** → converts Drive URLs to direct (uc?export=view&id=...) CreateImagebyOpernRouter (Gemini)** → calls google/gemini-2.5-flash-image-preview:free wait20sec (Wait)** → small delay setBase64data (Code)** → splits data URI into { data, mimeType, fileName } Convert to File** → creates binary uploadImagetoGdrive (Google Drive)** → uploads image updateImageURL (Google Sheets)** → writes back img_url Zone 1 — Create Image (Fal nano‑banana) + Prepare for Video Reads product rows, normalizes Drive links, generates image with Fal nano‑banana, polls until complete, fetches the output image URL, then runs an image analysis (OpenAI Vision) to prepare structured text for the video step. Key nodes Get Data (Google Sheets)** → reads nanoBanana tab Edit Fields (Set)** → converts Drive links to direct (uc?export=view&id=...) Call Fal.ai API (nanoBanana)** → POST https://queue.fal.run/fal-ai/nano-banana/edit Get image status / If / Wait / Get the image** → job polling until complete Analyze image (OpenAI Vision)** → returns structured description (brand text, colors, type, short description) Zone 2 — Generate Video (WAN2.2 & Veo3) Creates a 5–8s UGC clip using the generated image + structured scene prompt. Key nodes Describe Each Scene for Video (AI Agent)** → expands analysis + user intent into detailed scene sections (Characters, Scene Background, Camera Movement, Movement in Scene, Sound Design) Structured Output Parser2 (Schema)** → enforces consistent JSON structure Veo3 (HTTP)** → POST /fal-ai/veo3/image-to-video with prompt + image_url Call Fal.ai API (WAN2.2) [Optional]** → POST /fal-ai/wan/v2.2-a14b/image-to-video Wait for the video / Get the video status / Video status / Get the video** → polling loop HTTP Request (Download File)** → downloads MP4 uploadImagetoGdrive1 (Google Drive)** → uploads video updateVideoURL (Google Sheets)** → writes back video_url Node settings (high‑level) Drive Link Parser (Set)** {{ (() => { const u = $json.product || ''; const q = u.match(/[?&]id=([-\w]{25,})/); const d = u.match(/\/d\/([-\w]{25,})/); const any = u.match(/[-\w]{25,}/); const id = q?.[1] || d?.[1] || (any ? any[0] : ''); return id ? 'https://drive.google.com/uc?export=view&id=' + id : ''; })() }} How to customize the workflow Adjust AI prompts to change ad style (funny, luxury, cozy, techy). Change video aspect ratio for TikTok/IG/Shorts (9:16, 1:1, 16:9). Extend Sheet schema for campaign labels, audiences, hashtags. Add distribution (Slack/LINE/Telegram) after Drive upload. Troubleshooting JSON parameter needs to be valid JSON** → Ensure expressions return objects, not strings. 403 on images** → Make Drive files public (Viewer) and convert links. Video never completes* → Check status_url, retry with -fast models or off‑peak times. Template metadata Uses:** Google Sheets, Google Drive, HTTP Request, Wait/If/Switch, Code, Convert to File, OpenAI/Gemini (optional), Fal.ai models (nano‑banana, WAN2.2, Veo3) Source workflow JSON:** Gemini\_NanoBanana\_Template.json (node names and connections match) Product Image Product Image - nano Banana Product Video - Veo3 Product Video - Wan2.2. An n8n automation workflow template by Jaruphat J..

By Avkash Kakdiya

How it works This workflow starts whenever a new lead submits a Typeform. It captures the lead’s details, checks their budget, and routes them based on priority and source. High-budget leads are pushed into HubSpot with a follow-up task for sales. Facebook leads are logged in Google Sheets for marketing, while SurveyMonkey leads are stored in Airtable for campaign tracking. Finally, every lead receives an automated Gmail acknowledgment to confirm receipt and set expectations. Step-by-step Capture Leads The workflow listens for new form responses from Typeform. Each lead’s details — name, email, phone, budget, and message — are captured for processing. Prioritize High-Budget Leads The budget field is checked. If the budget is greater than $5,000 → the lead is flagged as high priority. These leads are added or updated in HubSpot CRM. A priority follow-up task is created in HubSpot for the sales team. Route by Lead Source If the source is Facebook → the lead is logged in a Google Sheet for marketing analysis. If the source is SurveyMonkey → the lead is stored in Airtable for structured campaign tracking. Send Auto-Response After storage, every lead receives an automated Gmail reply. The email thanks them for their interest and assures them that the sales team will follow up within 24 hours. Why use this? Captures and organizes leads from multiple channels in one workflow. Flags and escalates high-budget leads instantly to sales. Routes leads to the right system (HubSpot, Google Sheets, Airtable) based on their source. Automates acknowledgment emails, improving response time and customer experience. Saves manual effort by centralizing lead capture, qualification, and routing in one place. An n8n automation workflow template by Avkash Kakdiya.

By Michael Taleb

Workflow Summary This automation keeps your Supabase vector database synchronized with documents stored in Google Drive, while also making the data contextual and vector based for better retrieval. When a file is added or modified, the workflow extracts its text, splits it into smaller chunks, and enriches each chunk with contextual metadata (such as summaries and document details). It then generates embeddings using OpenAI and stores both the vector data and metadata in Supabase. If a file changes, the old records are replaced with updated, contextualized content. The result is a continuously updated and context-aware vector database, enabling highly accurate hybrid search and retrieval. To setup 1. Connect Google Drive • Create a Google Drive folder to watch. • Connect your Google Drive account in n8n and authorize access. • Point the Google Drive Trigger node to this folder (new/modified files trigger the flow). 2. Configure Supabase • Please refer to the Setting Up Supabase Sticky Note. 3. Connect OpenAI (or your embedding model) • Add your OpenAI API key in n8n credentials. An n8n automation workflow template by Michael Taleb.

By Harry Siggins

This n8n template transforms your daily meeting preparation by automatically researching attendees and generating comprehensive briefing documents. Every weekday morning, it analyzes your calendar events, researches each external attendee using multiple data sources, and delivers professionally formatted meeting briefs directly to your Slack channel. Who's it for Business professionals, sales teams, account managers, and executives who regularly attend meetings with external contacts and want to arrive fully prepared with relevant context, conversation starters, and strategic insights about their attendees. How it works The workflow triggers automatically Monday through Friday at 6 AM, fetching your day's calendar events and filtering for meetings with external attendees. For each meeting, an AI agent researches attendees using your CRM (Attio), email history (Gmail), past calendar interactions, and external company research via Perplexity when needed. The system then generates structured meeting briefs containing attendee background, relationship context, key talking points, and strategic objectives, delivering everything as a formatted Slack message to start your day. Requirements Google Calendar with OAuth2 credentials Gmail with OAuth2 credentials Slack workspace with bot token and channel access Attio CRM with API bearer token OpenRouter API key for AI model access (or other API credentials to connect AI to your AI agents) Perplexity API key for company research How to set up Configure credentials for all required services in your n8n instance Update personal identifiers in the workflow: Replace "YOUR_EMAIL@example.com" with your actual calendar email in both Google Calendar nodes Replace "YOUR_SLACK_CHANNEL_ID" with your target channel ID in both Slack nodes Adjust AI models in OpenRouter nodes based on your preferences and model availability Test the workflow manually with a day that contains external meetings Verify Slack formatting appears correctly in your channel How to customize the workflow Change meeting research depth: Modify the AI agent prompt to focus on specific research areas like company financial data, recent news, or technical background. Adjust notification timing: Update the cron expression in the Schedule Trigger to run at different times or days. Expand CRM integration: Add additional Attio API calls to capture more contact details or create follow-up tasks. Enhance Slack formatting: Customize the Block Kit message structure in the JavaScript code node to include additional meeting metadata or visual elements. Add more research sources: Connect additional tools like LinkedIn, company databases, or news APIs to the AI agent for richer attendee insights. The template uses multiple AI models through OpenRouter for different processing stages, allowing you to optimize costs and performance by selecting appropriate models for research tasks versus text formatting operations. An n8n automation workflow template by Harry Siggins.

By Khair Ahammed

Transform your customer support with this intelligent Gmail-based automation system that combines AI analysis, vector knowledge bases, and smart escalation workflows. This comprehensive solution automatically processes incoming support emails, provides contextual responses using your knowledge base, and seamlessly escalates complex issues to human agents. Key Features 🤖 Advanced AI Analysis GPT-4 powered email categorization (technical, billing, general, complaint) Automatic priority assignment (high, medium, low) with SLA tracking Smart escalation detection based on complexity and customer sentiment Context-aware responses using vector knowledge base integration 📧 Gmail Integration Real-time email monitoring with unread message triggers Automatic reply generation and sending Thread history analysis for contextual conversations Smart labeling system for automated organization Reply detection to prevent infinite loops 🧠 Knowledge Base Integration Qdrant vector store for semantic search capabilities Mistral Cloud embeddings for accurate content matching Tool-based knowledge retrieval during AI analysis Contextual responses based on your support documentation 📊 Comprehensive Tracking Google Sheets logging with detailed ticket information SLA tracking with automatic due date calculation Priority-based response time management Complete conversation history preservation 📱 Team Notifications Telegram alerts for escalated tickets Status updates with priority indicators Rich formatting with emojis and structured messages Real-time team coordination Workflow Components Core Processing Flow: Gmail Trigger monitors incoming emails Email filtering prevents reply loops and internal processing Data extraction captures customer information Thread history analysis for reply context AI agent analyzes with knowledge base access Smart routing based on escalation needs Automated responses or human escalation Comprehensive logging and notifications Advanced Features: Conversation context preservation Multi-source knowledge base queries Structured JSON output parsing Dynamic SLA assignment Conditional escalation workflows Required Integrations APIs & Services: Gmail OAuth2 (email processing) OpenAI GPT-4 (AI analysis) Qdrant (vector knowledge base) Mistral Cloud (embeddings) Google Sheets (logging) Telegram Bot (notifications) Setup Requirements: Gmail account with API access OpenAI API key Qdrant vector database Mistral Cloud account Google Sheets document Telegram bot token ##Use Cases Perfect for: SaaS companies with high support volume E-commerce businesses needing 24/7 support Service providers requiring categorized ticket handling Teams wanting to reduce response times Organizations needing SLA compliance tracking Industries: Software & Technology E-commerce & Retail Financial Services Healthcare & Medical Education & Training Business Benefits Efficiency Gains: 80% reduction in manual email processing Instant response to common inquiries Automatic priority and SLA assignment Reduced human agent workload Quality Improvements: Consistent response quality Knowledge base-powered accuracy Context-aware conversation handling Professional tone maintenance Operational Excellence: Complete audit trail in Google Sheets Real-time team notifications Escalation workflow automation Performance metrics tracking Technical Specifications Node Types Used: Gmail Trigger & Actions (5 nodes) LangChain AI Agent (2 nodes) Vector Store Integration (2 nodes) Data Processing (6 nodes) Conditional Logic (2 nodes) Notification Systems (1 node) Data Flow: Input: Gmail unread emails Processing: AI analysis with knowledge base Output: Automated replies or escalations Logging: Google Sheets with full details Notifications: Telegram status updates Installation & Setup Quick Start: Import workflow JSON Configure Gmail OAuth2 credentials Set up OpenAI API connection Connect Qdrant vector database Configure Google Sheets logging Set Telegram bot notifications Test with sample emails Customization Options: Modify AI prompts for your business Adjust escalation criteria Customize response templates Configure SLA timeframes Add additional knowledge sources. An n8n automation workflow template by Khair Ahammed.

By Yang

Who is this for? This workflow is perfect for content strategists, SEO specialists, marketing agencies, and virtual assistants who need to quickly audit and collect blog content from client websites into a structured Google Sheet without doing manual crawling and copy-pasting. What problem is this workflow solving? Manually visiting a website, finding blog posts, and copying content into a spreadsheet is time-consuming and prone to errors. This workflow automates the process: it crawls a website, filters only blog-related pages, scrapes the article content, and stores everything neatly in Google Sheets for easy analysis and content strategy planning. What this workflow does The workflow starts when a client submits their website URL through a form. A Google Sheet is automatically created and headers are added for organizing the audit. Dumpling AI then crawls the website to discover all available pages, while the automation filters out only blog-related URLs. Each blog page is scraped for content, and the structured results (URL, crawled page, and website content) are appended row by row into the Google Sheet. Nodes Overview Form Trigger – Form Submission (Client URL) Captures the client’s website URL to start the workflow. Google Sheets – Create Blog Audit Sheet Creates a new Google Sheet with a title based on the submitted URL. Set – Set Sheet Headers Defines the headers: Url, Crawled_pages, website_content. Code – Format Header Row Formats the headers properly before sending them to the sheet. HTTP Request – Insert Headers into Sheet Updates the Google Sheet with the prepared header row. HTTP Request – Dumpling AI: Crawl Website Crawls the submitted URL to discover internal pages. Code – Extract Blog URLs Filters the crawl results and keeps only URLs that match common blog patterns (e.g., /blog/, /articles/, /posts/). HTTP Request – Dumpling AI: Scrape Blog Pages Scrapes the text content from each filtered blog page. Set – Prepare Row Data Maps the URL, blog page link, and scraped content into structured fields. Google Sheets – Save Blog Data to Google Sheets Appends the structured data into the audit sheet row by row. 📝 Notes Set up Dumpling AI and generate your API key from: Dumpling AI Google Sheets must be connected with write permissions enabled. You can change the crawl depth or limit (currently set to 10 pages) in the Dumpling AI: Crawl Website node. The Extract Blog URLs node uses regex patterns to detect blog content. You can customize these patterns to match your website’s URL structure. An n8n automation workflow template by Yang.

By Yang

Who is this for? This workflow is perfect for content marketers, bloggers, SEO professionals, and virtual assistants who need to transform keyword research into complete blog posts without spending hours writing and formatting. What problem is this workflow solving? Writing a blog post from scratch requires research, summarizing content, and structuring it into a polished article. This workflow automates that process by taking a single keyword, fetching related news articles, cleaning the data, and generating a professional blog draft automatically in Google Docs. What this workflow does The workflow begins when a keyword is submitted through a form. It expands the keyword into trending suggestions using Dumpling AI Autocomplete, then fetches recent news articles with Dumpling AI Google News. Articles are filtered to only include those published within the last 1–2 days, then scraped and cleaned for quality text. The aggregated content is sent to OpenAI, which generates a polished blog draft with a clear title. Finally, the draft is saved directly into Google Docs for easy editing and publishing. Nodes Overview Form Trigger – Form Submission (Keywords) Starts the workflow when a keyword is submitted through a form. HTTP Request – Dumpling AI Autocomplete Expands the keyword into multiple trending search suggestions. Split Out – Split Autocomplete Suggestions Breaks the list of autocomplete suggestions into individual items for processing. Loop – Loop Suggestions Iterates through each suggestion to process articles separately. Wait – Delay Between Requests Adds a pause to avoid sending too many requests at once. HTTP Request – Dumpling AI Google News Fetches recent news articles for each suggestion. Split Out – Split News Articles Splits the returned news results into individual articles. Code – Filter Articles (1–2 Days Old) Keeps only articles that are between 1 and 2 days old for fresh content. Limit – Limit Articles Restricts the workflow to the top 2 articles for each suggestion. HTTP Request – Dumpling AI Scraper Scrapes and cleans the full text content from the article URLs. Code – Clean & Prepare Article Content Removes clutter like links, images, and unrelated sections to ensure clean input. Aggregate – Aggregate Articles Combines the cleaned article content into one dataset. OpenAI – Generate Blog Draft Uses OpenAI to create a polished blog post draft and title in Markdown format. Google Docs – Create Blog File Creates a new Google Doc with the generated blog title. Google Docs – Insert Blog Content Inserts the full blog draft into the created document. 📝 Notes Set up Dumpling AI and generate your API key from: Dumpling AI OpenAI must be connected with an active API key for blog generation. Google Docs must be connected with write permissions to create and update blog posts. You can adjust the article filter (currently set to 1–2 days old) in the code node depending on your needs. An n8n automation workflow template by Yang.

By Yang

Who is this for? This workflow is perfect for content creators, newsletter publishers, digital marketers, and virtual assistants who need a quick way to generate professional newsletters from trending news without manually curating and formatting articles. What problem is this workflow solving? Manually searching for news, summarizing articles, formatting them into a newsletter, and sending them by email is time-consuming and inconsistent. This workflow automates the process end-to-end: from capturing a keyword in Telegram to sending a ready-to-publish HTML newsletter by Gmail. What this workflow does The workflow begins when a keyword is received from Telegram. The keyword is expanded into trending suggestions using Dumpling AI Autocomplete, then passed to Dumpling AI Google News to fetch recent articles. The results are structured, split, and scraped for clean content. The combined content is sent to OpenAI to generate a professional HTML newsletter and subject line, which is finally delivered to a chosen inbox via Gmail. Nodes Overview Telegram Trigger – Start: Receive Keyword Listens for a keyword sent from Telegram to initiate the workflow. HTTP Request – Google Autocomplete via Dumpling AI Expands the keyword into trending search suggestions. HTTP Request – Search Google News via Dumpling AI Fetches recent news articles related to the autocomplete suggestions. Parser and Split Nodes – Process Articles Formats results into structured JSON and splits them into individual articles. HTTP Request – Scraper via Dumpling AI Scrapes and cleans each article to extract high-quality text. Aggregate – Combine Article Content Merges all cleaned articles into a single dataset for newsletter generation. OpenAI – Generate Newsletter Produces a ready-to-use HTML newsletter and subject line. Gmail – Send Newsletter Delivers the completed newsletter to the specified inbox. 📝 Notes You must connect Dumpling AI and OpenAI accounts with valid API keys before running. The Telegram trigger can be configured for private or group chats depending on your use case. Ensure Gmail is properly connected with send permissions enabled. An n8n automation workflow template by Yang.

By AI/ML API | D1m7asis

Who’s it for Teams and makers who want a plug-and-play vision bot: users send a photo in Telegram, the bot returns a concise description plus OCR text. No custom servers required—just n8n, a Telegram bot, and an AIMLAPI key. What it does / How it works The workflow listens for new Telegram messages, fetches the highest-resolution photo, converts it to base64, normalizes the MIME type, and calls AIMLAPI (GPT-4o Vision) via the HTTP Request node using the OpenAI-compatible messages format with an image_url data URI. The model returns a short caption and extracted text. The answer is sent back to the same Telegram chat. Requirements n8n instance (self-hosted or cloud) Telegram bot token (from @BotFather) AIMLAPI account and API key (OpenAI-compatible endpoint) How to set up Create a Telegram bot with @BotFather and copy the token. In n8n, add Telegram credentials (no hardcoded tokens in nodes). Add AIMLAPI credentials with your API key (base URL: https://api.aimlapi.com/v1). Import the workflow JSON and connect credentials in the nodes. Execute the trigger and send a photo to your bot to test. How to customize the workflow Modify the vision prompt (e.g., add brand, language, or formatting rules). Switch models within AIMLAPI (any vision-capable model using the same messages schema). Add an IF branch for text-only messages (reply with guidance). Log usage to Google Sheets or a database (user id, file id, response). Add rate limits, user allowlists, or Markdown formatting in Telegram responses. Increase timeouts/retries in the HTTP Request node for long-running images. An n8n automation workflow template by AI/ML API | D1m7asis.

By FabioInTech

Who’s it for Generate personalized sales leads, ready-to-send, HTML-formatted emails, and send them automatically. This workflow is ideal for sales professionals, marketers, and business development teams aiming to scale their outreach. By automating the tedious tasks of research and email drafting, you can focus on building relationships and closing deals. How it works This workflow automates the process of finding sales leads and drafting personalized emails. It starts by pulling a list of unprocessed companies from an Airtable base. For each company, it uses Jina DeepSearch to find key decision-makers, their roles, and email addresses. An AI agent then analyzes the research to identify the best contact and creates a custom, professional cold email. The email's content and subject are evaluated by a second AI agent, which assigns a score from 0-100. If the email scores below 80, it's sent to an Email Re-writer agent for improvement before being evaluated again. Finally, the workflow formats the polished email into an HTML draft in Gmail and updates the Airtable record with the lead information and the outcome. How to set up Airtable: Create your Airtable credentials here. Set up an Airtable base with a table that includes the following columns: Company_name, Company_website, Company_e-mail, processed, lead_name, lead_email, email_subject, email_text, email_summary, create_date and a task_result column. Jina AI: Get an API key from Jina AI and add it to the Jina_API_Key node. You can find more information here. Gmail: Connect your Gmail account using the Gmail node to allow the workflow to create email drafts. You can find the documentation for the Gmail node here. OpenAI: This workflow uses the OpenAI nodes (gpt-5-mini model) for the AI agents. You will need to provide your OpenAI API credentials. You can find the API documentation here. Business Info: Fill in your company's information in the Business_Info node, including your business name, description, key benefits, website URL, target audience, and the desired email language. Requirements An n8n account Airtable API Key** and a base with lead data. Jina AI API Key** for the deep search functionality. OpenAI API Key** to power the AI agents. A Gmail account connected to n8n. How to customize the workflow Changing the Score Threshold**: The If node is set to a threshold of 80. You can change this to a higher or lower number to control which emails are re-written. Database Integration**: Instead of Airtable, you can use a different database like Google Sheets or a CRM by swapping out the Airtable nodes for the corresponding integration nodes. Email Sending**: The workflow currently creates drafts in Gmail. You can easily modify the Gmail node to send the emails directly instead of creating drafts, but be cautious with this approach to avoid sending unwanted emails. Need a Professional and Personalized automation Contact me Need Help? Join the Discord or ask in the Forum!. An n8n automation workflow template by FabioInTech.

By Weiser22

Shopify Multilingual Product Copy with n8n & Gemini 2.5 Flash-Lite Use for free Created by <Weiser22> · Last update 2025-09-02 Categories: E-commerce, Product Content, Translation, Computer Vision Description Generate language-specific Shopify product copy (ES, DE, EN, FR, IT, PT) from each product’s main image and metadata. The workflow performs a vision analysis to extract objective, verifiable details, then produces product names, descriptions, and handles per language, and stores the results in Google Sheets for review or publishing. Good to know Model:** models/gemini-2.5-flash-lite (supports image input). Confirm pricing/limits in your account before scaling. Image requirement:** products should have images[0].src; add a fallback if some products lack a primary image. Sheets mapping:** the sheet node uses Auto-map; ensure your matching column aligns with the field you emit (id vs product_id). Strict output:** the Agent enforces a multilingual JSON contract (es,de,en,fr,it,pt), each with shopify_product_name, shopify_description, handle. How it works Manual Trigger:** start a test run on demand. Get many products (Shopify):** fetch products and their images. Analyze image (Gemini Vision):** send images[0].src with an objective, 3–5 sentence prompt. AI Agent (Gemini Chat):** merge Shopify fields + vision text under anti-hallucination rules and a strict JSON schema. Structured Output Parser:** validates the exact JSON shape. Expand Languages & Sanitize (Code):** split into 6 items and normalize handles/HTML content as needed. Append row in sheet (Google Sheets):** add one row per language to your spreadsheet. Requirements Shopify Access Token with product read permissions. Google AI Studio (Gemini) API key for Vision + Chat Model nodes. Google Sheets credentials (OAuth or Service Account) with access to the target spreadsheet. How to use Connect credentials: Shopify, Gemini (same key for Vision and Chat), and Google Sheets. Configure nodes: Get many products: adjust limit/filters. Analyze image: verify ={{ $json.images[0].src }} resolves to a public image URL. AI Agent & Parser: keep the strict JSON contract as provided. Code (Expand & Sanitize): emits product_id, lang, handle, shopify_product_name, shopify_description, base_handle_es. Google Sheets (Append): set documentId and tab name; confirm the matching column. Run a test: execute the workflow and confirm six rows per product (one per language) appear in the sheet. Data contract (Agent output) { "es": {"shopify_product_name": "", "shopify_description": "", "handle": ""}, "de": {"shopify_product_name": "", "shopify_description": "", "handle": ""}, "en": {"shopify_product_name": "", "shopify_description": "", "handle": ""}, "fr": {"shopify_product_name": "", "shopify_description": "", "handle": ""}, "it": {"shopify_product_name": "", "shopify_description": "", "handle": ""}, "pt": {"shopify_product_name": "", "shopify_description": "", "handle": ""} } Customising this workflow Publish to Shopify:** after review in Sheets, add a product.update step to write finalized copy/handles. Handle policy:** tweak slug rules (diacritics, separators, max length) in the Code node to match store conventions. No-image fallback:** add an IF/Switch to skip vision when images[0].src is missing and generate copy from title + body only. Tone/length:** adjust temperature and token limits on the Chat Model for brand-fit. Troubleshooting No rows in Sheets:** confirm spreadsheet ID, tab name, Auto-map status, and that the matching column matches your emitted field. Vision errors:** ensure images[0].src is reachable. Parser failures:* the Agent must return *bare JSON** with the six root keys and three fields per language—no extra text. An n8n automation workflow template by Weiser22.

By Alok Kumar

Multi-Level Document Approval & Audit Workflow This workflow automates a document approval process using Supabase and Gmail. Who it’s for Teams that need structured multi-level document approvals. Companies managing policies, contracts, or proposals. Medical document need multiple lavel of review and approval. How it works Form Trigger – A user submits a document via the form. Supabase Integration – The document is saved in the documents table. Supabase Storage – The document is saved in the bucket. Workflow Levels – Fetches the correct approval level from workflow_levels. Assign Approvers – Matches approvers by role from the users table. Approval Record – Creates an approvals record with a unique token and expiry. Email Notification – Sends an email with Approve / Reject links. Audit Logs – Records every approval request in audit_logs. Repeat - repeat the flow till all the aproval level is comepted How to set up Configure your Supabase credentials. Create tables as per data model given. Create a storage bucket in Supabase Storage. Connect your Gmail account. Adjust approval expiry time (48h default). Deploy and test via the Form Trigger. Customization Add multiple approval levels by chaining workflow_levels. Replace Gmail with Slack, Teams, or another notification channel. Adjust audit logging for compliance needs. Update the endpoint http://localhost:5678/webhook-test/ based on instance and env (remove test if you run in prod) Update the bucket name. Important steps 1. Form Submit Triggered when by submiting form Captures form parameters: Title (Document Title) Description (Document Description) file (Document need for approval) 2. Webhook Entry Point Triggered when an approver clicks the Approve or Reject link in email. Captures query parameters: token (approval token) decision (approved/rejected) 3. Approval Data Retrieval & Update Fetch approval record from Supabase (approvals) using token. Update approval status: Approved → moves to next workflow level or final approval. Rejected → document marked as rejected immediately. Records acted_at timestamp. 4. Decision Check IF Node* checks whether the decision is *approved* or *rejected**. Reject Path* → Update document status to *Rejected** in documents. Approve Path** → Continue workflow level progression. 5. Workflow Level Progression Fetch details of the current workflow level. Identify the next level (workflow_levels) based on level_number. ✅ If Next Level Exists: Retrieve approvers by role_id. Generate unique approval tokens. Create new approval records in approvals. Send email notifications with approval/reject links. ❌ If No Next Level (Last Level): Update document status to Approved in documents. 6. Audit Logging Every approval action is logged into audit_logs table: document_id action (e.g., approval_sent, approved, rejected) actor_email (system/approver) details (workflow level, role info, etc.) 📨 Email Template Approval request email includes decision links: Please review the document: ✅ Approve | ❌ Reject Happy Automating! 🚀. An n8n automation workflow template by Alok Kumar.

By Dariusz Koryto

Automated FTP File Migration with Smart Cleanup and Email Notifications Overview This n8n workflow automates the secure transfer of files between FTP servers on a scheduled basis, providing enterprise-grade reliability with comprehensive error handling and dual notification systems (email + webhook). Perfect for data migrations, automated backups, and multi-server file synchronization. What it does This workflow automatically discovers, filters, transfers, and safely removes files between FTP servers while maintaining complete audit trails and sending detailed notifications about every operation. Key Features: Scheduled Execution**: Configurable timing (daily, hourly, weekly, or custom cron expressions) Smart File Filtering**: Regex-based filtering by file type, size, date, or name patterns Safe Transfer Protocol**: Downloads → Uploads → Validates → Cleans up source Dual Notifications**: Email alerts + webhook integration for both success and errors Comprehensive Logging**: Detailed audit trail of all operations with timestamps Error Recovery**: Automatic retry logic with exponential backoff for network issues Production Ready**: Built-in safety measures and extensive documentation Use Cases 🏢 Enterprise & IT Operations Data Center Migration**: Moving files between different hosting environments Backup Automation**: Scheduled transfers to secondary storage locations Multi-Site Synchronization**: Keeping files in sync across geographic locations Legacy System Integration**: Bridging old and new systems through automated transfers 📊 Business Operations Document Management**: Automated transfer of contracts, reports, and business documents Media Asset Distribution**: Moving images, videos, and marketing materials between systems Data Pipeline**: Part of larger ETL processes for business intelligence Compliance Archiving**: Moving files to compliance-approved storage systems 🔧 Development & DevOps Build Artifact Distribution**: Deploying compiled applications across environments Configuration Management**: Synchronizing config files between servers Log File Aggregation**: Collecting logs from multiple servers for analysis Automated Deployment**: Moving release packages to production servers How it works 📋 Workflow Steps Schedule Trigger → Initiates workflow at specified intervals File Discovery → Lists files from source FTP server with optional recursion Smart Filtering → Applies customizable filters (type, size, date, name patterns) Secure Download → Retrieves files to temporary n8n storage with retry logic Safe Upload → Transfers files to destination with directory auto-creation Transfer Validation → Verifies successful upload before proceeding Source Cleanup → Removes original files only after confirmed success Comprehensive Logging → Records all operations with detailed metadata Dual Notifications → Sends email + webhook notifications for success/failure 🔄 Error Handling Flow Network Issues** → Automatic retry with exponential backoff (3 attempts) Authentication Problems** → Immediate email alert with troubleshooting steps Permission Errors** → Detailed logging with recommended actions Disk Space Issues** → Safe failure with source file preservation File Corruption** → Integrity validation with rollback capability Setup Requirements 🔑 Credentials Needed Source FTP Server Host, port, username, password Read permissions required SFTP recommended for security Destination FTP Server Host, port, username, password Write permissions required Directory creation permissions SMTP Email Server SMTP host and port (e.g., smtp.gmail.com:587) Authentication credentials For success and error notifications Monitoring API (Optional) Webhook URL for system integration Authentication tokens if required ⚙️ Configuration Steps Import Workflow → Load the JSON template into your n8n instance Configure Credentials → Set up all required FTP and SMTP connections Customize Schedule → Adjust cron expression for your timing needs Set File Filters → Configure regex patterns for your file types Configure Paths → Set source and destination directory structures Test Thoroughly → Run with test files before production deployment Enable Monitoring → Activate email notifications and logging Customization Options 📅 Scheduling Examples 0 2 * * * # Daily at 2 AM 0 */6 * * * # Every 6 hours 0 8 * * 1-5 # Weekdays at 8 AM 0 0 1 * * # Monthly on 1st */15 * * * * # Every 15 minutes 🔍 File Filter Patterns Documents \\.(pdf|doc|docx|xls|xlsx)$ Images \\.(jpg|jpeg|png|gif|svg)$ Data Files \\.(csv|json|xml|sql)$ Archives \\.(zip|rar|7z|tar|gz)$ Size-based (add as condition) {{ $json.size > 1048576 }} # Files > 1MB Date-based (recent files only) {{ $json.date > $now.minus({days: 7}) }} 📁 Directory Organization // Date-based structure /files/{{ $now.format('YYYY/MM/DD') }}/ // Type-based structure /files/{{ $json.name.split('.').pop() }}/ // User-based structure /users/{{ $json.owner || 'system' }}/ // Hybrid approach /{{ $now.format('YYYY-MM') }}/{{ $json.type }}/ Template Features 🛡️ Safety & Security Transfer Validation**: Confirms successful upload before source deletion Error Preservation**: Source files remain intact on any failure Audit Trail**: Complete logging of all operations with timestamps Credential Security**: Secure storage using n8n's credential system SFTP Support**: Encrypted transfers when available Retry Logic**: Automatic recovery from transient network issues 📧 Notification System Success Notifications: Confirmation email with transfer details File metadata (name, size, transfer time) Next scheduled execution information Webhook payload for monitoring systems Error Notifications: Immediate email alerts with error details Troubleshooting steps and recommendations Failed file information for manual intervention Webhook integration for incident management 📊 Monitoring & Analytics Execution Logs**: Detailed history of all workflow runs Performance Metrics**: Transfer speeds and success rates Error Tracking**: Categorized failure analysis Audit Reports**: Compliance-ready activity logs Production Considerations 🚀 Performance Optimization File Size Limits**: Configure timeouts based on expected file sizes Batch Processing**: Handle multiple files efficiently Network Optimization**: Schedule transfers during off-peak hours Resource Monitoring**: Track n8n server CPU, memory, and disk usage 🔧 Maintenance Regular Testing**: Validate credentials and connectivity Log Review**: Monitor for patterns in errors or performance Credential Rotation**: Update passwords and keys regularly Documentation Updates**: Keep configuration notes current Testing Protocol 🧪 Pre-Production Testing Phase 1: Test with 1-2 small files (< 1MB) Phase 2: Test error scenarios (invalid credentials, network issues) Phase 3: Test with representative file sizes and volumes Phase 4: Validate email notifications and logging Phase 5: Full production deployment with monitoring ⚠️ Important Testing Notes Disable Source Deletion** during initial testing Use test directories to avoid production data impact Monitor execution logs** carefully during testing Validate email delivery** to ensure notifications work Test rollback procedures** before production use Support & Documentation This template includes: 8 Comprehensive Sticky Notes** with visual documentation Detailed Node Comments** explaining every configuration option Error Handling Guide** with common troubleshooting steps Security Best Practices** for production deployment Performance Tuning** recommendations for different scenarios Technical Specifications n8n Version**: 1.0.0+ Node Count**: 17 functional nodes + 8 documentation sticky notes Execution Time**: 2-10 minutes (depending on file sizes and network speed) Memory Usage**: 50-200MB (scales with file sizes) Supported Protocols**: FTP, SFTP (recommended) File Size Limit**: Up to 150MB per file (configurable) Concurrent Files**: Processes files sequentially for stability Who is this for? 🎯 Primary Users System Administrators** managing file transfers between servers DevOps Engineers** automating deployment and backup processes IT Operations Teams** handling data migration projects Business Process Owners** requiring automated file management 💼 Industries & Use Cases Healthcare**: Patient data archiving and compliance reporting Financial Services**: Secure document transfer and regulatory reporting Manufacturing**: CAD file distribution and inventory data sync E-commerce**: Product image and catalog management Media**: Asset distribution and content delivery automation. An n8n automation workflow template by Dariusz Koryto.

By Muhammad Farooq Iqbal

This n8n template demonstrates how to create an automated emotional story generation system that produces structured video prompts and generates corresponding images using AI. The workflow creates a complete story with 5 scenes featuring a Pakistani character named Yusra, converts them into Veo 3 video generation prompts, and generates images for each scene. Use cases include: Automated story creation for social media content Video pre-production with AI-generated storyboards Content creation for educational or entertainment purposes Multi-scene narrative development with consistent character design Good to know: Uses Gemini 2.5 Flash Lite for story generation and prompt conversion Uses Gemini 2.0 Flash Exp for image generation The image generation model may be geo-restricted in some regions Workflow includes automatic Google Drive organization and Google Sheets tracking How it works: Story Creation: Gemini AI creates a 5-scene emotional story featuring Yusra, a Pakistani girl aged 20-25 in traditional dress Folder Organization: AI generates a unique folder name with timestamp for project organization Google Sheets Setup: Creates a new sheet to track all scenes and their processing status Scene Processing: Each scene is processed individually with character and action prompts Veo 3 Prompt Conversion: Converts natural language scene descriptions into structured JSON format optimized for Veo 3 video generation, including parameters like: Detailed scene descriptions Camera movements and angles Lighting and mood settings Style and quality specifications Aspect ratios and technical parameters Image Generation: Uses Gemini's image generation model to create visual representations of each scene File Management: Automatically uploads images to Google Drive and organizes them in project folders Status Tracking: Updates Google Sheets with processing status and file URLs Automated Workflow: Includes conditional logic to handle different processing states and file movements How to use: Execute the workflow manually or set up automated triggers The system will automatically create a new story with 5 scenes Each scene gets processed through the AI pipeline Generated images are organized in Google Drive folders Track progress through the Google Sheets interface The workflow handles all file management and status updates automatically Requirements: Gemini API access for both text and image generation Google Drive for file storage and organization Google Sheets for project tracking and management n8n instance with appropriate node access Customizing this workflow: Modify the character description in the Story Creator node Adjust the number of scenes by changing the story prompt Customize the Veo 3 prompt parameters for different video styles Add additional AI models or processing steps Integrate with other content creation tools Modify the folder naming convention or organization structure Technical Features: Automated retry logic for failed operations Conditional processing based on status flags Batch processing for multiple scenes Error handling and status tracking File organization with timestamp-based naming Integration with Google Workspace services This template is perfect for content creators, educators, or anyone looking to automate story-based content creation with AI assistance. An n8n automation workflow template by Muhammad Farooq Iqbal.

By Atta

What it does Customer support calls contain a wealth of valuable feedback and urgent issues, but manually reviewing audio files is inefficient. This workflow acts as an AI assistant for your call log, transforming unstructured audio recordings into structured, actionable data. It provides a clean summary, sentiment analysis, and a list of required actions for every call, eliminating the need for manual listening and ensuring key insights are never missed. How it works The workflow runs on a schedule to fully automate the call analysis process from start to finish. Fetch New Recordings: The workflow triggers on a schedule (e.g., every 5 minutes), searches a designated Google Drive folder for new call recordings, and downloads any new files it finds. Transcribe Audio: Each audio file is sent to the ElevenLabs API to be converted from speech to a text transcript. The result is then formatted into a conversational, multi-speaker format. AI-Powered Analysis: The transcript is passed to a Google Gemini node, which is prompted to return a structured JSON object. This JSON contains a complete analysis of the call, including speaker identification (agent_name, client_name), a summary, the client_sentiment, a call_topic, a department_tag, and a list of action_items. Log the Results: The complete, structured analysis output from Gemini is appended as a new row in a Google Sheet, creating a centralized log with all the extracted call details and the full transcript. Take Action: The workflow uses conditional logic based on the detected sentiment: Negative Sentiment: If a call was negative, an immediate alert containing the call summary and action items is sent to a manager's group on Telegram. Positive Sentiment: If a call was positive, a kudos message is sent to the support team's Telegram channel to celebrate good work. File Management: After processing, the original audio file is automatically moved to a separate "Processed" folder in Google Drive to ensure it isn’t analyzed again. Setup Instructions To configure this workflow, you will need to set up your file storage in Google Drive, create a Google Sheet for logging, and configure credentials for all connected services. Required Credentials Google: You will need Google OAuth2 credentials that have permission for Google Drive, Google Sheets, and the Google AI (Gemini) APIs. ElevenLabs: Sign up for an account at ElevenLabs and get your API Key. You will add this directly into the HTTP Request node for transcription. Telegram: Create a bot using the BotFather in Telegram to get your Bot Token. You will also need the specific Chat ID for the managers' channel and the team's channel. Step-by-Step Configuration Google Drive: Create two folders in your Google Drive: one named "Company - Support Call Recordings" and another named "Processed Recordings". Copy the unique Folder ID from the URL for each and paste it into the respective Google Drive nodes. Google Sheets: Create a new Google Sheet to log the results. In the first row, create the following headers exactly as written: Recording File, Sentiment, Department, Topic, Agent, Client, Summary, Actions, and Fulltext. Copy the Sheet ID from the URL and paste it into the "Log Recording Analysis" (Google Sheets) node. ElevenLabs Node: In the "Convert Speech To Text" (HTTP Request) node, make sure the URL is set to the correct ElevenLabs API endpoint for speech-to-text. Add your ElevenLabs API Key to the authentication header. Telegram Nodes: In the "Send Alert To Managers" node, enter the Chat ID for your managers' group. In the "Send Kudos to Team" node, enter the Chat ID for the main team channel. How to Adapt the Template This workflow is a powerful starting point. Based on your specific needs, you can customize the inputs, the AI analysis, the logging method, and the final actions. Input Method Change File Source:* Instead of Google Drive, you can adapt the workflow to fetch recordings from other services like *Dropbox, **OneDrive, or a custom FTP server. Use a Webhook:* Replace the *Schedule Trigger* with a *Webhook Trigger** to process calls in real-time as they are added from your call software (if it supports webhooks). Final Actions Create Service Tickets:* This is a key area for customization. Replace the *Telegram* nodes with nodes for ticketing systems. For a negative call, you can automatically create a high-priority ticket in *Jira, **Zendesk, or ServiceNow. Create Tasks:* For calls with specific action items, use a node like *Asana, **Trello, or Todoist to automatically create a task and assign it to the correct team member. Send Email Notifications:* Use the *Send Email** node to dispatch summaries and alerts to stakeholders who are not on Telegram. Logging and Analysis Log to a Database:* Instead of Google Sheets, you can use a *Postgres, **MySQL, or Data Warehouse node to log the structured data for more advanced business intelligence and dashboarding. Customize the AI Prompt:** The prompt in the Google Gemini node is the "brain" of the operation. It specifically instructs the AI to return a JSON object with a predefined structure. To change what data is extracted, you can modify this structure in the prompt. For example, you could add a new key-value pair like "competitor_mentioned": "Name of competitor if mentioned, otherwise null" to the JSON structure. The current workflow asks the AI to populate a JSON object like this: { "speaker_identification": { "agent": "speaker_id", "agent_name": "The agent's name", "client": "client_id", "client_name": "The client's name" }, "summary": "A concise summary.", "client_sentiment": "Positive, Negative, or Neutral", "call_topic": "A brief phrase for the topic.", "department_tag": "The most relevant department.", "action_items": [ "A list of actionable tasks." ] } Change AI or STT Service:* You can swap out the *Google Gemini* node for an *OpenAI* node, or change the *HTTP Request* node to use a different transcription service like *AssemblyAI* or *Deepgram**. An n8n automation workflow template by Atta.

By Ladies Build With AI

Who is it for This workflow is designed for anyone who wants to simplify email automation without leaving Google Sheets. You can also send out emails automatically, without even visiting Google Sheets. It’s especially useful for: Marketers sending bulk or personalized campaigns Recruiters managing outreach from candidate lists Small business owners who want automated follow-ups Anyone who wants to trigger emails directly from sheet updates, e.g. event updates. How it works The workflow connects Google Sheets with Gmail to let you send emails in either of two ways: Bulk emails (mail merge): Use data from your sheet to send an email to multiple email addresses, one by one. Triggered emails: Automatically send an email whenever specific values or conditions in your sheet are met. No need to manually copy, paste, or switch to Gmail, because the process is fully automated. How to set it up Copy this template into your personal n8n workspace: https://docs.google.com/spreadsheets/d/1fWg_GOU0m_2cQpah7foDiz1WqTRKjCbJJCLBGCvJlXc/edit?usp=sharing Connect your Google Sheets and Gmail accounts using this workflow in n8n. Select the spreadsheet and sheet you want to use. Customize the email nodes with your subject line, body text, and variables (e.g., names or links from your sheet). Test the workflow, then activate it to start sending emails automatically. For a step-by-step walkthrough, check out this video guide on YouTube: https://www.youtube.com/watch?v=XJQ0W3yWR-0 Requirements A Google Sheets account with your data organized in rows and columns A Gmail account for sending emails An active n8n account to run the workflow. An n8n automation workflow template by Ladies Build With AI.

By Dhruv Dalsaniya

This workflow is designed for e-commerce, marketing teams, or creators who want to automate the production of high-quality, AI-generated product visuals and ad creatives. Here is what the workflow does: It accepts a product description and other creative inputs through a web form. It uses AI to transform your text input into a detailed, creative prompt. This prompt is then used to generate a product image. The workflow analyzes the generated image and creates a new prompt to generate a second image that includes a model, adding a human element to the visual. A final prompt is created from the model image to generate a short, cinematic video. All generated assets (images and video) are automatically uploaded to your specified hosting platform, providing you with direct URLs for immediate use. This template is an efficient solution for scaling your content creation efforts, reducing time spent on manual design, and producing a consistent stream of visually engaging content for your online store, social media, and advertising campaigns. Prerequisites: OpenRouter Account:** Required for AI agents to generate image and video prompts. GOAPI Account:** Used for the final video generation process. Media Hosting Platform:** A self-hosted service like MediaUpload, or any alternative like Google Drive or a similar service that can provide a direct URL for uploaded images and videos. This is essential for passing the visuals between different steps of the workflow. An n8n automation workflow template by Dhruv Dalsaniya.

By DuyTran

Description 📌 Overview This workflow creates a chat-based Retrieval-Augmented Generation (RAG) agent that lets you upload documents to Google Drive and then query them directly through Telegram. It uses embeddings, vector storage, and an AI agent to retrieve, analyze, and answer user questions with context-aware responses. 🧩 Key Features 📂 Google Drive Integration Watches a folder for new file uploads. Downloads and loads documents automatically into the system. 🔎 Vector Embeddings & Storage Uses OpenAI embeddings to transform documents into vectors. Stores them in an in-memory vector store for retrieval. 🤖 AI Agent with Memory Built on LangChain Agent + GPT-4.1-mini. Performs similarity search in the vector store. Provides contextual answers with citations from the uploaded documents. Maintains short-term conversation memory for better continuity. 💬 Telegram Bot Integration Users can send questions directly to the bot. AI agent retrieves relevant information and replies with clear answers. ⚙️ How It Works Trigger: Upload a file into the Google Drive folder. Processing: Workflow downloads the file → loads → embeds → stores in vector memory. Query: User sends a question via Telegram. Retrieval & Response: AI agent searches stored documents → analyzes results → returns summarized answer in Telegram. 🔐 Requirements Google Drive OAuth credentials. OpenAI API key (for embeddings + LLM). Telegram Bot API token. 📥 Use Cases 📑 Knowledge base assistant – Upload internal docs and query them in chat. 🏫 Learning support – Students upload study materials and ask questions. 📊 Business intelligence – Teams upload reports and get instant summaries. More templet: https://aitool.wiki/. An n8n automation workflow template by DuyTran.

By Kunsh

How it works Automatically monitors Twitter for bug bounty tips and educational content every 4 hours, then saves valuable insights to Google Sheets for easy reference and organization. Set up steps Get your API key from https://twitterapi.io/ (free tier available) Configure Google Sheets credentials in n8n Create a Google Sheet with the required columns Update the Sheet ID in the final node What you'll get A continuously updated database of bug bounty tips, techniques, and insights from the security community, perfectly organized in Google Sheets with: Tweet content and URLs Engagement metrics (likes, retweets, replies) Formatted timestamps for easy sorting Automatic duplicate prevention Perfect for security researchers, bug bounty hunters, and cybersecurity professionals who want to stay updated with the latest tips and techniques from Twitter's security community. An n8n automation workflow template by Kunsh.

By Parth Pansuriya

AI Meeting Summary Generator with Google Docs Integration Who’s it for Teams that record meetings and want fast, clear summaries without manual note-taking. Managers who need action items extracted automatically. Anyone using Google Drive + Google Docs as their central workspace. How it works / What it does This workflow automates meeting documentation: Watches a Google Drive folder for new audio/video meeting files. Downloads the file and transcribes speech into text using Gemini AI. Summarizes transcripts into Key Discussions and Action Items. Creates or updates a Google Doc with the formatted summary (title, bullets, checkmarks, styling). Sends final output to Docs with bold headings, bullets, and spacing for readability. How to set up Add your Google Drive Trigger to monitor a folder. Connect Gemini AI to handle transcription + summarization. Configure the Google Docs Tool to create/update your summary documents. (Optional) Use the Code Node + Docs API to apply bullet/checkmark formatting. Requirements Google Drive OAuth2 – for monitoring & downloading files Google Docs OAuth2 – for creating and updating documents Google Gemini API – for transcription + AI-powered summarization How to customize the workflow Change the Google Drive folder to monitor a different workspace. Edit the system prompt in the Summarizer to tweak summary style (e.g., more detail, decisions only, etc.). Modify the Code Node formatting rules (bullets, checkmarks, bold text). Add integrations (e.g., Slack, Email, Notion) to send summaries beyond Google Docs. An n8n automation workflow template by Parth Pansuriya.

By Avkash Kakdiya

How it works This workflow automatically scrapes LinkedIn job postings for a list of target companies and organizes the results in Google Sheets. Every Monday morning, it checks your company list, runs a LinkedIn job scrape using Phantombuster, waits for the data to be ready, and then fetches the results. Finally, it formats the job postings into a clean structure and saves them into a results sheet for easy analysis. Step-by-step Start with Scheduled Trigger The workflow runs automatically at 9:00 AM every Monday. It reads your “Companies Sheet” in Google Sheets and filters only those marked with Status = Pending. Scrape LinkedIn Jobs The workflow launches your Phantombuster agent with the LinkedIn profile URLs from the sheet. It waits 3 minutes to let the scraper finish running. Then it fetches the output CSV link containing the job posting results. Format the Data The scraped data is cleaned and structured into fields like: Company Name Job Title Job Description Job Link Date Posted Location Employment Type Save Everything in Google Sheets The formatted job data is appended into your “Job Results” Google Sheet. Each entry includes a scrape date so you can track when the data was collected. Why use this? Automates job market research and competitive hiring analysis. Collects structured job posting data from multiple companies at scale. Saves time by running on a schedule with no manual effort. Keeps all results organized in Google Sheets for easy review and sharing. Helps HR and recruitment teams stay ahead of competitors’ hiring activity. An n8n automation workflow template by Avkash Kakdiya.

By Atta

What it does Instead of manually checking separate apps for your calendar, weather, and news each morning, this workflow consolidates the most important information into a single, convenient audio briefing. The "Good Morning Podcast" is designed to be a 3-minute summary of your day ahead, delivered directly to you. It's multi-lingual and customizable, allowing you to start your day informed and efficiently. How it works The workflow executes in three parallel branches before merging the data to generate the final audio file. Weather Summary: It starts by taking a user-provided city and fetching the current 15-hour forecast from the OpenWeatherMap. It formats this information into a concise weather report. Calendar Summary: It securely connects to your Google Calendar to retrieve all of today's scheduled meetings and events. It then formats the schedule into a clear, readable summary. News Summary: It connects to the NewsAPI to perform two tasks: it fetches the top general headlines and also searches for articles based on user-defined keywords (e.g., "AI", "automation", "space exploration"). The collected headlines are then summarized using a Google Gemini node to create a brief news digest. Audio Generation and Delivery: All three text summaries (weather, calendar, and news) are merged into a single script. The workflow uses Google's Text-to-Speech (TTS) to generate the raw multi-speaker audio. A dedicated FFmpeg node then processes and converts this audio into the final MP3 format. The completed podcast is then sent directly to you via a Telegram Bot. Setup Instructions To get this workflow running, you will need to configure credentials for each of the external services and set your initial parameters. ⚠️ Important Prerequisite Install FFmpeg: The workflow requires the FFmpeg software package to be installed on the machine running your n8n instance (local or server). Please ensure it is installed and accessible in your system's PATH before running this workflow. Required Credentials OpenWeatherMap: Sign up for a free account at OpenWeatherMap and get your API key. Add the API key to your n8n OpenWeatherMap credentials. Google Calendar & Google AI (Gemini/TTS): You will need Google OAuth2 credentials for the Google Calendar node. You will also need credentials for the Google AI services (Gemini and Text-to-Speech). Follow the n8n documentation to create and add these credentials. NewsAPI: Get a free API key from NewsAPI.org. Add the API key to your n8n NewsAPI credentials. Telegram: Create a new bot by talking to the BotFather in your Telegram app. Copy the Bot Token it provides and add it to your n8n Telegram credentials. Send a message to your new bot and get your Chat ID from the Telegram Trigger node or another method. You will need this for the Telegram send node. Workflow Inputs In the first node (or when you run the workflow manually), you must provide the following initial data: name: Your first name for a personalized greeting. city: The city for your local weather forecast (e.g., "Amsterdam"). language: The language for the entire podcast output (e.g., "en-US", "nl-NL", "fa-IR"). news_keywords: A comma-separated list of topics you are interested in for the news summary (e.g., "n8n,AI,technology"). How to Adapt the Template This workflow is highly customizable. Here are several ways you can adapt it to fit your needs: Triggers Automate It:* The default trigger is manual. Change it to a *Schedule Trigger** to have your podcast automatically generated and sent to you at the same time every morning (e.g., 7:00 AM). Content Sources Weather:** In the "User Weather Map" node, you can change the forecast type or switch the units from metric to imperial. Calendar:** In the "Get Today Meetings" node, you can select a different calendar from your Google account (e.g., a shared work calendar instead of your personal one). News:** In the "Get Headlines From News Sources" node, change the country or category to get different top headlines. In the "Get Links From Keywords" node, update your keywords to track different topics. In the "Aggregate Headlines" (Gemini) node, you can modify the prompt to change the tone or length of the AI-generated news summary. Audio Generation Voice & Language:** The language is a starting parameter, but you can go deeper into the Google TTS nodes (Generate Virtual Parts, etc.) to select specific voices, genders, and speaking rates to create a unique podcast host style. Scripting:** Modify the Set and Merge nodes that construct the final script. You can easily change the greeting, the transition phrases between sections, or the sign-off message. Delivery Platform:** Don't use Telegram? Swap the Telegram node for a Slack node, Discord node, or even an Email node to send the MP3 file to your preferred platform. Message:** Customize the text message that is sent along with the audio file in the final node. An n8n automation workflow template by Atta.

By Trung Tran

Decodo Scraper API Workflow Template (n8n Automation Amazon Book Purchase Report) Watch the demo video below: > This workflow demos how to use Decodo Scraper API to crawl any public web page (headless JS, device emulation: mobile/desktop/tablet), extract structured product data from the returned HTML, generate a purchase-ready report, and automatically deliver it as a Google Doc + PDF to Slack/Drive. 🚀 Try Decodo — Web Scraping & Data API (Coupon: TRUNG) Decodo is a powerful public data access platform offering managed web scraping APIs and proxy infrastructure to collect structured web data at scale. It handles proxies, anti-bot protection, JavaScript rendering, retries, and global IP rotation—so you can focus on data, not scraping complexity. Why Decodo Managed Web Scraping API with anti-bot bypass & high success rates Works with JS-heavy sites; outputs JSON/HTML/CSV Easy integration (Python, Node.js, cURL) for eCommerce, SERP, social & general web data 🎟️ Special Discount Use coupon TRUNG to get the Advanced Scraping API plan — 23,000 requests for $5. Who’s it for Creators / Analysts** who need quick product lists (books, gadgets, etc.) with prices/ratings. Ops & Marketing teams** building weekly “top picks” reports. Engineers** validating the Decodo Scraper API + LLM extraction pattern before scaling. How it works / What it does Trigger – Manually run the workflow. Edit Fields (manual) – Provide inputs: targetUrl (e.g., an Amazon category/search/listing page) deviceType (desktop | mobile | tablet) Optional: maxItems, notes, reportTitle, reportOwner Scraper API Request (HTTP Request → POST) Calls Decodo Scraper API with: URL to crawl, headless JS enabled Device emulation (UA + viewport) Optional waitFor / executeJS to ensure late-loading content is captured HTML Response Parser (Code/Function or HTML node) Pulls the HTML string from Decodo response and normalizes it (strip scripts/styles, collapse whitespace). Product Analyzer Agent (LLM + Structured Output Parser) Prompts an LLM to extract structured “book” objects from the HTML: The Structured Output Parser enforces a strict JSON schema and drops malformed items. Build 📚 Book Purchase Report (Code/LLM) Converts the JSON array into a Markdown (or HTML) report with: Executive summary (top picks, average price/rating) Table of items (rank, title, author, price, rating, link) “Recommended to buy” shortlist (rules configurable) Notes / owner / timestamp Configure Google Drive Folder (manual) Choose/create a Drive folder for output artifacts. Create Document File (Google Docs API) Creates a Doc from the generated Markdown/HTML. Convert Document to PDF (Google Drive export) Exports the Doc to PDF. Upload report to Slack Sends the PDF (and/or Doc link) to a chosen Slack channel with a short summary. How to set up 1 Prerequisites n8n** (self-hosted or Cloud) Decodo Scraper API** key OpenAI (or compatible) API key** for the Analyzer Agent Google Drive/Docs** credentials (OAuth2) Slack** Bot/User token (files:write, chat:write) 2 Environment variables (recommended) DECODO_API_KEY OPENAI_API_KEY DRIVE_FOLDER_ID (optional default) SLACK_CHANNEL_ID 3 Nodes configuration (high level) Edit Fields (Set node) Scraper API Request (HTTP Request → POST) HTML Response Parser (Code node) Product Analyzer Agent Build Book Purchase Report (Code/LLM) Create Document File Convert to PDF Upload to Slack Requirements Decodo**: Active API key and endpoint access. Be mindful of concurrency/rate limits. Model**: GPT-4o/4.1-mini or similar for reliable structured extraction. Google**: OAuth client (Docs/Drive scopes). Ensure n8n can write to the target folder. Slack**: Bot token with files:write + chat:write. How to customize the workflow Target site: Change targetUrl to any **public page (category, search, or listing). For other domains (not Amazon), tweak the LLM guidance (e.g., price/label patterns). Device emulation**: Switch deviceType to mobile to fetch mobile-optimized markup (often simpler DOMs). Late-loading pages**: Adjust waitFor.selector or use waitUntil: "networkidle" (if supported) to ensure full content loads. Client-side JS**: Extend executeJS if you need to interact (scroll, click “next”, expand sections). You can also loop over pagination by iterating URLs. Extraction schema**: Add fields (e.g., discount_percent, bestseller_badge, prime_eligible) and update the Structured Output schema accordingly. Filtering rules**: Modify recommendation logic (e.g., min ratings count, price bands, languages). Report branding**: Add logo, cover page, footer with company info; switch to HTML + inline CSS for richer Docs formatting. Destinations**: Besides Slack & Drive, add Email, Notion, Confluence, or a database sink. Scheduling: Add a **Cron trigger for weekly/monthly auto-reports. An n8n automation workflow template by Trung Tran.

By Michael Taleb

Workflow Summary This workflow automatically scrapes new Reddit posts from your chosen subreddits and keywords, analyzes them with AI to extract summaries, pain points, and content angles, and then saves the insights into a Google Sheet. It’s a fully automated Content Research Engine that delivers fresh marketing ideas and community pain points straight into your database. Setting up the workflow Connect Reddit • In n8n, create a Reddit credential. • Add the subreddits and keywords you want to track. Connect Google Sheets • Make a copy of the database sheet. • Connect your Google account in n8n. Connect OpenAI • Add your OpenAI API key as a credential. • The AI will summarize posts, extract pain points, and suggest content ideas. Run the workflow • The workflow will search Reddit on a schedule. • Results are processed by AI and automatically added to your Google Sheet. An n8n automation workflow template by Michael Taleb.

By Jitesh Dugar

Overview Automatically generate professional PDF invoices when new orders are placed in Shopify. This template creates beautifully formatted invoices from order data, converts them to PDF, saves to Google Drive, and emails customers - all in one seamless workflow. 🎯 What This Template Does Transform your Shopify order fulfillment with complete invoice automation. When a customer places an order, this workflow automatically: ✅ Receives order data via Shopify webhook ✅ Validates payment status (only processes paid orders) ✅ Generates professional HTML invoice with your branding ✅ Converts to PDF using HTML to PDF conversion ✅ Saves invoice to Google Drive for record-keeping ✅ Emails PDF invoice to customer automatically ✅ Provides webhook response back to Shopify 🚀 Key Benefits Save Hours of Manual Work Eliminate manual invoice creation and sending Process unlimited orders 24/7 without intervention Professional invoices enhance your brand image Complete Automation No missed invoices - every paid order gets processed Automatic file organization in Google Drive Immediate customer notification improves satisfaction Professional Results Clean, branded invoice design that looks enterprise-ready Proper calculations for taxes, shipping, and totals PDF format suitable for accounting and customer records 🛠 What You'll Need Required Integrations: Shopify Store** - For order webhooks HTML to PDF Service** - For invoice conversion (API key required) Google Drive** - For invoice storage Email Provider** - For sending invoices to customers Technical Requirements: n8n instance (cloud or self-hosted) Basic webhook configuration in Shopify 10 minutes for initial setup 📋 Features Included Smart Order Processing Payment validation (only processes paid orders) Complete order data extraction (customer, items, addresses) Tax and shipping calculations Multi-currency support Professional Invoice Design Modern, clean layout with company branding Detailed line items with SKUs and quantities Proper totals breakdown (subtotal, tax, shipping) Customer billing and shipping addresses Automated Distribution PDF saved with descriptive filename (invoice-ORDER_NUMBER.pdf) Organized storage in Google Drive "Invoices" folder Professional email template with attachment Proper webhook responses for Shopify integration Error Handling Skips unpaid orders with proper notification Comprehensive data validation Detailed execution logs for troubleshooting 🎨 Customization Options Easy Branding Update company name, address, and contact details Modify color scheme and styling Add your logo and brand elements Invoice Layout Customize invoice template in HTML/CSS Add or remove fields as needed Modify PDF formatting options Email Templates Personalize customer email messages Add tracking links or additional information Customize sender details 💼 Perfect For E-commerce Stores** - Shopify merchants of any size Service Businesses** - Professional service invoicing Digital Products** - Immediate invoice delivery B2B Companies** - Automated business invoicing Accounting Teams** - Streamlined record-keeping 🔧 Setup Instructions Import Template - Add to your n8n instance Configure Webhook - Set up Shopify order webhook Add Credentials - Connect Google Drive and email accounts Update API Endpoint - Add your HTML to PDF service URL Customize Branding - Update company information in HTML template Test & Deploy - Run test orders to verify functionality 📊 Expected Results Time Savings: Save 15-30 minutes per order on manual invoice processing Accuracy: Eliminate human errors in invoice calculations Customer Experience: Immediate invoice delivery improves satisfaction Organization: All invoices automatically organized and stored Scalability: Handle thousands of orders without additional effort 🔗 Works With Shopify** (primary trigger) WooCommerce** (with minor modifications) Any HTML to PDF API** (Puppeteer, wkhtmltopdf, etc.) Google Drive** (file storage) Gmail/SMTP** (email delivery) 📈 Use Cases Retail Stores Automatic invoice generation for online orders Professional receipts for customer records Seamless integration with existing Shopify workflow Service Businesses Automated billing for completed services Professional invoice presentation Immediate delivery to clients Digital Products Instant invoice delivery upon purchase Automated VAT/tax handling for different regions Professional documentation for digital goods 🎯 ROI Calculator If you process 100 orders per month: Manual time**: 100 orders × 20 minutes = 33+ hours Cost savings**: 33 hours × $25/hour = $825/month Annual savings**: $9,900+ in labor costs alone Plus benefits of improved customer satisfaction, reduced errors, and better organization. 🚀 Get Started Ready to automate your invoice workflow? This template provides everything you need for professional, automated invoice generation that scales with your business. Installation Time: 10 minutes Skill Level: Beginner to Intermediate Maintenance: Zero - runs automatically once configured Transform your order fulfillment process today with this complete invoice automation solution!. An n8n automation workflow template by Jitesh Dugar.

By Don Jayamaha Jr

Instantly access live OKX Spot Market data directly in Telegram! This workflow integrates the OKX REST v5 API with Telegram and optional GPT-4.1-mini formatting, delivering real-time insights such as latest prices, order book depth, candlesticks, trades, and mark prices — all in clean, structured reports. 🔎 How It Works A Telegram Trigger node listens for incoming user commands. The User Authentication node validates the Telegram ID to allow only authorized users. The workflow creates a Session ID from chat.id to manage session memory. The OKX AI Agent orchestrates data retrieval via HTTP requests to OKX endpoints: Latest Price (/api/v5/market/ticker?instId=BTC-USDT) 24h Stats (/api/v5/market/ticker?instId=BTC-USDT) Order Book Depth (/api/v5/market/books?instId=BTC-USDT&sz=50) Best Bid/Ask (book ticker snapshot) Candlesticks / Klines (/api/v5/market/candles?instId=BTC-USDT&bar=15m) Average / Mark Price (/api/v5/market/mark-price?instType=SPOT&instId=BTC-USDT) Recent Trades (/api/v5/market/trades?instId=BTC-USDT&limit=100) Utility tools refine the data: Calculator → spreads, % change, normalized volumes. Think → reshapes raw JSON into clean text. Simple Memory → stores sessionId, symbol, and state for multi-turn interactions. A message splitter ensures Telegram output stays under 4000 characters. Final results are sent to Telegram in structured, human-readable format. ✅ What You Can Do with This Agent Get latest price and 24h stats for any Spot instrument. Retrieve order book depth with configurable size (up to 400 levels). View best bid/ask snapshots instantly. Fetch candlestick OHLCV data across intervals (1m → 1M). Monitor recent trades (up to 100). Check the mark price as a fair average reference. Receive clean, Telegram-ready reports (auto-split if too long). 🛠️ Setup Steps Create a Telegram Bot Use @BotFather to generate a bot token. Configure in n8n Import OKX AI Agent v1.02.json. Replace the placeholder in User Authentication node with your Telegram ID. Add Telegram API credentials (bot token). Add your OpenAI API key for GPT-4.1-mini. Add your OKX API key optional. Deploy and Test Activate the workflow in n8n. Send a query like BTC-USDT to your bot. Instantly get structured OKX Spot data back in Telegram. 📺 Setup Video Tutorial Watch the full setup guide on YouTube: ⚡ Unlock real-time OKX Spot Market insights directly in Telegram — no private API keys required! 🧾 Licensing & Attribution © 2025 Treasurium Capital Limited Company Architecture, prompts, and trade report structure are IP-protected. No unauthorized rebranding permitted. 🔗 For support: Don Jayamaha – LinkedIn. An n8n automation workflow template by Don Jayamaha Jr.

By SpaGreen Creative

Bulk WhatsApp Campaign Automation with Rapiwa API (Unofficial Integration) Who’s it for This n8n workflow lets you send bulk WhatsApp messages using your own number through Rapiwa API, avoiding the high cost and limitations of the official WhatsApp API. It integrates seamlessly with Google Sheets, where you can manage your contacts and messages with ease. Ideal for easy-to-maintain bulk messaging solution using their own personal or business WhatsApp number. This solution is perfect for small businesses, marketers, or teams looking for a cost-effective way to manage WhatsApp communication at scale. How it Works / What It Does Reads data from a Google Sheet where the Status column is marked as "pending". Cleans each phone number (removes special characters, spaces, etc.). Verifies if the number is a valid WhatsApp user using the Rapiwa API. If valid: Sends the message via Rapiwa. Updates Status = sent and Verification = verified. If invalid: Skips message sending. Updates Status = not sent and Verification = unverified. Waits for a few seconds (rate-limiting). Loops through the next item. The entire process is triggered automatically every 5 minutes. How to Set Up Duplicate the Sample Sheet: Use this format. Fill Contacts: Add columns like WhatsApp No, Name, Message, Image URL, and set Status = pending. Connect Google Sheets: Authenticate and link Google Sheets node inside n8n. Subscribe to Rapiwa: Go to Rapiwa.com and get your API key. Paste API Key: Use the HTTP Bearer token credential in n8n. Activate the Workflow: Let n8n take care of the automation. Requirements Google Sheets API credentials Configured Google Sheet (template linked above) WhatsApp (Personal or Business) n8n instance with credentials setup How to Customize the Workflow Add delay between messages**: Use the Wait node to introduce pauses (e.g., 5–10 seconds). Change message format**: Modify the HTTP Request node to send media or templates. Personalize content**: Include dynamic fields like Name, Image URL, etc. Error handling**: Add IF or SET nodes to capture failed attempts, retry, or log errors. Workflow Highlights Triggered every 5 minutes** using the Schedule Trigger node. Filters messages** with Status = pending. Cleans numbers* and *verifies WhatsApp existence** before sending. Sends WhatsApp messages** via Rapiwa (Unofficial API). Updates Google Sheets** to mark Status = sent or not sent and Verification = verified/unverified. Wait node** prevents rapid-fire sending that could lead to being flagged by WhatsApp. Setup in n8n 1. Connect Google Sheets Add a Google Sheets node Authenticate using your Google account Select the document and worksheet Use filter: Status = pending 2. Loop Through Rows Use SplitInBatches or a Code node to process rows in small chunks (e.g., 5 rows) Add a Wait node to delay 5 seconds between messages 3. Send Message via HTTP Node How the "Send Message Using Rapiwa" Node Sends Messages This node makes an HTTP POST request to the Rapiwa API endpoint: https://app.rapiwa.com/api/send-message It uses Bearer Token Authentication with your Rapiwa API key. When this node runs, it sends a WhatsApp message to the specified number with the given text and optional image. The Rapiwa API handles message delivery using your own WhatsApp number connected to their service. JSON Body**: { "number": "{{ $json['WhatsApp No'] }}", "message": "{{ $json['Message'] }}" } Sample Google Sheet Structure A Google Sheet formatted like this sample | SL | WhatsApp No | Name | Message | Image URL | Verification | Status | |----|----------------|------------------------|----------------------|---------------------------------------------------------------------------|--------------|---------| | 1 | 8801322827799 | SpaGreen Creative | This is Test Message | https://spagreen.sgp1.cdn.digitaloceanspaces.com/... | verified | sent | | 2 | 8801725402187 | Abdul Mannan Zinnat | This is Test Message | https://spagreen.sgp1.cdn.digitaloceanspaces.com/... | verified | sent | Tips Modify the Limit node to increase/decrease messages per cycle. Adjust the Wait node to control how fast messages are sent (e.g., 5–10s delay). Make sure WhatsApp numbers are properly formatted (e.g., 8801XXXXXXXXX, no +, no spaces). Store your Rapiwa API key securely using n8n credentials. Use publicly accessible image URLs if sending images. Always mark processed messages as "sent" to avoid duplicates. Use the Error workflow in n8n to catch failed sends for retry. Test with a small batch before going full-scale. Schedule the Trigger node for every 5 minutes to keep automation running. Useful Links Dashboard:** https://app.rapiwa.com Official Website:** https://rapiwa.com Documentation:** https://docs.rapiwa.com Support & Community Need help setting up or customizing the workflow? Reach out here: WhatsApp: Chat with Support Discord: Join SpaGreen Server Facebook Group: SpaGreen Community Website: SpaGreen Creative Envato: SpaGreen Portfolio. An n8n automation workflow template by SpaGreen Creative.

By Automate With Marc

Automatic Personalized Sales Follow-Up with GPT-5, Pinecone, and Tavily Research Description Never let a lead go cold. This workflow automatically sends personalized follow-up emails to every inbound inquiry. It combines GPT-5, Pinecone Vector DB, and Tavily Research to craft responses that align with your brand’s best practices, tone, and the latest product updates. With embedded research tools, every response is both timely and relevant—helping your sales team convert more leads without manual effort. 👉 Watch step-by-step builds of workflows like these on: www.youtube.com/@automatewithmarc How It Works Form Trigger – Captures inbound lead details (name, company, email, and message). AI Sales Agent (GPT-5) – Researches the lead’s business and problem statement, referencing Pinecone for your brand guidelines and product updates. Uses Tavily research for real-time enrichment. Structured Output Parser – Ensures the subject line and email body are formatted cleanly in JSON. Send Follow-Up Email (Gmail Node) – Delivers a polished, ready-to-go follow-up directly to the lead. Simple Memory – Maintains context across follow-ups for more natural conversations. Why Sales Teams Will Love It ⏱ Faster responses — every lead gets an immediate, high-quality reply. 📝 On-brand every time — Pinecone ensures tone matches your playbook. 🌍 Research-driven — Tavily enriches responses with fresh, relevant context. 📈 Higher conversions — timely, personalized outreach drives more meetings. 🤖 Hands-off automation — sales reps focus on closing, not chasing. Setup Instructions Form Trigger Configure your inbound form to capture lead details (name, email, company, message). Connect it to this workflow. Pinecone Setup Create a Pinecone index and embed your brand guidelines, sales playbook, and product updates. Update the Pinecone Vector Store node with your index name. Tavily Setup Add your Tavily API key to the Tavily Research node. OpenAI Setup Add your OpenAI API key to the GPT-5 Chat Model node. Adjust the system prompt inside the AI Agent to reflect your company’s style and tone. Gmail Node Connect your Gmail account to the Send Follow-Up Email node. Update sender details if you want the emails to come from a shared inbox or a rep’s personal account. Customization Tone of Voice – Modify the system prompt inside the AI Agent to be more professional, casual, or industry-specific. Scheduling Links – Replace the default Calendly link with your own booking tool. Form Fields – Add or remove fields depending on the information you collect (e.g., budget, role, region). Requirements Gmail account (for sending follow-up emails) OpenAI API key (GPT-5) Pinecone account (for storing/retrieving guidelines + updates) Tavily API key (for online research enrichment). An n8n automation workflow template by Automate With Marc.

By SerpApi

Google Play Store App Rank and Rating Monitoring What and who this is for This workflow will be useful for anyone looking to do SEO tracking on the Google Play Store. It automates checking Google Play Store rank positions and average ratings for a list of app titles. The SerpApi component can also be modified to use other APIs for anyone looking for SEO tracking on any other search engine supported by SerpApi. How it works This workflow takes in a list of keywords and app titles to identify the apps' rank in Google Play Store search results. It also grabs the average rating of the app. The search uses SerpApi's Google Play Store API. The results are then synced to two different sheets in a Google Sheet. The first is a log of all past run. The latest results are appended to the bottom of the log. The second updates a kind of "dashboard" to show the results from the latest run. The workflow includes a Wait node that delays 4 seconds between each app title and keyword pair to prevent hitting the default Google Sheets' API per minute rate limit. You can delete this if you have a high enough custom rate limit on the Google Sheets API. The Schedule Trigger is configured to run at 10 AM UTC every day. How to use Create a free SerpApi account here: https://serpapi.com/ Add SerpApi credentials to n8n. Your SerpApi API key is here: https://serpapi.com/manage-api-key Connect your Google Sheets accounts to n8n. Help available here: https://n8n.io/integrations/google-sheets/ Copy this Google Sheet to your own Google account: https://docs.google.com/spreadsheets/d/1DiP6Zhe17tEblzKevtbPqIygH3dpPCW-NAprxup0VqA/edit?gid=1750873622#gid=1750873622 Set your own list of keywords and app titles to match in the 'Latest Run' sheet. This is the source list used to run the searches and must be set. Connect your Google Sheet in the 'Get Keywords and Titles to Match' Google Sheet node Connect your Google Sheet in the 'Update Rank & Rating Log' Google Sheet node Connect your Google Sheet again in the 'Update Latest Run' Google Sheet node (Optional) Update the schedule or disable the schedule to only run manually Documentation SerpApi Google Play Store API SerpApi n8n Node Intro Guide. An n8n automation workflow template by SerpApi.

By SpaGreen Creative

WhatsApp Bulk Number Verification in Google Sheets Using Unofficial Rapiwa API Who’s it for This workflow is for marketers, small business owners, freelancers, and support teams who want to automate WhatsApp messaging using a Google Sheet without the official WhatsApp Business API. It’s suitable when you need a budget-friendly, easy-to-maintain solution that uses your personal or business WhatsApp number via an unofficial API service such as Rapiwa. How it works / What it does The workflow looks for rows in a Google Sheet where the Status column is pending. It cleans each phone number (removes non-digits). It verifies the number with the Rapiwa verify endpoint (/api/verify-whatsapp). If the number is verified: The workflow can send a message (optional). It updates the sheet: Verification = verified, Status = sent (or leaves Status for the send node to update). If the number is not verified: It skips sending. It updates the sheet: Verification = unverified, Status = not sent. The workflow processes rows in batches and inserts short delays between items to avoid rate limits. The whole process runs on a schedule (configurable). Key features Scheduled automatic checks (configurable interval; recommended 5–10 minutes). Cleans phone numbers to a proper format before verification. Verifies WhatsApp registration using Rapiwa. Batch processing with limits to control workload (recommended max per run configurable). Short delay between items to reduce throttling and temporary blocks. Automatic sheet updates for auditability (verified/unverified, sent/not sent). Defaults recommended in this workflow Trigger interval: every 5–10 minutes (adjustable). Max items per run: configurable (example: 200 max per cycle). Delay between items: 2–5 seconds (example uses 3 seconds). How to set up Duplicate the sample Google Sheet: ➤ Sample Fill contact rows and set Status = pending. Include columns like WhatsApp No, Name, Message, Verification, Status. In n8n, add and authenticate a Google Sheets node pointed to your sheet. Create an HTTP Bearer credential in n8n and paste your Rapiwa API key. Configure the workflow nodes (Trigger → Google Sheets → Limit/SplitInBatches → Code (clean) → HTTP Request (verify) → If → Update Sheet → Wait). Enable the workflow and monitor first runs with a small test batch. Requirements n8n instance with Google Sheets and HTTP Request nodes enabled. Google Sheets OAuth2 credentials configured in n8n. Rapiwa account and Bearer token (stored in n8n credentials). Google Sheet formatted to match the workflow columns. Why use Rapiwa Cost-effective and developer-friendly REST API for WhatsApp verification and sending. Simple integration via HTTP requests and n8n. Useful when you prefer not to use the official WhatsApp Business API. Note: Rapiwa is an unofficial service — review its terms and risks before production use. How to customize Change schedule frequency in the Trigger node. Adjust maxItems in Limit/SplitInBatches for throughput control. Change the Wait node delay for safer sending. Modify the HTTP Request body to support media or templates if the provider supports it. Add logging or a separate audit sheet to record API responses and errors. Best practices Test with a small batch first. Keep the sheet headers exact and consistent. Store API keys in n8n credentials (do not hardcode). Increase Wait time or reduce batch size if you see rate limits. Keep a log sheet of verified/unverified rows for troubleshooting. Example HTTP verify body (n8n HTTP Request node) { "number": "{{ $json['WhatsApp No'] }}" } Notes and best practices Test with a small batch before scaling. Store the Rapiwa token in n8n credentials, not in node fields. Increase Wait delay or reduce batch size if you see rate limits or temporary blocks. Keep the sheet headers consistent; the workflow matches columns by name. Log API responses or errors for troubleshooting. Optional Add a send-message HTTP Request node after verification to send messages. Append successful and failed rows to separate sheets for easy review. Support & Community Need help setting up or customizing the workflow? Reach out here: WhatsApp: Chat with Support Discord: Join SpaGreen Server Facebook Group: SpaGreen Community Website: SpaGreen Creative Envato: SpaGreen Portfolio. An n8n automation workflow template by SpaGreen Creative.

By Mohammad

Telegram ticket intake and status tracking with Postgres Who’s it for Anyone running support requests through Telegram, Email, Webhooks, and so on who needs a lightweight ticketing system without paying Zendesk prices. Ideal for small teams, freelancers, or businesses that want tickets logged in a structured database (Postgres) and tracked automatically. I'm using Telegram since it's the most convenient one. How it works / What it does This workflow turns (Telegram) into a support desk: Receives new requests via a Telegram bot command. Creates a ticket in a Postgres database with a correlation ID, requester details, and status. Auto-confirms back to the requester with the ticket ID. Provides ticket updates (status changes, resolutions) when queried. Keeps data clean using dedupe keys and controlled input handling. How to set up Create a Telegram bot using @BotFather and grab the token. Connect your Postgres database to n8n and create a tickets table: CREATE TABLE tickets ( id BIGSERIAL PRIMARY KEY, correlation_id UUID, source TEXT, external_id TEXT, requester_name TEXT, requester_email TEXT, requester_phone TEXT, subject TEXT, description TEXT, status TEXT, priority TEXT, dedupe_key TEXT, chat_id TEXT, created_at TIMESTAMP DEFAULT NOW(), updated_at TIMESTAMP DEFAULT NOW() ); Add your Telegram and Postgres credentials in n8n (via the Credentials tab, not hardcoded). Import the workflow JSON and replace the placeholder credentials with yours. Test by sending /new in Telegram and follow the prompts. Requirements n8n (latest version recommended) Telegram bot token Postgres instance (local, Docker, or cloud) How to customize the workflow Change database fields if you need more requester info. Tweak the Switch node and Comands for multiple status types. Extend with Slack, Discord, or email nodes for broader notifications. Integrate with external systems (CRM, project management) by adding more branches. An n8n automation workflow template by Mohammad.

By Ronnie Craig

AI Personal Assistant Template Template Overview Template Name: AI Personal Assistant - Task & Email Management Price: $27 Category: Productivity & Automation Difficulty: Intermediate Use Case: Personal productivity automation for busy professionals Description Transform your daily workflow with this comprehensive AI Personal Assistant that manages your tasks, emails, and calendar through simple Telegram conversations. This template combines the power of AI with seamless integrations to create your ultimate productivity companion. Key Features 🤖 AI-Powered Personal Assistant Intelligent conversation handling with memory Natural language processing for commands Context-aware responses and task management Support for both voice and text messages 📧 Complete Email Management Automatically read and summarize unread emails Send emails on your behalf with AI-generated content Smart email categorization and priority handling Gmail integration with OAuth2 security 📅 Advanced Calendar Integration Create calendar events from natural language Read upcoming events and schedule conflicts Delete and modify calendar entries Automatic timezone handling 📋 Intelligent Task Management Add tasks via voice or text commands Due date tracking with ISO 8601 formatting Status updates (pending/completed) Smart task categorization and prioritization ⏰ Automated Reminder System 30-minute interval reminder checks Smart filtering to prevent duplicate notifications Customizable reminder messages with emojis Automatic status tracking to prevent spam 🎙️ Voice & Text Processing OpenAI Whisper voice transcription Seamless voice-to-text conversion Support for multiple languages Text cleaning and formatting Technical Specifications Required Integrations Telegram Bot API - Main interface for user interaction OpenAI API - AI responses and voice transcription Google Gmail API - Email reading and sending Google Calendar API - Calendar event management Google Sheets API - Task data storage and management Node Count Total Nodes**: 30+ Trigger Nodes**: 2 (Telegram, Schedule) AI Nodes**: 2 (Agent, OpenAI) Integration Nodes**: 12 (Google services, Telegram) Logic Nodes**: 8 (Code, Switch, Set) Documentation Nodes**: 15 (Sticky Notes) Performance Features Memory Management**: Conversation context retention Duplicate Prevention**: Hash-based response filtering Error Handling**: Robust date parsing and validation Scalability**: Multi-user support with dynamic session IDs Setup Requirements 1. Telegram Bot Setup Create bot via @BotFather Get bot token Add token to Telegram nodes Get your chat ID for reminders 2. Google Services Configuration Enable Gmail, Calendar, and Sheets APIs Create OAuth2 credentials Authorize n8n access Create task management spreadsheet 3. OpenAI API Setup Get OpenAI API key Configure for GPT-4o-mini model Enable Whisper for voice transcription 4. Google Sheets Structure Required columns: Task Name (text) Due Date (ISO 8601 format) Status (pending/completed) Reminder Sent (yes/no) Installation Instructions Step 1: Import Template Download the JSON file Import into n8n workflow Activate the workflow Step 2: Configure Credentials Set up all required API credentials Test each integration separately Replace placeholder values with actual IDs Step 3: Customize Settings Update AI system message with your details Set your Telegram chat ID for reminders Adjust reminder frequency if needed Step 4: Test Functionality Send test message to Telegram bot Try voice message transcription Test task creation and email sending Verify reminder system works Usage Examples Creating Tasks "Add a task to call John tomorrow at 2 PM" "Remind me to submit report by Friday 5 PM" 🎙️ Voice: "Create task for grocery shopping this weekend" Email Management "Check my unread emails and summarize them" "Send email to team about meeting tomorrow" "Draft response to latest client email" Calendar Management "Schedule dentist appointment next Tuesday 10 AM" "What meetings do I have tomorrow?" "Cancel my 3 PM meeting today" General Assistance "What tasks are due today?" "Show me my schedule for this week" "Mark grocery shopping task as completed" Customization Options AI Personality Modify system message to change assistant tone Add specific knowledge about your industry Include personal preferences and shortcuts Reminder Frequency Change from 30-minute to custom intervals Set specific reminder times (e.g., 9 AM daily) Add weekend/holiday awareness Integration Extensions Add Slack or Discord support Include additional calendar providers Integrate with project management tools Troubleshooting Guide Common Issues Voice not transcribing: Check OpenAI API credits Reminders not sending: Verify chat ID and Telegram token Calendar events not creating: Check timezone settings Tasks not saving: Verify Google Sheets permissions Performance Optimization Monitor API usage and costs Implement rate limiting for heavy users Regular cleanup of completed tasks Optimize memory usage for long conversations Value Proposition Time Savings 2-3 hours daily** saved on manual task management Instant email processing** instead of constant checking Automated scheduling** eliminates back-and-forth Voice commands** for hands-free operation Cost Comparison Personal assistant service: $2000+/month Multiple productivity apps: $100+/month Custom development: $5000+ This template: $27 one-time** ROI Calculation Time saved: 15 hours/week × $50/hour = $750/week Monthly value: $3000+ Template cost: $27 ROI: 11,000%+ in first month** Target Audience Primary Users Entrepreneurs** managing multiple ventures Executives** with complex schedules Consultants** juggling client communications Remote workers** needing better organization Skill Level Beginner**: Can use with basic setup Intermediate**: Can customize and extend Advanced**: Can modify for enterprise use Support & Documentation Included Documentation Complete setup guide with screenshots Video walkthrough (optional) Troubleshooting checklist Customization examples Community Support Template-specific Discord channel Regular updates and improvements User-contributed extensions Best practices sharing Legal & Compliance Data Privacy All data stays in your Google/Telegram accounts No third-party data storage GDPR compliant with proper configuration End-to-end encryption for sensitive communications API Compliance Follows all provider terms of service Respects rate limits and usage policies Secure credential management Regular security updates Version History v1.0 (Current) Initial release with core features Full voice and text support Comprehensive integrations Automated reminder system Planned Updates v1.1: Enhanced AI capabilities v1.2: Additional calendar providers v1.3: Team collaboration features v1.4: Mobile app integration Conclusion This AI Personal Assistant template represents the pinnacle of personal productivity automation. For just $27, you get a system that rivals expensive custom solutions and provides immediate value through intelligent task management, email automation, and seamless calendar integration. The template is designed for both beginners looking for a powerful productivity boost and advanced users who want a solid foundation for further customization. With comprehensive documentation and proven real-world effectiveness, this template is an investment that pays for itself within days. Transform your productivity today with the AI Personal Assistant template - because time is your most valuable asset. Template created by productivity automation experts. Tested with 500+ hours of real-world usage. Satisfaction guaranteed with 30-day money-back promise. An n8n automation workflow template by Ronnie Craig.

By SpaGreen Creative

Automated WhatsApp Welcome Messages for Sales Leads with Google Sheets & Rapiwa Who is this for? This automation is ideal for sales teams, digital marketers, support agents, or small business owners who collect leads in Google Sheets and want to automatically send WhatsApp welcome messages. It's a cost-effective and easy-to-use solution built for those not using the official WhatsApp Business API but still looking to scale communication. What this Workflow Does This n8n automation reads leads from a connected Google Sheet, verifies if the provided WhatsApp numbers are valid using the Rapiwa API, and sends a personalized welcome message. It updates the sheet based on delivery success or failure, and continues this process every 5 minutes — ensuring new leads are automatically engaged. Key Features Automatic Scheduling**: Runs every 5 minutes (adjustable) Google Sheets Integration**: Reads and updates lead data WhatsApp Number Validation**: Confirms number validity via Rapiwa Personalized Messaging**: Uses lead name for custom messages Batch Processing**: Sends up to 60 messages per cycle Safe API Usage**: Adds 5-second delay between each message Error Handling**: Marks failed messages as not sent and unverified Live Status Updates**: Sheet columns are updated after each attempt Loop Logic**: Repeats continuously to catch new rows How to Use Step-by-step Setup Prepare Your Google Sheet Copy this Sample Sheet Ensure it includes the following columns: WhatsApp No name (note: trailing space is required) row_number status, check, validity Connect Google Sheets in n8n Use OAuth2 credentials to allow n8n access Set the workflow to fetch rows where check is not empty Get a Rapiwa Account Sign up at https://rapiwa.com Add your WhatsApp number Retrieve your Bearer Token from your Rapiwa dashboard Configure HTTP Request Nodes Use Rapiwa's API endpoints: Verify Number: https://app.rapiwa.com/api/verify-whatsapp Send Message: https://app.rapiwa.com/api/send-message Add your Bearer Token to the header Start Your Workflow Run the n8n automation It will read leads, clean phone numbers, verify WhatsApp validity, send messages, and update the sheet accordingly Requirements A Google Sheet with correctly formatted columns Active Rapiwa subscription (~$5/month) A valid Bearer Token from Rapiwa Your WhatsApp number connected to Rapiwa n8n instance with: Google Sheets integration (OAuth2 setup) HTTP Request capability Google Sheet Column Reference | name | number | email | time | check | validity | status | |-----------------|--------------|-------------------|-----------------------------|---------|------------|-----------| | Abdul Mannan | 8801322827799| contact@spagreen.net| September 14th 2025, 10:34 | checked | verified | sent | | Abdul Mannan | 8801322827798| contact@spagreen.net| September 14th 2025, 10:34 | checked | unverified | not sent | Workflow Logic Summary Trigger Every 5 Minutes Fetch All Rows with Pending Status Limit to 60 Rows per Execution Clean and Format Phone Numbers Check Number Validity via Rapiwa Condition Check: If valid → Send Message If invalid → Update status as not sent, unverified Send WhatsApp Message via Rapiwa Update Sheet Row On success: sent, verified, checked On failure: not sent, unverified Delay 5 seconds before next message Repeat for next lead Customization Ideas Add image or document sending support via Rapiwa Customize messages based on additional fields (e.g., product, service) Log failures to a separate sheet Send admin email for failed batches Add support for multilingual messages Notes & Warnings The column name "name " includes a space — do not remove or rename it. International number format is required for Rapiwa to work correctly. If you're sending many messages, increase the Wait node delay to prevent API throttling. Support WhatsApp Support: Chat Now Discord: Join SpaGreen Community Facebook Group: SpaGreen Support Website: https://spagreen.net Developer Portfolio: Codecanyon SpaGreen. An n8n automation workflow template by SpaGreen Creative.

By Robert Breen

Automate company enrichment directly in Google Sheets using Dun & Bradstreet (D&B) Data Blocks. This workflow reads DUNS numbers from a sheet, fetches a Bearer token (via Basic Auth → /v3/token), calls the Data Blocks API for each row (/v1/data/duns/...), extracts Paydex, and appends or updates the sheet. A Filter node skips rows already marked Complete for efficient, idempotent runs. ✅ What this template does Pulls DUNS values from a Google Sheet (Option A) Uses an HTTP Header Auth credential for D&B, or (Option B) Dynamically fetches a Bearer token from /v3/token (Basic Auth) Calls D&B Data Blocks per row to retrieve payment insights Extracts Paydex and upserts results back to the sheet Skips rows already Complete 👤 Who's it for RevOps/Data teams enriching company lists at scale SDR/Marketing teams validating firmographic/credit signals BI/Automation builders who want a no-code/low-code enrichment loop 🧩 How it works (node-by-node) Get Companies (Google Sheets) – Reads rows with at least duns, paydex, Complete. Only New Rows (Filter) – Passes only rows where Complete is empty. D&B Info (HTTP Request) – Calls Data Blocks for each DUNS using a header credential (Authorization: Bearer <token>). Keep Score (Set) – Maps nested JSON to a single Paydex field: {{$json.organization.businessTrading[0].summary[0].paydexScoreHistory[0].paydexScore}} Append to g-sheets (Google Sheets) – Append or Update by duns, writing paydex and setting Complete = Yes. > The workflow also includes Sticky Notes with in-canvas setup help. 🛠️ Setup instructions (from the JSON) 1) Connect Google Sheets (OAuth2) In n8n → Credentials → New → Google Sheets (OAuth2) and sign in. Use/prepare a sheet with columns like: duns, paydex, Complete. In your Google Sheets nodes, select your credential and target spreadsheet/tab. For upsert behavior, set Operation to Append or Update and Matching column to duns. > Replace any example Sheet IDs/URLs with your own (avoid publishing private IDs). 2) Get a D&B Bearer Token (Basic Auth → /v3/token) — Optional Dynamic Token Node Add/enable HTTP Request node named Get Bearer Token1. Configure: Authentication: Basic Auth (your D&B username/password) Method: POST URL: https://plus.dnb.com/v3/token Body Parameters: grant_type = client_credentials Headers: Accept = application/json Execute to receive access_token. Reference the token in other nodes via: Authorization: Bearer {{$node["Get Bearer Token1"].json["access_token"]}} > ⚠️ Security: Don't hardcode tokens. Prefer credentials or fetch dynamically. 3) Call D&B Data Blocks (use Header Auth or dynamic token) Node: D&B Info (HTTP Request) Authentication:** Header Auth (recommended) URL:** https://plus.dnb.com/v1/data/duns/{{ $json.duns }}?blockIDs=paymentinsight_L4_v1&tradeUp=hq&customerReference=customer%20reference%20text&orderReason=6332 Headers:** Accept = application/json If not using a stored Header Auth credential, set: Authorization = Bearer {{$node["Get Bearer Token1"].json["access_token"]}} > {{ $json.duns }} is resolved from the current row provided by Get Companies. 4) Map Paydex and Upsert to Google Sheets Keep Score (Set)** Field Paydex (Number): {{$json.organization.businessTrading[0].summary[0].paydexScoreHistory[0].paydexScore}} Append to g-sheets (Google Sheets)** Operation: Append or Update Matching column: duns Columns mapping: duns = {{ $('Get Companies').item.json.duns }} paydex = {{ $json.Paydex }} Complete = Yes 🧪 Test checklist Add a few test DUNS rows (leave Complete blank). Run the workflow and confirm Only New Rows passes expected items. Check D&B Info returns payment insight data. Confirm Paydex is set and the row is updated with Complete = Yes. 🔐 Security & best practices Store secrets in Credentials (HTTP Header Auth/Basic Auth). Avoid publishing real Sheet IDs or tokens in screenshots/notes. Consider rate limits and backoff for large sheets. Log/handle API errors (e.g., invalid DUNS or expired tokens). 🩹 Troubleshooting 401/403 from D&B:** Verify credentials/token; ensure correct environment and entitlements. Missing Paydex path:** D&B responses vary by subscription/data availability—add guards (IF node) before mapping. Rows not updating:* Confirm *Append or Update* is used and *Matching column** exactly matches your sheet header duns. Filtered out rows:** Ensure Complete is truly empty (no spaces) for new items. 🧯 Customize further Enrich additional fields (e.g., viability score, portfolio comparison, credit limits). Add retry logic, batching, or scheduled triggers. Push results to a CRM/DB or notify teams via Slack/Email. 📬 Contact Need help customizing this (e.g., enriching more fields, normalizing responses, or bulk-processing large sheets)? 📧 robert@ynteractive.com 🔗 https://www.linkedin.com/in/robert-breen-29429625/ 🌐 https://ynteractive.com. An n8n automation workflow template by Robert Breen.

By Robert Breen

Pull a Dun & Bradstreet Business Information Report (PDF) by DUNS, convert the response into a binary PDF file, extract readable text, and use OpenAI to return a clean, flat JSON with only the key fields you care about (e.g., report date, Paydex, viability score, credit limit). Includes Sticky Notes for quick setup help and guidance. ✅ What this template does Requests a D&B report* (PDF) for a specific *DUNS** via HTTP Converts* the API response into a *binary PDF file** Extracts** the text from the PDF for analysis Uses OpenAI with a Structured Output Parser to return a flat JSON Designed to be extended to Sheets, databases, or CRMs 🧩 How it works (node-by-node) Manual Trigger — Runs the workflow on demand ("When clicking 'Execute workflow'"). D&B Report (HTTP Request) — Calls the D&B Reports API for a Business Information Report (PDF). Convert to PDF File (Convert to File) — Turns the D&B response payload into a binary PDF. Extract Binary (Extract from File) — Extracts text content from the PDF. OpenAI Chat Model — Provides the language model context for the analyzer. Analyze PDF (AI Agent) — Reads the extracted text and applies strict rules for a flat JSON output. Structured Output (AI Structured Output Parser) — Enforces a schema and validates/auto-fixes the JSON shape. (Optional) Get Bearer Token (HTTP Request) — Template guidance for OAuth token retrieval (shown as disabled; included for reference if you prefer Bearer flows). 🛠️ Setup instructions (from the JSON) 1) D&B Report (HTTP Request) Auth:* Header Auth (use an n8n *HTTP Header Auth** credential) URL:** https://plus.dnb.com/v1/reports/duns/804735132?productId=birstd&inLanguage=en-US&reportFormat=PDF&orderReason=6332&tradeUp=hq&customerReference=customer%20reference%20text Headers:** Accept: application/json Credential Example:** D&B (HTTP Header Auth) > Put your Authorization: Bearer <token> header inside this credential, not directly in the node. 2) Convert to PDF File (Convert to File) Operation:** toBinary Source Property:** contents[0].contentObject > This takes the PDF content from the D&B API response and converts it to a binary file for downstream nodes. 3) Extract Binary (Extract from File) Operation:** pdf > Produces a text field with the extracted PDF content, ready for AI analysis. 4) OpenAI Model(s) OpenAI Chat Model** Model:** gpt-4o (as configured in the JSON) Credential:* Your stored *OpenAI API* credential (do *not** hardcode keys) Wiring:** Connect OpenAI Chat Model as ai_languageModel to Analyze PDF Connect another OpenAI Chat Model (also gpt-4o) as ai_languageModel to Structured Output 5) Analyze PDF (AI Agent) Prompt Type:** define Text:** ={{ $json.text }} System Message (rules):** You are a precision extractor. Read the provided business report PDF and return only a single flat JSON object with the fields below. No arrays/lists. No prose. If a value is missing, output null. Dates: YYYY-MM-DD. Numbers: plain numerics (no commas or $). Prefer most recent or highest-level overall values if multiple are shown. Never include arrays, nested structures, or text outside of the JSON object. 6) Structured Output (AI Structured Output Parser) JSON Schema Example:** { "report_date": "", "company_name": "", "duns": "", "dnb_rating_overall": "", "composite_credit_appraisal": "", "viability_score": "", "portfolio_comparison_score": "", "paydex_3mo": "", "paydex_24mo": "", "credit_limit_conservative": "" } Auto Fix:** enabled Wiring:* Connect as ai_outputParser to *Analyze PDF** 7) (Optional) Get Bearer Token (HTTP Request) — Disabled example If you prefer fetching tokens dynamically: Auth:** Basic Auth (D&B username/password) Method:** POST URL:** https://plus.dnb.com/v3/token Body Parameters:** grant_type = client_credentials Headers:** Accept: application/json Downstream usage:** Set header Authorization: Bearer {{$json["access_token"]}} in subsequent calls. > In this template, the D&B Report node uses Header Auth credential instead. Use one strategy consistently (credentials are recommended for security). 🧠 Output schema (flat JSON) The analyzer + parser return a single flat object like: { "report_date": "2024-12-31", "company_name": "Example Corp", "duns": "123456789", "dnb_rating_overall": "5A2", "composite_credit_appraisal": "Fair", "viability_score": "3", "portfolio_comparison_score": "2", "paydex_3mo": "80", "paydex_24mo": "78", "credit_limit_conservative": "25000" } 🧪 Test flow Click Execute workflow (Manual Trigger). Confirm D&B Report returns the PDF response. Check Convert to PDF File for a binary file. Verify Extract from File produces a text field. Inspect Analyze PDF → Structured Output for valid JSON. 🔐 Security notes Do not hardcode tokens in nodes; use Credentials (HTTP Header Auth or Basic Auth). Restrict who can execute the workflow if it's accessible from outside your network. Avoid storing sensitive payloads in logs; mask tokens/headers. 🧩 Customize Map the structured JSON to Google Sheets, Postgres/BigQuery, or a CRM. Extend the schema with additional fields (e.g., number of employees, HQ address) — keep it flat. Add validation (Set/IF nodes) to ensure required fields exist before writing downstream. 🩹 Troubleshooting Missing PDF text?* Ensure *Convert to File** source property is contents[0].contentObject. Unauthorized from D&B?** Refresh/verify token; confirm Header Auth credential contains Authorization: Bearer <token>. Parser errors?** Keep the agent output short and flat; the Structured Output node will auto-fix minor issues. Different DUNS/product?** Update the D&B Report URL query params (duns, productId, etc.). 🗒️ Sticky Notes (included) Overview:** "Fetch D&B Company Report (PDF) → Convert → Extract → Summarize to Structured JSON (n8n)" Setup snippets for Data Blocks (optional) and Auth flow 📬 Contact Need help customizing this (e.g., routing the PDF to Drive, mapping JSON to your CRM, or expanding the schema)? 📧 robert@ynteractive.com 🔗 https://www.linkedin.com/in/robert-breen-29429625/ 🌐 https://ynteractive.com. An n8n automation workflow template by Robert Breen.

By Robert Breen

Use this template to upload an image, run a first-pass OpenAI Vision analysis, then re-attach the original file (binary/base64) to the next step using a Merge node. The pattern ensures your downstream AI Agent (or any node) can access both the original file (data) and the first analysis result (content) at the same time. ✅ What this template does Collects an image file* via *Form Trigger** (binary field labeled data) Analyzes the image* with *OpenAI Vision* (GPT-4o) using *base64** input Merges* the original upload and the analysis result (combine by position) so the next node has *both** Re-analyzes/uses* the image alongside the first analysis in an *AI Agent** step 🧩 How it works (Node-by-node) Form Trigger Presents a simple upload form and emits a binary/base64 field named data. Analyze image (OpenAI Vision) Reads the same data field as base64 and runs image analysis with GPT-4o. The node outputs a text content (first-pass analysis). Merge (combine by position) Combines the two branches so the next node receives both the original upload (data) and the analysis (content) on the same item. AI Agent Receives data + content together. Prompt includes the original image (=data) and the first analysis ({{$json.content}}) to compare or refine results. OpenAI Chat Model Provides the language model for the Agent (wired as ai_languageModel). 🛠️ Setup Instructions (from the JSON) > Keep it simple: mirror these settings and you’re good to go. 1) Form Trigger (n8n-nodes-base.formTrigger) Path:* d6f874ec-6cb3-46c7-8507-bd647c2484f0 *(you can change this) Form Title:** Image Document Upload Form Description:** Upload a image document for AI analysis Form Fields:** Label: data Type: file Output:* emits a binary/base64 field named *data**. 2) Analyze image (@n8n/n8n-nodes-langchain.openAi) Resource:** image Operation:** analyze Model:** gpt-4o Text:* =data *(use the uploaded file field) Input Type:** base64 Credentials:* OpenAI (use your stored *OpenAI API** credential) 3) Merge (n8n-nodes-base.merge) Mode:** combine Combine By:** combineByPosition Connect Form Trigger → Merge (input 2) Connect Analyze image → Merge (input 1) This ensures the original file (data) and the analysis (content) line up on the same item. 4) AI Agent (@n8n/n8n-nodes-langchain.agent) Prompt Type:** define Text:** System Message:** analyze the image again and see if you get the same result. Receives:** merged item containing data + content. 5) OpenAI Chat Model (@n8n/n8n-nodes-langchain.lmChatOpenAi) Model:** gpt-4.1-mini Wiring:* connect as *ai_languageModel* to the *AI Agent** Credentials:** same OpenAI credential as above > Security Note: Store API keys in Credentials (do not hardcode keys in nodes). 🧠 Why “Combine by Position” fixes the binary issue Some downstream nodes lose access to the original binary once a branch processes it. By merging the original branch (with data) and the analysis branch (with content) by position, you restore a single item with both fields—so the next step can use the image again while referencing earlier analysis. 🧪 Test Tips Upload a JPG/PNG and execute the workflow from the Form Trigger preview. Confirm Merge output contains both data (binary/base64) and content (text). In the AI Agent, log or return both fields to verify availability. 🔧 Customize Swap GPT-4o for another Vision-capable model if needed. Extend the AI Agent to extract structured fields (e.g., objects detected, text, brand cues). Add a Router after Merge to branch into storage (S3, GDrive) or notifications (Slack, Email). 📝 Requirements n8n (cloud or self-hosted) with web UI access OpenAI** credential configured (Vision support) 🩹 Troubleshooting Binary missing downstream?* Ensure *Merge* receives *both** branches and is set to combineByPosition. Wrong field name?* The *Form Trigger* upload field must be labeled *data** to match node expressions. Model errors?* Verify your *OpenAI* credential and that the chosen model supports *image analysis**. 💬 Sticky Note (included in the workflow) > “Use Binary Field after next step” — This workflow demonstrates how to preserve and reuse an uploaded file (binary/base64) after a downstream step by using a Merge node (combineByPosition). A user uploads an image via Form Trigger → the image is analyzed with OpenAI Vision → results are merged back with the original upload so the next AI Agent step can access both the original file (data) and the first analysis (content) at the same time. 📬 Contact Need help customizing this (e.g., filtering by campaign, sending reports by email, or formatting your PDF)? 📧 rbreen@ynteractive.com 🔗 https://www.linkedin.com/in/robert-breen-29429625/ 🌐 https://ynteractive.com. An n8n automation workflow template by Robert Breen.

By Robert Breen

Send VAPI voice requests into n8n with memory and OpenAI for conversational automation This template shows how to capture voice interactions from VAPI (Voice AI Platform), send them into n8n via a webhook, process them with OpenAI, and maintain context with memory. The result is a conversational AI agent that responds back to VAPI with short, business-focused answers. ✅ What this template does Listens for POST requests from VAPI containing the session ID and user query Extracts session ID and query for consistent conversation context Uses OpenAI (GPT-4.1-mini) to generate conversational replies Adds Memory Buffer Window so each VAPI session maintains history Returns results to VAPI in the correct JSON response format 👤 Who’s it for Developers and consultants building voice-driven assistants Businesses wanting to connect VAPI calls into automation workflows Anyone who needs a scalable voice → AI → automation pipeline ⚙️ How it works Webhook node catches incoming VAPI requests Set node extracts session_id and user_query from the request body OpenAI Agent generates short, conversational replies with your business context Memory node keeps conversation history across turns Respond to Webhook sends results back to VAPI in the required JSON schema 🔧 Setup instructions Step 1: Create Function Tool in VAPI In your VAPI dashboard, create a new Function Tool Name: send_to_n8n Description: Send user query and session data to n8n workflow Parameters: session_id (string, required) – Unique session identifier user_query (string, required) – The user’s question Server URL: https://your-n8n-instance.com/webhook/vapi-endpoint Step 2: Configure Webhook in n8n Add a Webhook node Set HTTP method to POST Path: /webhook/vapi-endpoint Save, activate, and copy the webhook URL Use this URL in your VAPI Function Tool configuration Step 3: Create VAPI Assistant In VAPI, create a new Assistant Add the send_to_n8n Function Tool Configure the assistant to call this tool on user requests Test by making a voice query — you should see n8n respond 📦 Requirements An OpenAI API key stored in n8n credentials A VAPI account with access to Function Tools A self-hosted or cloud n8n instance with webhook access 🎛 Customization Update the system prompt in the OpenAI Agent node to reflect your brand’s voice Swap GPT-4.1-mini for another OpenAI model if you need longer or cheaper responses Extend the workflow by connecting to CRMs, Slack, or databases 📬 Contact Need help customizing this (e.g., filtering by campaign, connecting to CRMs, or formatting reports)? 📧 rbreen@ynteractive.com 🔗 https://www.linkedin.com/in/robert-breen-29429625/ 🌐 https://ynteractive.com. An n8n automation workflow template by Robert Breen.

By Davide Boizza

This workflow provides an intelligent automation solution for processing RSS feeds using ScrapeGraph API and delivering personalized news summaries via email and Telegram. Key Benefits Time-Saving Automation ✅ Eliminates manual news monitoring by automatically processing RSS feeds ✅ Filters content to show only articles from the last 24 hours ✅ Reduces information overload by limiting to the 3 most recent relevant articles Multi-Channel Distribution ✅ Delivers summaries simultaneously via email and Telegram ✅ Ensures you stay informed across your preferred communication platforms ✅ Provides flexibility in how you consume your daily news digest AI-Powered Content Processing ✅ Uses ScrapeGraphAI to convert web articles into clean, readable markdown ✅ Employs multiple AI models (OpenAI GPT and Google Gemini) for robust content extraction ✅ Generates structured, coherent summaries that highlight key concepts and main ideas Quality Content Filtering ✅ Automatically filters out outdated content (older than 24 hours) ✅ Focuses on the most recent and relevant articles ✅ Processes only high-quality content through intelligent extraction algorithms How it Works Trigger & Data Fetching: The workflow starts manually. It reads a specified RSS feed and immediately filters the items to keep only those published within the last 24 hours, ensuring the digest is current. Content Processing: For each recent article (up to a limit of 3), the workflow performs a two-step process: Scraping: It visits the article's URL using ScrapeGraphAI to extract the main content and convert it into clean text. Information Extraction: A Language Model (Google Gemini) analyzes the scraped text to identify and extract the most relevant information, discarding superfluous content like ads or navigation menus. Digest Generation & Delivery: The extracted content from all articles is aggregated. A powerful Language Model (OpenAI) is then instructed to synthesize this information into a well-structured summary with a clear subject and body, formatted as an email. Finally, this generated digest is sent simultaneously to a specified email address via Gmail and to a Telegram channel or chat. Set up Steps Before executing the workflow, you need to configure the following steps: Install the Community Node: Install the ScrapeGraphAI node from the n8n community nodes list. This node is essential for scraping article content and is not part of the core n8n installation. Configure Credentials: Ensure the following credentials are correctly set up in your n8n instance: ScrapegraphAI account: For the web scraping functionality. OpenAi account: For the summary generation. Gmail account: To send the email. Telegram account: To send the Telegram message. Set Key Parameters: Update the workflow with your specific details: In the "RSS Read" node: Replace URL_FEED with the actual URL of the RSS feed you want to monitor. In the "Send to Telegram" node: Replace YOUR_CHAT_ID with the unique identifier of your Telegram channel or chat. Need help customizing? Contact me for consulting and support or add me on Linkedin. An n8n automation workflow template by Davide Boizza.

By Jemee

This workflow automates the extraction of SEO metadata (URL, page title, and meta description) from every page listed in your website's sitemap and exports it to Google Sheets. Ideal for SEO audits, content inventories, and tracking on-page elements. Prerequisites Before using this workflow: A publicly accessible sitemap.xml URL Google Sheets spreadsheet with columns: URL, Title, and meta description Google Sheets API access via OAuth2 Setup Instructions 1. Configure Sitemap Source In the "Get Sitemap XML" node, replace the default URL with your actual sitemap URL 2. Connect Google Sheets Open the "Append or update row in sheet" node Configure Google Sheets credentials Set Document ID and Sheet Name Verify column mappings match your spreadsheet 3. Adjust Rate Limiting (Optional) Modify Wait nodes if encountering 429 errors Increase delay between requests if needed How It Works Trigger: Manual workflow execution Sitemap Fetch: Retrieve sitemap.xml file URL Parsing: Extract all URLs from sitemap Batch Processing: Process URLs in manageable batches Data Extraction: Scrape title and meta description from each page Data Merge: Combine URL with extracted metadata Sheet Update: Append or update rows in Google Sheets using URL as a unique key Features Duplicate Prevention**: Uses appendOrUpdate with URL matching Rate Limiting**: Built-in delays between requests Flexible Processing**: Handles sitemaps of various sizes Easy Customization**: Modify code nodes for additional data extraction Use Cases SEO audits of title and description tags Content migration planning Website content inventory management Ongoing SEO monitoring and reporting. An n8n automation workflow template by Jemee.

By LeeWei

Overview of the n8n Workflow This n8n workflow automates the transformation of spreadsheet data into professional charts and graphs using AI-driven analysis. Triggered via Slack, it processes uploaded files (Excel, CSV, Google Sheets, or Drive links), interprets the data with an AI agent to determine the best visualization type (e.g., bar, line, pie, doughnut, or bubble charts), generates images via QuickChart, uploads them to Google Drive, and delivers the results back to the user in Slack with titles and shareable links. It maintains conversation context in Postgres for seamless multi-turn interactions and handles audio or text inputs for chart requests. What this workflow does: Hooks up to Slack for seamless spreadsheet uploads Automatically extracts your data and generates bar charts, line graphs, bubble charts, and more Delivers stunning visualizations straight back to you in Slack Makes it easy to spot trends, patterns, and insights—on demand How it Works • Users upload spreadsheets or share links via Slack, along with a natural language request (e.g., "Create a bar chart of sales by month"). • The workflow detects file types, extracts and aggregates data, then uses an AI agent to parse the request and select an appropriate chart type. • Data is formatted and sent to QuickChart's API to generate the visualization image. • Images are uploaded to Google Drive, and a confirmation message with titles and links is sent back to Slack. Set Up Steps Setup takes about 15-30 minutes, mainly for credential configuration. Detailed node instructions are in the workflow's sticky notes—focus on pasting API keys and testing triggers. Once cloned, the workflow runs plug-and-play; only tweak credentials and optional prompts as needed. ⚙️ Turn Spreadsheets Into Charts & Graphics Automate turning uploaded spreadsheets into AI-generated charts (bar, line, pie, etc.) via Slack, with results shared as Google Drive links. 🧑‍💻 Author: LeeWei 🚀 Steps to Connect: Slack Bot Setup Create a Slack app at api.slack.com/apps and add scopes for chat:write, files:read, channels:read. Generate a Bot User OAuth Token and paste it into the Slack Trigger node's credentials in n8n. Invite the bot to your desired channel for file uploads and messages. OpenAI API Key Sign up at platform.openai.com and generate an API key. Paste this key into the OpenAI (gpt-4o-mini) node's credentials. 💡 For cost efficiency, monitor usage—basic charts use minimal tokens. Postgres Database Connection Set up a Postgres instance (e.g., via Supabase or your host) with a table named n8n_rodger_chat for chat history. Add connection details (host, database, user, password) to the Postgres nodes' credentials. This enables thread memory; skip if not using multi-turn chats (but recommended for context). Google Sheets & Drive Setup Create OAuth2 credentials at console.cloud.google.com with scopes for Sheets (read) and Drive (upload, share). Paste the credentials into the Google Sheets and implied Drive upload nodes. Test by sharing a sample sheet—ensures data extraction and image storage work. QuickChart Integration No API key needed for free tier (up to 500 charts/month); visit quickchart.io to confirm. For production (100k+ charts/month), upgrade to corporate plan ($40/month) and add any auth if required in the HTTP Request node. The node is pre-configured for chart generation—edit URL params only for custom styling. Plug and Play Instructions Clone the workflow JSON directly into n8n—all nodes (triggers, AI agents, extractors, switches) are pre-wired and ready. No re-setup needed beyond the steps above. Key editable fields (found in sticky notes): AI Agent Node: System Prompt** Customize the chart interpretation (default: auto-selects bar/line/pie/etc. based on data). Example: Change to prioritize "scatter plots for correlations" if needed. Switch Nodes (File Detection)** Add rules for new formats (e.g., .ods for OpenDocument) in the conditions for XLS/XLSX/CSV/Sheets/Drive. HTTP Request Node (QuickChart)** Tweak chart params like width=800&height=600 for size, or colors via ?chart=... for branding. Let User Know Upload Complete: Text** Adjust the confirmation message template for tone (e.g., add emojis or custom phrasing). Test with a sample Slack message: "Make a line graph from this sales CSV over months." Results appear instantly with links. Potential Customizations Add Chart Types**: Duplicate a chart branch (e.g., Line Graph) and integrate new QuickChart endpoints for scatter or funnel charts. Switch AI Provider**: Replace OpenAI with OpenRouter in the Chat Model node for alternative LLMs. Batch Size**: Edit the Loop Over Items node's batch for larger datasets (default handles small files efficiently). Error Handling**: Add IF nodes post-extraction to notify on invalid data. Considerations and Improvements Rate Limits**: QuickChart free tier suits testing; scale to paid for heavy use. OpenAI tokens add up for complex data. File Limits**: Supports up to ~10MB uploads; for larger, preprocess externally. Privacy**: Data passes through OpenAI—review for sensitive info. Enhancements**: Integrate image OCR for scanned tables, or export to PDF for reports. This workflow streamlines data viz without coding, perfect for teams analyzing trends on the fly. Questions? Drop a Slack message in your bot channel!. An n8n automation workflow template by LeeWei.

By Guillaume Duvernay

Quick overview Describe a playlist idea and track count in a web form, and an AI agent researches matching songs on the live web via Linkup, curates a tracklist and title, builds the playlist in your Spotify account, then redirects you straight to it. How it works The workflow starts with the On form submission trigger, a web form asking for a "Playlist request" (free text describing style, mood, artists) and a "Number of tracks" to include. The Ideate playlist AI Agent node receives the form data and acts as a DJ: it plans a search query based on the request and track count. The agent calls its connected tool, Web query to find tracks, an HTTP Request node that sends a POST request to the Linkup API (api.linkup.so/v1/search) with a structured output schema, returning candidate tracks with title, artist, and a short explanation for each. Using the OpenAI Chat Model (gpt-4.1-mini) and the Structured Output Parser node, the agent selects the final tracks and creates a playlist name, returning a strict JSON object with "playlistName" and a "tracks" array. The Create playlist node (Spotify node) creates a new public playlist in your Spotify account using the generated name. The Get tracks array and Split out tracks nodes turn the agent's track list into individual items, one per track. For each track, the Search the track node (Spotify node, search operation) looks up the track by "artist - title" and the Get track IDs node extracts its Spotify ID. The Add track to playlist node adds each track to the newly created playlist one by one, then Get the final playlist retrieves the completed playlist. The Opening the playlist node (form completion) redirects the user's browser directly to the playlist's Spotify URL, so it's ready to play immediately. Setup Add your Spotify credentials to the three Spotify nodes: Create playlist, Search the track, Add track to playlist, and Get the final playlist. These require an authenticated Spotify account (via OAuth2) with permission to create and edit playlists. Add your Linkup API credentials to the Web query to find tracks node (HTTP Request Tool). This node uses generic HTTP Bearer Auth authentication, so create a Bearer Auth credential with YOUR_LINKUP_API_KEY. Linkup's free plan covers this use case. Add your OpenAI credentials to the OpenAI Chat Model node, which powers the Ideate playlist AI Agent (model: gpt-4.1-mini). Any OpenAI account with API access and available credit works. No changes are required to the Structured Output Parser node; it already defines the expected JSON schema (playlistName and tracks array with artist/title/explanation) and should be left as-is. Activate the workflow by toggling it to "Active" so the form trigger becomes reachable. Open the form URL exposed by the On form submission trigger (path: spotify-playlist-generator), describe your desired playlist and the number of tracks, and submit to generate and open the playlist. Requirements A Spotify account with permission to create and edit playlists, connected via OAuth2 credentials in n8n. A Linkup account and API key (linkup.so) for the live web-search tool; the free plan is sufficient. An OpenAI account with API access for the gpt-4.1-mini chat model used by the AI agent. Customization Replace the On form submission trigger with another entry point, such as a Telegram message, a Discord bot command, or a generic webhook, to launch playlist generation from a different channel. Add a step to collect and merge multiple people's song ideas before the Ideate playlist agent runs, to build collaborative group playlists. In the Web query to find tracks node, change the "depth" body parameter from "deep" to "standard" for faster, cheaper (but less thorough) track research. Additional info The Web query to find tracks node runs in "deep" search mode by default for higher-quality results; switch it to "standard" mode to trade some research depth for speed and lower cost. The workflow relies on Linkup's structured output feature to get consistently formatted track suggestions, so the "structuredOutputSchema" body parameter in that node should not be altered. An n8n automation workflow template by Guillaume Duvernay.

By Dmytro

This automation template allows you to automatically receive news from RSS feeds, process their content, and publish or schedule posts on various social media platforms using PostPulse. ⚠️Disclaimer:* This workflow uses the community node @postpulse/n8n-nodes-postpulse. Make sure community nodes are enabled in your n8n instance before importing and using this template.* 👉 To install it: Go to Settings → Community Nodes → Install and enter:"@postpulse/n8n-nodes-postpulse". 💡 For more details, see n8n Integration Guide: PostPulse Developers – n8n Integration. Who Is This For? Marketers** who want to automatically fill their content plan with relevant news. Content creators and editors** who want to effectively distribute news across different platforms without unnecessary effort. Media agencies** that want to maintain a constant presence on social media by republishing content from reliable sources. What Problem Does This Workflow Solve? Instead of manually searching, copying, and publishing news, you get: Automated news collection:** The workflow automatically reads the RSS feed and finds new content. Intelligent processing:** It automatically extracts the text and, when possible, images from news articles, adapting the content for different social media platforms. Seamless publishing:** PostPulse publishes posts simultaneously on TikTok, Instagram, YouTube, LinkedIn, Telegram, Bluesky, X, and Threads. Flexibility and customization:** RSS feeds from different websites have unique structures. This workflow is designed as a flexible template that can automatically publish news (even without images) and allows easy adaptation to any news source. Time saving:** Automates routine processes, freeing up your time for more important tasks. How It Works This workflow runs on a schedule, reads news, and processes it before sending it to PostPulse. Scheduled execution:** The workflow is triggered at a set time, for example, daily at 9:00 AM. RSS feed reading:** The RSS Feed Read node connects to the specified RSS feed (default: https://rss.unian.ua/site/gplay_56_ukr.rss) and retrieves the latest news. Filtering and media check:** The If and Media Check IF nodes verify whether the news was published yesterday and whether it contains an image, looking for it in several possible fields (enclosure, media:content, or even tags in the HTML). Media upload:** If an image is found, the PostPulse Upload Media node uploads it to PostPulse. Then the Get Upload Status node checks if the media is ready for publishing. Post creation:** The content (with or without media) is sent to the Publish Post nodes, which create a draft post in PostPulse, adapting the text to each platform’s limits (e.g., 280 characters for X/Twitter). Publishing:** PostPulse automatically publishes or schedules the posts across all connected platforms. Setup 1. Connect PostPulse to n8n Request your OAuth client key and secret from PostPulse support at support@post-pulse.com. Add your PostPulse account in the Credentials section in n8n. 2. Find an RSS Feed that you need The easiest way is to check the page’s source code. Open the news website you are interested in. Go to the page with a specific news category (e.g., "Sports"). Press Ctrl + U (or Cmd + Option + U on Mac) to open the page’s source code. Press Ctrl + F (or Cmd + F on Mac) to search the text. Type "rss" and press Enter. Usually, you will find a link pointing to an XML page, which is the RSS feed. 3. Configure the RSS Feed Read node Open the RSS Feed Read node. Paste the URL of your RSS feed into the URL field. 4. Configure the Limit to N Post node This node limits the number of posts generated in a single run. By default, const limit = 1;. You can change the value from 1 to any number of posts you want to publish at once. Requirements Connected PostPulse accounts** (TikTok, Instagram, YouTube, LinkedIn, Telegram, Bluesky, X, Threads). OAuth client key and secret** obtained from PostPulse. An n8n instance** with community nodes enabled. ✨ With this workflow, PostPulse and n8n become your all-in-one automation hub for publishing news. How To Customize The Workflow This workflow is designed to be fully flexible and adaptable to your specific needs. While it works out-of-the-box with the default RSS feed, you can easily optimize it for any news source: Adapt to different RSS feeds:** Each website’s RSS feed can have a unique structure. You can adjust the workflow to extract text, images, or additional fields as needed. Handle missing media:** Some feeds may not include images in standard fields. The workflow is built to publish posts even without images, but you can customize it to extract images from other tags or HTML elements. Extend content extraction:** If a feed stores the full text in a separate link, you can add nodes or logic to pull more content for richer posts. Text trimming and platform-specific formatting:** You can modify the trimming logic in the Publish Post nodes to fit platform limits or adjust content formatting as desired. Flexible scheduling and limits:** Easily change the number of posts per run, the schedule, or date filters to match your workflow and publishing strategy. 💡 Tip: The workflow is meant to be a template — fully functional out-of-the-box, but easily customizable to match any RSS feed or content source. Its main strength is flexibility, allowing you to adapt it to different feeds, extract more content, and adjust publishing rules without touching the core workflow. An n8n automation workflow template by Dmytro.