Workflow Templates

How it works This workflow automatically processes bank statements from various formats and extracts structured transaction data with intelligent categorization using AI. Key Steps File Upload - Accepts bank statements via webhook upload (PDF, Excel, CSV formats). Smart Format Detection - Automatically routes files to appropriate processors (PDF text extraction or spreadsheet parsing). AI-Powered Extraction - Uses GPT-4 to extract account details, transactions, and balances from statement data. Data Processing & Categorization - Cleans, validates, and automatically categorizes transactions into expense categories. Database Storage - Saves processed data to PostgreSQL database for analysis and reporting. API Response - Returns structured summary with transaction counts, expense totals, and category breakdowns. Set up steps Setup time: 8-12 minutes Configure OpenAI credentials - Add your OpenAI API key for AI-powered data extraction. Set up PostgreSQL database - Connect your PostgreSQL database and create the required table structure. Configure webhook endpoint - The workflow provides a /upload-statement endpoint for file uploads. Customize transaction categories - Modify the AI prompt to include your preferred expense categories. Test the workflow - Upload a sample bank statement to verify the extraction and categorization process. Set up database table - Ensure your PostgreSQL database has a bank_statements table with appropriate columns. Features Multi-format support**: PDF, Excel, CSV bank statements AI-powered extraction**: GPT-4 extracts account details and transactions Automatic categorization**: Expenses categorized as groceries, dining, gas, shopping, utilities, healthcare, entertainment, income, fees, or other Data validation**: Cleans and validates transaction data with error handling Database storage**: PostgreSQL integration for data persistence API responses**: Clean JSON responses with transaction summaries and category breakdowns Smart routing**: Automatic format detection and appropriate processing paths

This n8n template from Intuz delivers a complete and automated solution to streamline your development workflow for a single repository. By embedding specific keywords and a JIRA issue ID within your git commit commands, this workflow automatically creates a Pull Request in GitHub and simultaneously updates the corresponding JIRA ticket. This provides a complete, seamless integration that eliminates manual steps and keeps your project management perfectly in sync with your codebase. How it works This workflow acts as a powerful bridge between your Git repository and your project management tools, driven entirely by the structure of your commit messages. GitHub Webhook Trigger: The workflow starts when a developer pushes a new commit to a specified repository in GitHub. Parse Commit Message: A Code node extracts key information from the commit message: The JIRA Issue Key (e.g., FF-1196). The base branch for the PR (e.g., development). Action commands like [auto-pr] and [taskcompleted]. Conditional PR Creation: An IF node checks if the [auto-pr] command is present. If yes, it uses the GitHub node to automatically create a pull request from the developer's branch to the specified base branch. If no, this step is skipped, allowing for multiple commits before a PR is made. Conditional JIRA Update: Another IF node checks for the [taskcompleted] command. If yes, it uses the JIRA node to transition the corresponding issue to your "Done" status (e.g., "Task Completed" or "In Review"). If no, the JIRA issue remains in its current state, perfect for work-in-progress commits. How to Use: Quick Start Guide Click the "Use Template" button to import this workflow into your n8n instance. Configure the GitHub Trigger: Open the "GitHub Push Trigger" node. It will display a unique Webhook URL. Copy this URL. In your GitHub repository, go to Settings > Webhooks > Add webhook. Paste the URL into the Payload URL field. Set the Content type to application/json. Under "Which events would you like to trigger this webhook?", select Just the push event. Click Add webhook. Connect Your Accounts: GitHub: Select your GitHub API credential in the "Create Pull Request" node. JIRA : Select your JIRA API credential in the "Update JIRA Issue Status" node. Customize the JIRA Transition (Important): Open the "Update JIRA Issue Status" node. In the Transition parameter, you need to set the specific status you want to move the issue to (e.g., 'Done', 'Completed', 'In Review'). You can use the ID or the exact name of the transition from your JIRA project's workflow. Activate the Workflow: Save your changes and activate the workflow. You're ready to automate! Example Commit Message: git commit -m "FF-1196 Implement OAuth login [auto-pr,development,taskcompleted]" Key Requirements to Use Template An active n8n instance. A GitHub account with repository admin permissions to create webhooks. A JIRA Cloud account with permissions to update issues. Developers who can follow the specified git commit message format. Connect with us Website: https://www.intuz.com/services Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz For Custom Worflow Automation Click here- Get Started

Overview Transform your contract management process with this enterprise-grade workflow that handles the complete contract lifecycle - from initial intake through execution, monitoring, and renewal. This comprehensive solution combines AI-powered contract analysis with automated risk scoring, clause comparison, obligation tracking, and proactive alerts. It integrates with multiple data sources including email, SharePoint, contract CLM systems, and creates a centralized contract intelligence hub that prevents revenue leakage, ensures compliance, and accelerates deal velocity. What You Can Do This advanced workflow orchestrates a complete contract management ecosystem that monitors multiple channels (email, Google Drive, SharePoint, APIs) for new contracts and amendments. It extracts and analyzes over 50 contract data points using AI, performs multi-dimensional risk assessment across legal, financial, and operational factors, compares clauses against your approved template library, tracks all obligations and key dates with automated reminders, integrates with Salesforce/CRM for deal alignment, routes contracts through dynamic approval workflows based on risk scores, generates executive dashboards with contract analytics, and maintains a searchable repository with version control. The system handles complex scenarios including multi-party agreements, framework contracts with statements of work, international contracts requiring jurisdiction analysis, and M&A due diligence requiring bulk contract review. Who It's For Designed for enterprise legal operations teams managing thousands of contracts annually, procurement departments negotiating complex vendor agreements, contract managers overseeing multi-million dollar portfolios, compliance teams ensuring regulatory adherence across jurisdictions, sales operations needing faster contract turnaround, and C-suite executives requiring contract intelligence for strategic decisions. Essential for organizations in regulated industries (healthcare, finance, government) and companies undergoing digital transformation of their legal operations. The Problem It Solves Manual contract management creates massive operational risks and inefficiencies. Organizations typically have contracts scattered across emails, shared drives, and filing cabinets with no central visibility. This leads to missed renewal deadlines costing 5-10% of contract value, unauthorized contract variations creating compliance risks, obligation failures resulting in penalties and damaged relationships, and inability to leverage favorable terms across similar contracts. Studies show that inefficient contract management costs organizations up to 9% of annual revenue. This workflow creates a single source of truth for all contracts, automates tracking and compliance, and provides predictive insights to prevent issues before they occur. Setup Instructions Multi-Channel Integration: Configure connectors for email (Office 365/Gmail), Google Drive, SharePoint, and contract management systems PDF Vector Setup: Install PDF Vector node and configure API with enterprise rate limits Database Configuration: Set up PostgreSQL/MySQL for contract repository with proper indexing Template Library: Upload your standard contract templates and approved clause library Risk Framework: Configure risk scoring matrix for your industry (legal, financial, operational risks) Approval Matrix: Define approval routing based on contract value, type, and risk score CRM Integration: Connect to Salesforce/HubSpot for opportunity and account alignment Notification Setup: Configure Slack/Teams channels and email distribution lists Dashboard Creation: Set up Tableau/PowerBI connectors for executive reporting Security Configuration: Enable encryption, audit logging, and role-based access controls Key Features Intelligent Intake System**: Monitor email attachments, shared folders, CRM uploads, and API submissions Advanced AI Extraction**: Extract 50+ data points including nested obligations and conditional terms Multi-Dimensional Risk Scoring**: Analyze legal, financial, operational, and reputational risks Clause Library Comparison**: Compare against approved templates and flag deviations Obligation Management**: Track deliverables, milestones, and SLAs with automated alerts Dynamic Approval Routing**: Route based on AI risk score, contract value, and deviation analysis Version Control & Redlining**: Track all changes and maintain complete audit trail Salesforce Integration**: Sync contract data with opportunities and accounts Predictive Analytics**: Forecast renewal likelihood and negotiation outcomes Bulk Processing**: Handle M&A due diligence with parallel processing of hundreds of contracts Multi-Language Support**: Process contracts in 15+ languages with automatic translation Executive Dashboards**: Real-time visibility into contract portfolio and risk exposure Customization Options Implement industry-specific modules for healthcare (BAAs, DPAs), financial services (ISDAs, loan agreements), technology (SaaS, licensing), or government contracting. Add AI models trained on your historical contracts for better extraction accuracy. Create custom risk factors for emerging regulations like AI governance or ESG compliance. Build integration with specific CLM systems (Ironclad, Docusign CLM, Icertis). Implement advanced analytics including contract similarity scoring, win-rate analysis by clause variations, and automatic playbook generation. Add blockchain integration for smart contract execution and configure automated contract assembly for standard agreements. Note: This workflow uses the PDF Vector community node. Make sure to install it from the n8n community nodes collection before using this template.

🤖AI-Powered Appointment Scheduling with Google Calendar & Sheets Virtual Receptionist Automate customer conversations with an AI-powered virtual receptionist. This workflow can chat naturally with clients, answer general business questions (like services, location, and hours), check availability in Google Calendar, book appointments, and save customer details in Google Sheets. Fully customizable for any business type — salons, clinics, agencies, consultants, and more. 📖 How It Works Welcome the customer when the customer says hi AI greets warmly: “Hello! I’m [AI name] from [Business name].” Answer general questions Provides instant replies about services, pricing, business location, hours, and availability. Understand their need Identifies the service requested and preferred time. Check availability Queries Google Calendar for open slots. Gather customer details Collects name, phone, and email (optional). Confirm booking Creates the appointment in Google Calendar. Save records Logs booking and customer info into Google Sheets. ⚙️ Setup Steps (Quick) Connect your Google Calendar and Google Sheets accounts. Add your business details (name, type, services, hours, policies) to the Business Info Sheet. Configure your OpenAI API key (or use n8n free credits). Optional: Connect Twilio WhatsApp for direct chat responses. 🏢 Example Business Info (Google Sheet) | business_id | business_name | business_type | location | phone | email | services | calendar_id | timezone | currency | working_hours | ai_name | ai_personality | ai_role | emergency_available | booking_advance_days | cancellation_hours | |-------------|-----------------|---------------------|----------------------------------|-----------------|---------------------------|----------|-----------------------|----------|----------|--------------------------------|---------|-----------------------------------|------------------------------------------------------------------------------------------------|----------------------|----------------------|-------------------| |001| Luxe Hair Studio | Hair & Beauty Salon | 123 Main Street, New York, NY 10001 | 1 (XXX) XXX-XXXX | yourbusiness@email.com | “Haircut & Styling (60 minutes, $3500…)Hair Coloring (120 minutes, $8000…)…” | calendar-id-here | GMT -3 | USD | Mon–Sat: 9:00 AM – 7:00 PM, Sun: Closed | bella | Friendly, Stylish, Professional | Manages bookings, answers FAQs, recommends services, gives beauty tips, sends reminders, etc. | no | 10 | 24 | ✅ Purpose: Supplies context (services, pricing, hours, AI personality, booking policies). 💡 The AI uses this sheet to answer general business questions (e.g., “Where are you located?”, “Do you do hair colouring?”, “What are your working hours?”). 📊 Appointments Sheet Example | client_number | client_name | event_id | summary | services | |----------------|-------------|-----------|----------------------------------|----------| | 001 | Sarah Lee | evt-10293 | Appointment with Sarah Lee – Haircut & Styling | Haircut & Styling | | 002 | John Smith | evt-10294 | Appointment with John Smith – Highlights | Highlights | ✅ Purpose: Logs confirmed bookings with service details and links back to Google Calendar. 💡 Features ✅ AI receptionist with conversation memory ✅ Answers FAQs – location, services, hours, pricing ✅ Google Calendar integration for real-time availability ✅ Google Sheets integration for customer records & reporting ✅ Customizable AI name, role, and personality 🔑 Who It’s For Salons & Spas** – Manage bookings and FAQs Clinics & Health Services** – Automated scheduling + patient info Agencies & Consultants** – Answer inquiries + schedule meetings Any Service Business** – Save time, improve customer experience

Overview This workflow automates the entire process of creating professional subtitle (.SRT) and synced lyrics (.LRC) files from audio recordings. Upload your vocal track, let Whisper AI transcribe it with precise timestamps, and GPT-5-nano segments it into natural, singable lyric lines. With an optional quality control step, you can manually refine the output while maintaining perfect timestamp alignment. Key Features Whisper AI Transcription**: Word-level timestamps with multi-language support via ISO codes Intelligent Segmentation**: GPT-5-nano formats transcriptions into natural lyric lines (2-8 words per line) Quality Control Option**: Download, edit, and re-upload corrections with smart timestamp matching Advanced Alignment**: Levenshtein distance algorithm preserves timestamps during manual edits Dual Format Export**: Generate both .SRT (video subtitles) and .LRC (synced lyrics) files No Storage Needed**: Files generated in-memory for instant download Multi-Language**: Supports various languages through Whisper API Use Cases Generate synced lyrics for music video releases on YouTube Create .LRC files for Musixmatch, Apple Music, and Spotify Prepare professional subtitles for social media content Batch process subtitle files for catalog releases Maintain consistent lyric formatting across artists Streamline content delivery for streaming platforms Speed up video editing workflow Perfect For For Musicians & Artists For Record Labels For Content Creators What You'll Need Required Setup OpenAI API Key** for Whisper transcription and GPT-5-nano segmentation Recommended Input Format**: MP3 audio files (max 25MB) Content**: Clean vocal tracks work best (isolated vocals recommended, but whole tracks works still good) Languages**: Any language supported by Whisper (specify via ISO code) How It Works Automatic Mode (No Quality Check) Upload your MP3 vocal track to the workflow Transcription: Whisper AI processes audio with word-level timestamps Segmentation: GPT-5-nano formats text into natural lyric lines Generation: Workflow creates .SRT and .LRC files Download your ready-to-use subtitle files Manual Quality Control Mode Upload your MP3 vocal track and enable quality check Transcription: Whisper AI processes audio with timestamps Initial Segmentation: GPT-5-nano creates first draft Download the .TXT file for review Edit lyrics in any text editor (keep line structure intact) Re-upload corrected .TXT file Smart Matching: Advanced diff algorithm aligns changes with original timestamps Download final .SRT and .LRC files with perfect timing Technical Details Transcription API**: OpenAI Whisper (/v1/audio/transcriptions) Segmentation Model**: GPT-5-nano with custom lyric-focused prompt System Prompt*: *"You are helping with preparing song lyrics for musicians. Take the following transcription and split it into lyric-like lines. Keep lines short (2–8 words), natural for singing/rap phrasing, and do not change the wording." Timestamp Matching**: Levenshtein distance + alignment algorithm File Size Limit**: 25MB (n8n platform default) Processing**: All in-memory, no disk storage Cost**: Based on Whisper API usage (varies with audio length) Output Formats .SRT (SubRip Subtitle) Standard format for: YouTube video subtitles Video editing software (Premiere, DaVinci Resolve, etc.) Media players (VLC, etc.) .LRC (Lyric File) Synced lyrics format for: Musixmatch Apple Music Spotify Music streaming services Audio players with lyrics display Pro Tips 💡 For Best Results: Use isolated vocal tracks when possible (remove instrumentals) Ensure clear recordings with minimal background noise For quality check edits, only modify text content—don't change line breaks Test with shorter tracks first to optimize your workflow ⚙️ Customization Options: Adjust GPT segmentation style by modifying the system prompt Add language detection or force specific languages in Whisper settings Customize output file naming conventions in final nodes Extend workflow with additional format exports if needed Workflow Components Audio Input: Upload interface for MP3 files Whisper Transcribe: OpenAI API call with timestamp extraction Post-Processing: GPT-5-nano segmentation into lyric format Routing Quality Check: Decision point for manual review Timestamp Matching: Diff and alignment for corrected text Subtitles Preparation: JSON formatting for both output types File Generation: Convert to .SRT and .LRC formats Download Nodes: Export final files Template Author: Questions or need help with setup? 📧 Email:xciklv@gmail.com 💼 LinkedIn:https://www.linkedin.com/in/vaclavcikl/

Who’s it for This template is designed for creators, researchers, freelance writers, founders, and automation professionals who want a reliable way to generate structured, citation-backed research content without doing manual data collection. Anyone creating blog posts, reports, briefs, or research summaries will benefit from this system. What it does This workflow turns a simple form submission into a complete research pipeline. It accepts a topic, determines what needs to be researched, gathers information from the web, writes content, fact-checks it against the collected sources, edits the draft for clarity, and compiles a final report. It behaves like a small agentic research team inside n8n. How it works A form collects the research topic, depth, and desired output format. A research agent generates focused search queries. SERP API retrieves real-time results for each query. The workflow aggregates and structures all findings. A writing agent creates the first draft based on the data. A fact-checking agent verifies statements against the sources. An editor agent improves tone, flow, and structure. A final review agent produces the completed research document with citations. This workflow includes annotated sticky notes to explain each step and guide configuration. Requirements Groq API key for running the Llama 3.3 model. SERP API key for performing web searches. An n8n instance (cloud or self-hosted). No additional dependencies are required. How to set up Add your Groq and SERP API credentials using n8n’s credential manager. Update the form fields if you want custom depth or output formats. Follow the sticky notes for detailed configuration. Run the workflow and submit a topic through the form to generate your first research report. How to customize Replace the writer agent with a different model if you prefer a specific writing style. Adjust the number of search queries or SERP results for deeper research. Add additional steps such as PDF generation, sending outputs to Notion, or publishing to WordPress. Modify the form to suit industry-specific content needs.

Community Node Disclaimer: This workflow uses KlickTipp community nodes. How It Works This workflow connects an MCP Server with the KlickTipp contact management platform and integrates it with an LLM (e.g. Claude etc.) to enable intelligent querying and segmentation of contact data. It covers all major KlickTipp API endpoints, providing a comprehensive toolkit for automated contact handling and campaign targeting. Key Features MCP Server Trigger: Initiates the workflow via the MCP server, listening for incoming requests related to contact queries or segmentation actions. LLM Interaction Setup: Interacts with an OpenAI or Claude model to handle natural language queries such as contact lookups, tagging, and segmentation tasks. KlickTipp Integration: Complete set of KlickTipp API endpoints included: Contact Management: Add, update, get, list, delete, and unsubscribe contacts. Contact Tagging: Tag, untag, list tagged contacts. Tag Operations: Create, get, update, delete, list tags. Opt-In Processes: List and retrieve opt-in process details. Data Fields: List and get custom data fields. Redirects: Retrieve redirect URLs. Use Cases Supported: Query contact information via email or name. Identify and segment contacts by city, region, or behavior. Create or update contacts from the provided data. Dynamically apply or remove tags to initiate campaigns. Automate targeted outreach based on contact attributes. Setup Instructions Install and Configure Nodes: Set up MCP Server. Configure the LLM connection (e.g., Claude Desktop configuration). Add and authenticate all KlickTipp nodes using valid API credentials. Define Tagging and Field Mapping: Identify which fields and tags are relevant to your use cases. Ensure necessary tags and custom fields are already created in KlickTipp. Workflow Logic: Trigger via MCP Server: A prompt or webhook call activates the server listener. Query Handling via LLM Agent: AI interprets the natural language input and determines the action. Contact Search & Segmentation: Searches contacts using identifiers (email, address) or criteria. Data Operations: Retrieves, updates, or manages contact and tag data based on interpreted command. Campaign Preparation: Applies tags or sends campaign triggers depending on query results. Benefits: AI-Powered Automation:** Reduces manual contact search and tagging efforts through intelligent processing. Scalable Integration:** Built-in support for full range of KlickTipp operations allows diverse use-case handling. Data Consistency:** Ensures structured data flows between MCP, AI, and KlickTipp, minimizing errors. Testing and Deployment: Use defined prompts such as: “Tell me something about the contact with email address X” “Tag all contacts from region Y” “Send campaign Z to customers in area A” Validate expected actions in KlickTipp after prompt execution. Notes: Customization:** Adjust tag logic, AI prompts, and contact field mappings based on project needs. Extensibility:** The template can be expanded with further logic for Google Sheets input or campaign feedback loops Resources: Use KlickTipp Community Node in n8n Automate Workflows: KlickTipp Integration in n8n

🛠️ Workflow: Jotform → HubSpot Company + Task Automation Automatically create or update HubSpot companies and generate follow-up tasks whenever a Jotform is submitted. All logs are stored to Google Sheets for traceability, transparency, and debugging. ✅ Use Cases Capture marketing queries from your website’s Jotform form and immediately create tasks for your sales or SDR team. Enrich HubSpot companies with submitted domains, company names, and contact data. Automatically assign tasks to owners and keep all form submissions logged and auditable. Avoid manual handoffs — full automation from form submission → CRM. 🔍 How It Works (Step-by-Step) 1. Jotform Trigger The workflow starts when a new submission is received via the Jotform webhook. Captured fields include: name, email, LinkedIn profile, company name, marketing budget, domain, and any specific query. 2. Create or Update Company in HubSpot + Format Data The “Create Company” node ensures the submitted company is either created in HubSpot or updated if it already exists. A Formatter (Function) node standardizes the data — names, email, LinkedIn URL, domain, marketing budget, and query text. It composes a task title, generates a follow-up timestamp, and dynamically assigns an owner. 3. Loop & HTTP Request – Create HubSpot Task The workflow loops through each formatted item. A Wait node prevents rate limit issues. It then sends an HTTP POST request to HubSpot’s Tasks API, creating a task with: Subject and body including the submission details Task status, priority, and type Assigned owner and associated company 4. Loop & HTTP Request – Set Company Domain After tasks are created, another loop updates each HubSpot company record with the submitted domain. This ensures all HubSpot companies have proper website data for future enrichment. 5. Storing Logs (Google Sheets) All processed submissions, responses, errors, and metadata are appended or updated in a Google Sheets document. This provides a complete audit trail — ideal for debugging, reporting, and performance monitoring. 🧩 Node Structure Overview | Step | Node | Description | |------|------|--------------| | 1️⃣ | Jotform Trigger | Receives form submission data | | 2️⃣ | HubSpot Create Company | Ensures company record exists | | 3️⃣ | Formatter / Function Node | Cleans & structures data, assigns owner, generates task fields | | 4️⃣ | Wait / Delay Node | Controls API call frequency | | 5️⃣ | HTTP Request (Create Task) | Pushes task to HubSpot | | 6️⃣ | HTTP Request (Update Domain) | Updates company domain in HubSpot | | 7️⃣ | Google Sheets Node | Logs inputs, outputs, and status | 📋 Requirements & Setup 🔑 HubSpot Private App Token with permissions to create companies, tasks, and update records 🌐 Jotform Webhook URL pointing to this workflow 📗 Google Sheets Credentials (OAuth or service account) with write access ✅ HubSpot app must have crm.objects.companies.write and crm.objects.tasks.write scopes ⚠️ Add retry or error-handling branches for failed API calls ⚙️ Customization Tips & Variations Add contact association:** Modify the payload to also link the task with a HubSpot Contact (via email) so it appears in both company and contact timelines. Use fallback values:** In the Formatter node, provide defaults like “Unknown Company” or “No query provided.” Dynamic owner assignment:** Replace hash-based assignment with round-robin or territory logic. Conditional task creation:** Add logic to only create tasks when certain conditions are met (e.g., budget > 0). Error branches:** Capture failed HTTP responses and send Slack/Email alerts. Extended logs:** Add response codes, errors, and retry counts to your Google Sheet for more transparency. 🎯 Benefits & Why You’d Use This ⚡ Speed & Automation — eliminate manual data entry into HubSpot 📊 Data Consistency — submissions are clean, enriched, and traceable 👀 Transparency — every action logged for full visibility 🌍 Scalability — handle hundreds of submissions effortlessly 🔄 Flexibility — adaptable for other use cases (support tickets, surveys, partnerships, etc.) ✨ Example Use Case A marketing form on your website captures partnership or franchise inquiries. This workflow instantly creates a HubSpot company, logs the inquiry as a task, assigns it to a regional manager, and saves a record in Google Sheets — all within seconds. Tags: HubSpot Jotform CRM GoogleSheets Automation LeadManagement

Generate social posts from GitHub pushes to Twitter and LinkedIn On each GitHub push, this workflow checks if the commit set includes README.md and CHANGELOG.md, fetches both files, lets an LLM generate a Twitter and LinkedIn post, then publishes to Twitter and LinkedIn (Person). Apps & Nodes Trigger:** Webhook Logic:** IF, Merge, Aggregate GitHub:** Get Repository File (×2) Files:** Extract from File (text) (×2) AI:** OpenAI Chat Model → LLM Chain (+ Structured Output Parser) Publish:** Twitter, LinkedIn (Person) Prerequisites GitHub:** OAuth2 or PAT with repo read. OpenAI:** API key. Twitter:* OAuth2 app with *Read and Write; scopes tweet.read tweet.write users.read offline.access. LinkedIn (Person):* OAuth2 credentials; *required scope:** w_member_social, openid. Setup GitHub Webhook: Repo → Settings → Webhooks Payload URL: https://<your-n8n-domain>/webhook/github/push Content type: application/json • Event: Push • Secret (optional) • Branches as needed. Credentials: Connect GitHub, OpenAI, Twitter, and LinkedIn (Person). How it Works Webhook receives GitHub push payload. IF checks that README and CHANGELOG appear in added/modified. GitHub (Get Repository File) pulls README.md and CHANGELOG.md. Extract from File (text) converts both binaries to text. Merge & Aggregate combines into one item with both contents. LLM (OpenAI + Parser) returns a JSON with twitter and linkedin. Twitter posts the tweet. LinkedIn (Person) posts the LinkedIn text.

This automated TLDW (Too Long; Didn't Watch) generator using Decodo's scraping API to extract complete video transcripts and metadata, then uses Google Gemini 3 to create intelligent summaries with key points, chapters breakdown, tools mentioned, and actionable takeaways—eliminating hours of manual note-taking and video watching. Why Use This Workflow? Time Savings: Convert a 2-hour video into a readable 5-minute summary, reducing research time by 95% Comprehensive Coverage: Captures key points, chapters, tools, quotes, and actionable steps that manual notes often miss Instant Accessibility: Receive structured summaries directly in Telegram within 30-60 seconds of sharing a link Multi-Language Support: Process transcripts in multiple languages supported by YouTube's auto-caption system Ideal For Content Creators & Researchers:** Quickly extract insights from competitor videos, educational content, or industry talks without watching hours of footage Students & Educators:** Generate study notes from lecture recordings, online courses, or tutorial videos with chapter-based breakdowns Marketing Teams:** Analyze competitor content strategies, extract tools and techniques mentioned, and identify trending topics across multiple videos Busy Professionals:** Stay updated with conference talks, webinars, or industry updates by reading summaries instead of watching full recordings How It Works Trigger: User sends any YouTube URL (youtube.com or youtu.be) to a configured Telegram bot Data Collection: Workflow extracts video ID and simultaneously fetches full transcript and metadata (title, channel, views, duration, chapters, tags) via Decodo API Processing: Raw transcript data is extracted and cleaned, while metadata is parsed into structured fields including formatted statistics and chapter timestamps AI Processing: Google Gemini Flash analyzes the transcript to generate a structured summary covering one-line overview, key points, main topics by chapter, tools mentioned, target audience, practical takeaways, and notable quotes Setup Guide Prerequisites | Requirement | Type | Purpose | |-------------|------|---------| | n8n instance | Essential | Workflow execution platform | | Telegram Bot API | Essential | Receives video links and delivers summaries | | Decodo Scraper API | Essential | Extracts YouTube transcripts and metadata | | Google Gemini API | Essential | AI-powered summary generation | Installation Steps Import the JSON file to your n8n instance Configure credentials: Telegram Bot API: Create a bot via @BotFather on Telegram, obtain the API token, and configure in n8n Telegram credentials Decodo API: Sign up at Decodo Dashboard, get your API key, create HTTP Header Auth credential with header name "Authorization" and value "Basic [YOUR_API_KEY]" Google Gemini API: Obtain API key from Google AI Studio, configure in n8n Google Palm API credentials Update environment-specific values: In the "Alert Admin" node, replace YOUR_CHAT_ID with your personal Telegram user ID for error notifications Optionally adjust the languageCode in "Set: Video ID & Config" node (default: "en") Customize settings: Modify the AI prompt in "Generate TLDR" node to adjust summary structure and depth Test execution: Send a YouTube link to your Telegram bot Verify you receive the "Processing..." notification, video info card, and formatted summary chunks Technical Details Workflow Logic The workflow employs parallel processing for efficiency. Transcript and metadata are fetched simultaneously after video ID extraction. Once both API calls complete, the transcript feeds directly into Gemini AI while metadata is parsed separately. The merge node combines AI output with structured metadata before splitting into Telegram-friendly chunks. Error handling is isolated on a separate branch triggered by any node failure, formatting error details and alerting admins without disrupting the main flow. Customization Options Basic Adjustments: Language Selection**: Change languageCode from "en" to "id", "es", "fr", etc. to fetch transcripts in different languages (YouTube must have captions available) Summary Style**: Edit the prompt in "Generate TLDR" to focus on specific aspects (e.g., "focus only on technical tools mentioned" or "create a summary for beginners") Message Length**: Adjust maxCharsPerChunk (currently 4000) to create longer or shorter message splits based on preference Advanced Enhancements: Database Storage**: Add a Postgres/Airtable node after "Merge: Data + Summary" to archive all summaries with timestamps and user IDs for searchable knowledge base (medium complexity) Multi-Model Comparison**: Duplicate the "Generate TLDR" chain and connect GPT-4 or Claude, merge results to show different AI perspectives on the same video (high complexity) Auto-Translation**: Insert a translation node after summary generation to deliver summaries in user's preferred language automatically (medium complexity) Troubleshooting Common Issues: | Problem | Cause | Solution | |---------|-------|----------| | "Not a YouTube URL" error | URL format not recognized | Ensure UR sent contains youtube.com or youtu.be | | No transcript available | Video lacks captions or wrong language | Check video has auto-generated or manual captions change languageCode to match available options | | Decodo API 401/403 error | Invalid or expired API key | Verify API key in HTTP Header Auth credential. regenerate if needed from Decodo dashboard || | Error notifications not received | Wrong chat ID in Alert Admin node | Get your Telegram user ID from @userinfobot and update the node | Use Case Examples Scenario 1: Marketing Agency Competitive Analysis Challenge: Agency needs to analyze 50+ competitor YouTube videos monthly to identify content strategies, tools used, and messaging angles—watching all videos would require 80+ hours Solution: Drop youtube links into a shared Telegram group with the bot. Summaries are generated instantly, highlighting tools mentioned, key talking points, and target audience insights Result: Research time reduced from 80 hours to 6 hours monthly (93% time savings), with searchable archive of all competitor content strategies Created by: Khaisa Studio Category: AI-Powered Automation Tags: YouTube, AI, Telegram, Summarization, Content Analysis, Decodo, Gemini Need custom workflows? Contact us Connect with the creator: Portfolio • Workflows • LinkedIn • Medium • Threads

⚡ Quick Setup Import this workflow into your n8n instance. Add your Apify, Google Sheets, and Firecrawl credentials. Activate the workflow to start your automated lead enrichment system. Copy the webhook URL from the MCP trigger node. Connect AI agents using the MCP URL. 🔧 How it Works This solution combines two powerful workflows to deliver fully enriched, AI-ready business leads from Google Maps: Apify Google Maps Scraper Node: Collects business data and, if enabled, enriches each lead with contact details and social profiles. Leads Missing Enrichment: Any leads without contact or social info are automatically saved to a Google Sheet. Firecrawl & Code Node Workflow: A second workflow monitors the Google Sheet, crawls each business’s website using Firecrawl, and extracts additional social media profiles or contact info using a Code node. Personalization Logic: AI-powered nodes generate tailored outreach content for each enriched lead. Native Integration: The entire process is exposed as an MCP-compatible interface, returning enriched and personalized lead data directly to the AI agent. 📋 Available Operations Business Search: Find businesses on Google Maps by location, category, or keyword. Lead Enrichment: Automatically append contact details, social profiles, and other business info using Apify and Firecrawl. Personalized Outreach Generation: Create custom messages or emails for each lead. Batch Processing: Handle multiple leads in a single request. Status & Error Reporting: Get real-time feedback on processing, enrichment, and crawling. 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: Search queries (location, keywords, categories) Enrichment options (contact, social, etc.) Personalization variables (name, business type, etc.) Response Format: Returns fully enriched lead data and personalized outreach content in a structured format.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This template generates structured synthetic company content using live web data from the Bedrijfsdata.nl API combined with an LLM. Provide a company domain (directly or via a Bedrijfsdata.nl ID) and the workflow retrieves relevant website and search engine content, then produces ready-to-use descriptions of the company, its offerings, and its target audience. ✨ Features Create high-quality Dutch-language company descriptions on demand Automatically pull live web content via Bedrijfsdata.nl RAG Domain & RAG Search Structured JSON output for consistent downstream use (e.g., CRM updates, lead qualification) Flexible trigger: run from ProspectPro ID, domain input, or another workflow Secure, modular, and extendable structure (error handling included) 🏢 Example Output The workflow produces structured content fields you can directly use in your sales, marketing, or enrichment flows: company_description** – 1-2 paragraph summary of the company products_and_services** – detailed overview of offerings target_audience** – specific characteristics of ideal customers (e.g., industry, location, company size, software usage) Example: { "company_description": "Bedrijfsdata.nl B.V. is een Nederlands bedrijf dat uitgebreide data levert over meer dan 3,7 miljoen bedrijven in Nederland...", "products_and_services": "Het bedrijf biedt API-toegang tot bedrijfsprofielen, sectoranalyses, en SEO-gegevens...", "target_audience": "Nederlandse MKB's die behoefte hebben aan actuele bedrijfsinformatie voor marketing- of salesdoeleinden..." } ⚙ Requirements n8n instance or cloud workspace Install the Bedrijfsdata.nl n8n Verified Community Node OpenAI API credentials (tested with gpt-4.1-mini and gpt-3.5-turbo) Bedrijfsdata.nl developer account (14-day free trial, 500 credits) 🔧 Setup Instructions 1. Trigger configuration Use Bedrijfsdata.nl ID (default) or provide a domain directly Can be called from another workflow using “Execute Workflow” 2. Configure API credentials Bedrijfsdata.nl API key OpenAI API key 3. Customize Output (Optional) Adjust prompt in the LLM node to create other types of synthetic content Extend structured output schema for your use case 4. Integrate with Your Stack Example node included to update HubSpot descriptions Replace or extend to match your CRM, database, or messaging tools 🔐 Security Notes Input validation for required domain Dedicated error branches for invalid input, API errors, LLM errors, and downstream integration errors RAG content checks before running the LLM 🧪 Testing Run workflow with a Bedrijfsdata.nl ID linked to a company with a known website Review generated JSON output Verify content accuracy before production use 📌 About Bedrijfsdata.nl Bedrijfsdata.nl operates the most comprehensive company database in the Netherlands. With real-time data on 3.7M+ businesses and AI-ready APIs, we help Dutch SMEs enrich their CRM, workflows, and marketing automation. Built on 25+ years of experience in data collection and enrichment, our technology brings corporate-grade data quality to every organisation. Website: https://www.bedrijfsdata.nl Developers: https://developers.bedrijfsdata.nl API docs: https://docs.bedrijfsdata.nl 📞 Support Email: klantenservice@bedrijfsdata.nl Phone: +31 20 789 50 50 Support hours: Monday–Friday, 09:00–17:00 CET