Category: n8n Workflows

What This Workflow Does

This n8n workflow automates the entire support ticket lifecycle by integrating Jira with AI-powered intelligence. It automatically retrieves open support tickets from Jira on a scheduled basis, uses artificial intelligence to analyze and categorize tickets, and generates intelligent responses or triage recommendations without manual intervention. The workflow eliminates duplicate processing and streamlines ticket management for support teams.

How It Works

The workflow operates through a series of interconnected steps that handle ticket retrieval, analysis, and organization:

• A scheduled trigger runs at defined intervals to check for newly opened tickets in your Jira support queue
• The Jira node fetches all open support tickets from your configured Jira instance
• A remove duplicates node prevents the same tickets from being processed multiple times by marking them as seen
• The workflow uses OpenAI’s language model to analyze ticket content and determine appropriate categorization
• An output parser structures the AI analysis into usable data formats
• Tickets are split into batches for efficient processing
• Results are aggregated and organized for easy review and action

Use Cases

• Automatic prioritization of support tickets based on urgency and complexity detected by AI analysis
• Intelligent ticket routing to appropriate support team members or departments without manual assignment
• Generation of initial response templates or suggested solutions for common support issues
• Detection and flagging of duplicate or related tickets for consolidation and better tracking
• Classification of tickets by issue type, product area, or customer segment for better organization and metrics

Nodes Used

• Schedule Trigger – Executes the workflow at specified intervals
• Jira – Retrieves open support tickets from your Jira instance
• Set – Configures and transforms data between workflow steps
• OpenAI LM Chat – Analyzes ticket content using advanced language models
• Output Parser Structured – Formats AI responses into structured data
• Chain LLM – Sequences multiple language model operations
• Split In Batches – Divides tickets into manageable groups for processing
• No Operation – Serves as a control flow node where needed
• Aggregate – Combines processed ticket data back together
• Sticky Note – Provides documentation and notes within the workflow
• Remove Duplicates – Prevents reprocessing of already-handled tickets

Prerequisites

• An active Jira account with access to your support ticket queue
• Jira API credentials configured in n8n for authentication
• An OpenAI API key with access to GPT models
• n8n instance with the ability to create and manage workflows
• Understanding of your ticket structure and desired triage categories
• Regular monitoring and adjustment of AI prompts for optimal results

Difficulty Level

Intermediate. This workflow combines multiple advanced nodes and requires configuration of API connections with both Jira and OpenAI. Users should have basic familiarity with n8n workflows, scheduled triggers, and AI model integration. However, the template provides a solid foundation that can be customized based on specific support requirements.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

This workflow automates the complete process of creating trend-based blog content. It researches current trends, analyzes them with AI, generates full-length articles, creates matching cover images, and publishes everything to your content management system—all on a scheduled basis without manual intervention.

How It Works

The workflow operates through a series of automated steps triggered on a weekly schedule:

• A scheduled trigger initiates the workflow at your defined intervals with a pre-configured search keyword
• Apify scrapes trending data from Google and social media platforms to identify current topics
• GPT-4O analyzes the scraped trend data and generates insights for article creation
• The workflow generates a complete, ready-to-publish blog article based on the analysis
• DALL-E 3 creates a custom cover image that matches the article topic and style
• The finished article and image are saved as a draft to Notion for review or immediate publishing
• A Slack notification alerts your team that new content is ready

Use Cases

• Content Marketing Agencies: Automatically generate trend-based content for multiple clients, scaling content production without proportional increases in team size
• News and Media Outlets: Stay ahead of trending topics by publishing AI-drafted articles about current events within hours of trends emerging
• Niche Blogs: Maintain consistent publishing schedules by automating research and drafting for industry-specific trends and topics
• E-commerce Businesses: Create trend-focused blog content that drives organic traffic and positions products as solutions to current customer interests
• SaaS Companies: Generate educational content around industry trends that establish thought leadership and improve search engine visibility

Nodes Used

• Schedule Trigger: Sets the frequency and timing for workflow execution
• Set Node: Defines configuration variables including search keywords and parameters
• Apify: Scrapes and extracts trending data from Google and social media sources
• OpenAI (GPT-4O): Analyzes trends and generates full-length blog articles with insights
• OpenAI (DALL-E 3): Creates custom, visually relevant cover images for articles
• Code Node: Processes and transforms data between workflow steps
• Notion: Stores completed articles and images as drafts for review or publishing
• Aggregate Node: Combines data from multiple sources into structured formats
• Slack: Sends notifications to your team when content is ready
• Sticky Note: Provides documentation and notes within the workflow

Prerequisites

• An active n8n account with workflow creation capabilities
• OpenAI API key with access to GPT-4O and DALL-E 3 models
• Apify account with enabled web scraping capabilities for Google Trends and social media
• Notion workspace with database created for storing draft articles
• Slack workspace with bot permissions for sending channel notifications
• Basic understanding of workflow configuration and API authentication

Difficulty Level

This workflow is classified as intermediate to advanced. While n8n handles most automation steps through pre-built nodes, successful implementation requires familiarity with API key configuration, database setup in Notion, and understanding of how to customize search keywords and AI prompts for your specific content needs. Users new to n8n should review the basic workflow documentation before attempting to deploy this template.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

This n8n workflow automates the entire process of handling Tally form submissions. Instead of manually copying and pasting responses, the workflow automatically captures each submission, stores it in Airtable, and sends a confirmation email to the user — all in seconds without requiring any code.

How It Works

The workflow follows a simple three-step automation pipeline:

• A webhook listens for incoming Tally form submissions in real-time
• Form data is automatically formatted and pushed into your Airtable database
• A confirmation email is instantly sent to the respondent with their submission details

The workflow uses a wait node to manage timing and a set node to prepare data for each step, ensuring smooth data flow and reliable delivery.

Use Cases

• Lead Generation: Capture contact information from landing page forms and automatically log leads in Airtable while sending confirmation emails
• Event Registration: Process sign-ups for webinars or events, store attendee data, and send instant registration confirmations
• Customer Feedback: Collect survey responses in a centralized database while acknowledging submissions with automated thank-you emails
• Job Applications: Receive application forms, organize candidate information in Airtable, and send automatic receipt confirmations
• Service Inquiries: Manage service request forms by logging details in Airtable and notifying customers that their inquiry was received

Nodes Used

• Webhook: Receives Tally form submissions as they happen
• Set: Prepares and structures data for downstream nodes
• Wait: Introduces timing delays between automation steps
• Airtable: Stores form responses in a database table
• Gmail: Sends confirmation emails to form respondents
• Sticky Note: Provides workflow documentation and reference notes

Prerequisites

• An active Tally account with a form ready to connect
• An Airtable workspace with a table prepared to receive form data
• A Gmail account configured in n8n for sending emails
• Access to n8n (cloud or self-hosted) with appropriate permissions
• Basic understanding of how to copy webhook URLs and configure integrations

Difficulty Level

This workflow is beginner-friendly and requires no programming knowledge. All nodes use simple point-and-click configuration. The most technical step is connecting your accounts and mapping form fields to Airtable columns, which takes just a few minutes to set up.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

This n8n workflow automates the monitoring of Trump Truth Social posts and sends real-time alerts to both Telegram and Discord channels. The automation checks for new posts on a scheduled basis, filters them based on criteria, and instantly notifies users through their preferred messaging platforms whenever new content matches the specified parameters.

How It Works

The workflow operates through a series of automated steps designed to streamline social media monitoring:

• A scheduled trigger initiates the workflow at predetermined intervals
• The workflow queries a Supabase database to retrieve stored data and track previous posts
• Conditional logic evaluates whether new posts meet the monitoring criteria
• An HTTP request fetches the latest content from Truth Social
• Custom code processes and formats the data for readability
• Telegram and Discord integrations send formatted alerts to specified channels
• Rate limiting prevents excessive notifications and API overuse

Use Cases

• Political analysts monitoring public statements for research and reporting purposes
• News organizations tracking breaking announcements for editorial content
• Social media managers staying informed about relevant industry discussions
• Community administrators keeping group members updated on important developments
• Content creators gathering reference material for commentary and analysis

Nodes Used

• Schedule Trigger: Sets the frequency for workflow execution
• If: Creates conditional branches based on specified criteria
• Supabase: Manages data storage and retrieval for tracking purposes
• Sticky Note: Provides workflow documentation and notes
• HTTP Request: Fetches data from Truth Social or other API endpoints
• Code: Executes custom JavaScript for data processing and formatting
• Telegram: Sends alerts to Telegram channels or direct messages
• Discord: Posts notifications to Discord servers and channels
• Limit: Controls notification frequency and prevents rate limit violations

Prerequisites

• Active n8n account or self-hosted n8n instance
• Supabase project with database tables configured
• Telegram bot token and chat ID for message delivery
• Discord webhook URL or bot token with appropriate permissions
• Access to Truth Social API or public data source
• Basic understanding of workflow automation and node configuration

Difficulty Level

Intermediate. This workflow requires knowledge of multiple integrations and basic API concepts. Users should be comfortable configuring database connections, webhooks, and conditional logic. Prior experience with n8n or similar automation platforms is recommended for successful deployment and customization.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

This automation sends deadline reminder emails at strategic intervals—today, 3 days before, and 7 days before task due dates. Instead of manually tracking spreadsheet tasks and sending individual reminders, the workflow automatically monitors your task list and notifies team members at the right time, ensuring nothing falls through the cracks.

How It Works

The workflow operates through a daily scheduled trigger that executes every morning at your specified time. Here’s the process:

• Schedule Trigger initiates the workflow automatically without manual intervention
• Google Sheets node retrieves your task list containing due dates and assignee information
• Split in Batches node divides tasks into manageable groups for processing
• If conditions evaluate each task to determine which reminder category it falls into (7-day, 3-day, or today)
• Gmail node sends formatted reminder emails to the appropriate recipients based on deadline proximity

Use Cases

• Project Management Teams tracking multiple deliverables across different deadlines and wanting automatic email notifications without manual oversight
• Freelance Agencies coordinating client projects where reminder emails reduce missed deadlines and improve project delivery rates
• Content Calendars where editorial teams need escalating reminders for publication dates and content submission deadlines
• HR Departments managing onboarding tasks, compliance deadlines, and employee review schedules with automated notifications
• Sales Teams tracking follow-up tasks and proposal deadlines to ensure timely client communication and increased closing rates

Nodes Used

• Schedule Trigger—sets the daily execution time for automated workflow runs
• Google Sheets—connects to your task management spreadsheet to fetch deadline and assignee data
• Split in Batches—processes tasks in groups to optimize email delivery performance
• If—evaluates task due dates against today’s date to categorize reminders by urgency level
• Gmail—sends personalized reminder emails with task details and deadlines
• Sticky Note—provides workflow documentation and setup instructions

Prerequisites

• Active n8n instance with workflow execution capability
• Google Sheets document containing tasks with columns for task name, due date, and assignee email
• Gmail account with SMTP access configured in n8n
• Proper authentication credentials stored in n8n for both Google Sheets and Gmail services
• Task spreadsheet formatted consistently with standardized date fields for accurate deadline calculation

Difficulty Level

Intermediate. This workflow requires understanding of scheduling triggers, conditional logic, and email integration. No coding is necessary, but familiarity with Google Sheets structure and Gmail configuration is helpful. Users comfortable with basic n8n workflows can implement and customize this template within 15-20 minutes.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

This n8n workflow automates the process of adding reactions to Telegram channel posts using bot accounts. It intelligently parses user requests, extracts post links and reaction quantities, and systematically applies reactions through multiple bot instances while respecting rate limits.

How It Works

The workflow follows these steps:

• A Telegram trigger listens for incoming messages containing reaction requests
• OpenAI analyzes the message to extract the target post URL and desired number of reactions
• The workflow splits the reaction batch into smaller groups to avoid overwhelming the Telegram API
• A wait node introduces delays between API calls to prevent rate limiting
• HTTP requests execute the actual reaction additions through Telegram bot endpoints
• The limit node ensures only valid requests are processed

Use Cases

• Boost engagement on Telegram channel announcements by automatically adding emoji reactions
• Increase post visibility by distributing reactions across multiple bot accounts
• Manage community feedback by allowing users to request reactions via simple commands
• Automate social proof mechanisms for promotional content on Telegram channels
• Create interactive workflows where channel admins can trigger mass reactions with natural language requests

Nodes Used

• Telegram Trigger: Captures incoming messages and initiates the workflow
• OpenAI (@n8n/openAi): Parses user requests to extract URLs and reaction counts
• Code: Processes and transforms data between workflow steps
• Split in Batches: Divides reactions into manageable groups for API calls
• Limit: Filters and validates incoming requests
• Wait: Introduces delays to prevent rate limiting
• HTTP Request: Executes API calls to add reactions to posts
• Sticky Note: Provides documentation and workflow notes

Prerequisites

• Active n8n instance with workflow creation access
• Telegram bot token for the primary bot account
• Multiple Telegram bot accounts or user accounts to distribute reactions
• OpenAI API key for message analysis and parsing
• Access to target Telegram channels for posting reactions
• Understanding of Telegram Bot API and reaction endpoints
• Valid Telegram channel links to use as targets

Difficulty Level

Intermediate to Advanced. This workflow requires understanding of API rate limiting, batch processing, and Telegram Bot API mechanics. Users should be comfortable with environment variables, API authentication, and debugging HTTP requests. Some customization of the OpenAI prompt and code nodes may be needed for specific use cases.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

The TG-Bot-Module-Cross_Posting-v1-db-sell-full workflow automates the process of receiving messages through a Telegram bot, processing them with AI summarization, storing data in a PostgreSQL database, and intelligently routing responses based on conditional logic. This workflow enables seamless cross-platform posting with automated content summarization and database management.

How It Works

The workflow begins when a Telegram bot receives a trigger message. The incoming data is processed through a series of nodes that validate, summarize, and route the information:

• Telegram trigger captures incoming bot messages
• Set node initializes and configures workflow variables
• PostgreSQL node stores message data and retrieves relevant information from the database
• If and Switch nodes evaluate conditions to determine the appropriate workflow path
• Summarize node uses AI to condense message content into concise summaries
• Telegram node sends processed responses back to users
• Sticky Note provides workflow documentation and guidance

Use Cases

• Product Listings: Automatically receive product information via Telegram, summarize details, store in database, and post across multiple channels
• Customer Service Automation: Capture customer inquiries, route them based on type, summarize issues, and log them in a database for tracking
• Content Distribution: Receive content submissions through Telegram, summarize key points, store versions, and cross-post to different platforms
• Lead Management: Collect lead information via bot messages, categorize using conditional logic, store in PostgreSQL, and trigger follow-up actions
• Inventory Updates: Process inventory changes submitted through Telegram, summarize updates, maintain database records, and distribute notifications

Nodes Used

• Telegram Trigger: Listens for incoming messages to the Telegram bot
• Set: Configures and initializes workflow variables and data structures
• PostgreSQL: Executes database queries to store and retrieve information
• If: Implements conditional branching based on single criteria
• Switch: Routes workflow based on multiple condition evaluations
• Summarize: Uses AI language models to create content summaries
• Telegram: Sends messages and responses back to Telegram users
• Sticky Note: Provides inline documentation and workflow notes

Prerequisites

• Active Telegram bot with API token configured in n8n
• PostgreSQL database with appropriate tables and schema
• n8n instance with database credentials configured
• AI/LLM service credentials for the summarize node
• Appropriate database permissions for read and write operations
• Telegram bot added to relevant groups or direct message configuration

Difficulty Level

Intermediate. This workflow requires understanding of database operations, conditional logic, external API integration with Telegram, and AI model usage. Users should have basic familiarity with n8n node types and database schema before implementing this workflow.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

This n8n workflow automates the processing of incoming Telegram messages by intelligently separating text content from file attachments. When a user sends a message to your Telegram bot, the workflow automatically parses the input and extracts both the text message and any files into separate, organized outputs. This makes it easy to handle different types of content independently without manual intervention.

How It Works

The workflow begins with a Telegram trigger that listens for incoming messages. When a message arrives, the workflow uses a switch node to determine whether the message contains text, files, or both. Based on this classification, it routes the message through different processing paths. Text content is isolated in one field while file attachments are extracted and converted to binary data format, making them ready for immediate use or storage. A split output node ensures that if multiple files are attached, each one is processed as a separate item.

Use Cases

• Customer support automation that separates customer inquiries (text) from supporting documents or images for organized ticket creation
• Content management systems that receive media files via Telegram and need to categorize them by message descriptions and file types
• Document processing pipelines where users send PDFs or images with descriptive text that needs to be parsed separately for indexing
• Lead generation workflows that collect form responses as text messages alongside supporting files like resumes or portfolios
• Automated archival systems that organize user-submitted content by separating descriptions from actual files for proper database storage

Nodes Used

• Telegram Trigger: Listens for incoming messages to your Telegram bot
• Set: Defines variables and prepares data for downstream processing
• Switch: Routes messages based on content type (text only, files only, or both)
• Split Out: Separates multiple files into individual items for parallel processing
• Telegram: Sends processed results or confirmations back through Telegram
• No Operation: A pass-through node used for conditional branching
• Sticky Note: Provides inline documentation and workflow explanations

Prerequisites

• An active n8n instance (cloud or self-hosted)
• A Telegram bot created through BotFather with a valid API token
• The Telegram bot webhook configured and running
• Basic familiarity with n8n workflow concepts and node configuration
• Appropriate permissions to create and manage Telegram bots

Difficulty Level

Intermediate. This workflow combines multiple logical branches and data transformation steps. Users should have basic experience with n8n, understand how to configure Telegram connections, and be comfortable working with conditional logic and data parsing. The modular design makes it a good learning project for understanding message routing and file handling in automation workflows.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

This n8n workflow automates the handover of customer support conversations from an AI assistant to human agents via Telegram. When conversations become too complex for the AI to handle, the system automatically escalates the chat to a human support team member and sends email alerts to notify them of the pending support request.

How It Works

The workflow begins when a user sends a message to a Telegram bot. The message is processed by GPT-4 through an AI agent that determines whether the query can be handled automatically or requires human intervention. If the AI detects that human assistance is needed, the workflow automatically:

• Pauses the automated response system
• Prepares a summary of the conversation context
• Sends an email alert to the support team with all relevant details
• Notifies the user in Telegram that a human agent will take over shortly
• Routes the conversation to the appropriate support channel for manual handling

Use Cases

• E-commerce support teams handling product inquiries that require manual verification or special approvals
• SaaS customer support routing technical issues from chatbots to specialist engineers
• Healthcare or legal service providers escalating sensitive client questions to qualified professionals
• Subscription services managing account-specific requests that need human verification
• Multi-language support centers identifying conversations requiring human translators or cultural context

Nodes Used

• Telegram Trigger – Captures incoming Telegram messages
• Set – Initializes and configures workflow variables
• Telegram – Sends messages back to users in Telegram
• If – Conditional logic for decision branching
• Email Send – Dispatches email notifications to support staff
• GPT-4 with OpenRouter – AI model for conversation analysis
• Agent – Orchestrates AI decision-making processes
• Memory Buffer Window – Maintains conversation history context
• Telegram Tool – Extended Telegram functionality
• Azure OpenAI – Alternative AI processing option
• Data Table – Organizes and displays structured data
• Switch – Routes workflow based on conditions
• HTTP Request – Makes external API calls if needed
• NoOp – Placeholder for future workflow extensions
• Sticky Note – Adds documentation and comments within the workflow

Prerequisites

• Active n8n account with workflow creation access
• Telegram account with admin access to create bots and groups
• OpenAI API key or Azure OpenAI credentials for GPT-4 access
• Email service credentials configured in n8n (SMTP or third-party email provider)
• Telegram group with Topics feature enabled for organizing support conversations
• BotFather access on Telegram for bot token generation
• Basic understanding of n8n workflow nodes and data flow

Difficulty Level

Intermediate. This workflow requires familiarity with n8n node configuration, Telegram bot setup, and AI model integration. While the basic structure is straightforward, customizing the escalation logic and email templates to match your specific support processes may require additional configuration and testing.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

The TG-Bot-Module-Quiz-v4-db-sell-full workflow is a comprehensive Telegram bot solution that delivers interactive quizzes to users while managing data persistence through a PostgreSQL database. This automation captures quiz responses, tracks user progress, and stores results for sales analytics and lead generation purposes.

How It Works

The workflow operates through a series of intelligent nodes that handle incoming Telegram messages and process quiz interactions. When a user triggers the bot, the telegramTrigger node initiates the sequence. The workflow then evaluates user input through conditional logic using switch and if nodes to route responses appropriately. Quiz data flows through a sort node for organization, while the set and code nodes transform and prepare information for storage. The postgres node manages all data persistence, saving quiz answers and user metrics to your database. The wait node introduces strategic delays for improved user experience, and the merge node consolidates data streams before final delivery back to Telegram users.

Use Cases

• Lead generation campaigns where businesses deliver product knowledge quizzes and capture qualified prospects through Telegram
• Educational platforms providing interactive learning modules with instant feedback and progress tracking for students
• E-commerce businesses using quizzes to guide product recommendations and save customer preferences for personalized marketing
• Market research and customer surveys collecting structured feedback directly through Telegram with automatic database organization
• Employee training programs delivering compliance or skill assessment quizzes with automated result documentation and reporting

Nodes Used

• telegramTrigger: Listens for incoming Telegram messages and initiates the workflow
• telegram: Sends quiz questions and responses back to users through Telegram
• switch: Routes workflow logic based on different user responses or input types
• if: Evaluates conditional statements to determine workflow path
• sort: Organizes quiz data and responses in specified order
• set: Assigns and formats data values for processing
• code: Executes custom JavaScript for advanced data manipulation and quiz logic
• postgres: Manages database connections and stores all quiz responses and user data
• wait: Introduces timed delays between quiz questions for better user experience
• merge: Combines multiple data streams into unified output
• summarize: Generates quiz result summaries and performance analytics
• stickyNote: Provides workflow documentation and usage notes

Prerequisites

• An active n8n instance or cloud account with workflow creation capabilities
• A Telegram bot token obtained from BotFather on Telegram
• PostgreSQL database with appropriate tables for storing quiz responses and user data
• Basic understanding of n8n node connections and data flow
• Postgres credentials configured in n8n (host, database name, username, password)
• Telegram bot webhook or polling configured to receive incoming messages

Difficulty Level

This workflow is classified as advanced. It requires familiarity with Telegram bot integration, PostgreSQL database management, and n8n’s conditional logic nodes. Users should understand how to map data between nodes and have experience writing basic JavaScript code for data transformation. While the workflow template provides a solid foundation, customization for specific quiz requirements and database schema modifications demand moderate technical expertise.

This workflow template is shared under the n8n fair-code license. Free to use and modify.