Category: n8n Workflows

What This Workflow Does

This n8n workflow automates comprehensive investor portfolio risk assessment and compliance monitoring using AI-powered analysis. It consolidates financial data from multiple sources and applies intelligent evaluation to identify potential risks, compliance issues, and portfolio vulnerabilities in real-time. The workflow leverages Qwen-Max AI through OpenRouter to process complex financial information and deliver actionable insights via Slack and email notifications.

How It Works

The workflow operates on a scheduled trigger that runs hourly or daily based on your configuration. Once activated, it authenticates with five critical data APIs to gather information across financial, operational, legal, and regulatory domains. The collected data flows through an AI agent powered by Qwen-Max, which analyzes portfolio metrics against predefined risk thresholds and compliance rules. Results are parsed into structured format, evaluated through conditional logic, and distributed to stakeholders via Slack messages and Gmail notifications. The merge node consolidates multiple data streams for comprehensive reporting.

Use Cases

• Real-time portfolio risk monitoring for investment firms managing multiple client accounts and asset classes
• Automated compliance verification ensuring adherence to regulatory requirements and internal governance policies
• Investor alert system that triggers notifications when portfolio metrics exceed risk tolerance thresholds
• Multi-source data consolidation combining financial performance, operational metrics, and legal compliance status into single dashboard view
• Due diligence automation for evaluating investment opportunities against standardized risk and compliance criteria

Nodes Used

• Schedule Trigger: Initiates workflow on hourly or daily schedule
• HTTP Request: Authenticates and retrieves data from five external APIs
• Set: Configures variables and data structure for workflow processing
• @n8n/Agent: Implements AI-powered analysis using Qwen-Max through OpenRouter
• @n8n/OutputParserStructured: Converts AI responses into structured JSON format
• If: Applies conditional logic based on risk thresholds and compliance rules
• Code: Executes custom JavaScript for advanced data transformation
• Gmail: Sends email notifications to portfolio managers and investors
• Slack: Posts real-time alerts and compliance reports to team channels
• @n8n/lmChatOpenRouter: Manages communication with language models via OpenRouter API
• Merge: Consolidates multiple data streams for comprehensive reporting
• Sticky Note: Provides documentation and configuration notes within workflow

Prerequisites

• Active n8n instance with access to workflow automation features
• OpenRouter API credentials for accessing Qwen-Max AI model
• Authentication credentials for five financial and compliance data APIs
• Slack workspace with webhook URL for bot integration
• Gmail account configured for automated email distribution
• Defined risk thresholds appropriate for your portfolio and investment strategy
• Compliance rules aligned with regulatory requirements and internal policies
• Recipient list for both Slack channels and email notifications

Difficulty Level

Advanced. This workflow requires expertise in financial data integration, API authentication, AI agent configuration, and multi-channel notification setup. Users should be comfortable mapping financial data structures, setting conditional logic based on risk metrics, and configuring OpenRouter credentials. Knowledge of compliance frameworks and portfolio risk assessment methodology is recommended for optimal customization.

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

What This Workflow Does

This workflow automates your entire post-meeting routine by intelligently analyzing meeting transcripts to extract action items, create organized tasks, and draft professional follow-up communications. Instead of manually reviewing recordings and sending emails after every meeting, this automation handles it all in seconds.

How It Works

The workflow follows a streamlined process to transform raw meeting data into actionable tasks and communications:

• Fetch Meeting Data: Retrieves meeting transcripts directly from Fireflies.ai using their API integration
• AI Analysis: Processes transcripts with GPT-4O to intelligently extract action items and identify tasks assigned to you
• Task Automation: Automatically creates organized tasks in ClickUp with relevant details and deadlines
• Draft Communications: Generates professional follow-up email drafts based on meeting content
• Smart Distribution: Routes notifications via Telegram and sends drafts through Gmail for your review

Use Cases

• Sales Team Efficiency: Automatically capture action items from client calls and create follow-up tasks without manual data entry
• Project Management: Extract deliverables and deadlines from team meetings and sync them directly to your project management system
• Executive Assistants: Streamline the process of transcribing, summarizing, and creating tasks from executive meetings
• Consulting Teams: Generate client follow-ups and action item summaries from consultation calls automatically
• Remote Team Coordination: Keep distributed teams aligned by automatically creating tasks from all-hands and department meetings

Nodes Used

• Schedule Trigger: Initiates workflow at specified intervals
• HTTP Request: Connects to Fireflies.ai API for transcript retrieval
• Code: Custom logic processing for data manipulation
• Split in Batches: Processes multiple transcripts efficiently
• n8n Agent: Orchestrates AI-powered decision making
• LM Chat OpenAI: GPT-4O integration for transcript analysis
• ClickUp Tool: Creates and manages tasks in ClickUp
• Telegram: Sends instant notifications
• If: Conditional routing based on analysis results
• Gmail: Sends draft emails for review
• Tool Think: Advanced reasoning capabilities
• Output Parser Structured: Formats AI responses into structured data
• Sticky Note: Documentation and workflow annotations

Prerequisites

• Active Fireflies.ai account with API access enabled
• OpenAI API key for GPT-4O model access
• ClickUp workspace with appropriate permissions for task creation
• Gmail account configured for sending emails
• Telegram bot token for notification delivery
• n8n instance with HTTP request and integration nodes available

Difficulty Level

Intermediate. This workflow combines multiple API integrations and AI processing. Users should be comfortable with API authentication, JSON data handling, and basic conditional logic. Prior experience with n8n or similar automation platforms is recommended.

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

What This Workflow Does

This n8n workflow automates invoice processing by allowing users to upload invoices through Telegram. The system automatically downloads files, extracts structured data using ChatGPT-4o-mini, and returns analyzed results directly in Telegram. Perfect for accountants and finance teams who need instant invoice data extraction without manual data entry.

How It Works

The workflow follows a straightforward process that handles invoice uploads and analysis seamlessly.

• A Telegram bot receives invoice documents sent by users
• The workflow validates that the uploaded file is a document
• Files are downloaded from Telegram servers via HTTP request
• OpenAI’s GPT-4o-mini model extracts key invoice data using advanced AI
• Extracted information is formatted into structured data
• Results are sent back to the user through Telegram

Use Cases

• Accounting teams automating invoice data entry and reducing manual work by hours daily
• Finance departments quickly extracting vendor information, amounts, and dates from hundreds of invoices
• Freelancers and small business owners tracking expenses and organizing financial records efficiently
• Corporate compliance teams auditing invoices and ensuring all required fields are captured correctly
• Accounts payable departments streamlining vendor invoice processing and payment approval workflows

Nodes Used

• Telegram Trigger – Listens for incoming messages and file uploads on Telegram
• If Node – Validates whether the uploaded file is a document before processing
• HTTP Request – Downloads invoice files from Telegram servers
• Extract From File – Processes document content for AI analysis
• ChatGPT-4o-mini (LM Chat OpenAI) – Extracts structured data from invoice content
• Code Node – Formats and prepares extracted data for output
• Telegram Node – Sends analysis results back to the user
• Sticky Note – Provides workflow documentation and instructions

Prerequisites

• An active n8n instance with access to workflow creation and management
• A Telegram bot token obtained from BotFather on Telegram
• An OpenAI API key with access to GPT-4o-mini model
• Basic understanding of workflow automation and node configuration
• Permission to connect your Telegram bot to n8n credentials

Difficulty Level

Intermediate. This workflow requires setting up Telegram bot credentials and OpenAI API keys, understanding how to validate file types, and configuring AI extraction parameters. Users with basic automation experience can deploy this workflow with minimal adjustments needed for their specific invoice formats.

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

What This Workflow Does

This intelligent invoice processing workflow automates the extraction, classification, and management of invoice data from PDF documents. The system uses advanced AI capabilities to categorize expenses, detect anomalies, and export structured data in XML format for seamless integration with accounting and financial management systems.

How It Works

The workflow follows a multi-stage intelligent processing pipeline:

• Invoices are uploaded through Google Drive or webhook triggers, initiating the automated workflow
• PDF content is extracted and parsed to retrieve key invoice data
• The extracted information is processed through AI-powered classification algorithms
• An intelligent agent analyzes and categorizes expenses while detecting potential anomalies or discrepancies
• Classified data is validated through conditional filters to ensure accuracy
• Results are exported to multiple destinations including XML files, Google Sheets, email notifications, and Slack alerts
• Webhook responses provide real-time feedback to connected systems

Use Cases

• Automated expense categorization for multi-departmental organizations requiring detailed cost allocation and budget tracking
• Accounts payable automation for reducing manual invoice processing time and improving accuracy in large-volume environments
• Fraud detection and anomaly identification by flagging unusual invoice patterns or suspicious transactions
• Integration with enterprise accounting systems through standardized XML export for seamless financial data synchronization
• Real-time invoice notifications to finance teams via Slack and email, enabling faster approval workflows and decision-making

Nodes Used

• Google Drive Trigger – Monitors for new invoice uploads in designated folders
• Webhook – Receives invoice submissions from external systems and applications
• Merge – Combines data from multiple sources for unified processing
• Filter – Validates and refines data based on specific criteria
• Google Drive – Retrieves and stores invoice files and processed results
• Extract From File – Parses PDF content and extracts structured invoice data
• Code – Performs custom data transformations and formatting
• OpenAI LM Chat – Powers AI-driven expense classification and analysis
• Agent – Coordinates intelligent decision-making and anomaly detection
• XML – Formats processed data into standard XML structure for system integration
• Set – Configures and transforms data payloads throughout the workflow
• If – Enables conditional routing based on classification results and validation rules
• Gmail – Sends email notifications to stakeholders with processing results
• Slack – Posts real-time alerts and summary reports to team channels
• Google Sheets – Logs all processed invoices and maintains audit trails
• Respond to Webhook – Returns processing results to requesting systems
• Sticky Note – Provides workflow documentation and instructions

Prerequisites

• Active n8n instance with workflow automation capabilities enabled
• Google Drive account with folder access for invoice storage and file management
• OpenAI API key for accessing GPT models and intelligent classification features
• Gmail account configuration for email notification delivery
• Slack workspace and webhook integration for team alert channels
• Google Sheets access for maintaining invoice processing logs
• PDF invoices in standardized format for accurate text extraction
• Understanding of XML structure for system integration requirements

Difficulty Level

Advanced – This workflow requires familiarity with multiple integration platforms, API configurations, and AI-driven automation concepts. Users should have experience with data extraction, conditional logic, and system integration to effectively customize and maintain this solution.

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

What This Workflow Does

This workflow automates the entire job application screening process using artificial intelligence. It intelligently analyzes resumes, evaluates candidate skills and cultural fit, maintains organized records in spreadsheets, and automatically schedules interviews through email. The system reduces manual review time and ensures consistent candidate evaluation across all applicants.

How It Works

The workflow follows a streamlined multi-step process to handle job applications efficiently:

• Receive Applications: A webhook endpoint receives new job application data in real-time
• Extract Resume Content: The system downloads and extracts text from uploaded resumes and CVs
• AI Analysis: GPT-4 analyzes extracted resume content to score technical skills, experience level, and cultural alignment with company values
• Record Results: Evaluation scores and candidate information are automatically saved to Google Sheets for tracking and reporting
• Decision Logic: Conditional branching determines next steps based on qualification thresholds
• Schedule Interviews: Qualified candidates receive automated email invitations with interview scheduling details
• Send Notifications: Team members receive Slack alerts about new qualified candidates and screening results

Use Cases

• High-volume recruitment departments receiving dozens of applications daily who need faster initial screening without sacrificing quality
• Startup hiring teams lacking dedicated HR resources that need automated candidate evaluation to scale hiring efforts
• Technical positions requiring specialized skill assessment where AI can objectively score qualifications against job requirements
• Remote companies managing global applications across different time zones needing asynchronous interview scheduling
• Contract and temporary staffing agencies processing numerous short-term applications requiring rapid turnaround and consistent evaluation standards

Nodes Used

• Webhook: Receives incoming job application data and triggers the workflow automatically
• HTTP Request: Downloads resume files from external URLs for processing
• Code Node: Processes and extracts text content from PDF and document files
• OpenAI: Uses GPT-4 to analyze resume content and generate candidate evaluation scores
• Google Sheets: Records all screening results, scores, and candidate information for tracking
• If Condition: Routes qualified candidates to interview scheduling based on score thresholds
• Gmail: Sends automated interview invitation emails to qualified candidates
• Slack: Notifies team members of screening results and qualified candidates
• Set Node: Formats and structures data between workflow steps
• Sticky Note: Provides workflow documentation and configuration instructions

Prerequisites

• Active n8n instance with webhook capability enabled
• OpenAI API key with GPT-4 model access for resume analysis
• Google Sheets document prepared with columns for candidate names, scores, and evaluation results
• Google Sheets API credentials configured in n8n
• Gmail account with SMTP access for sending interview invitations
• Gmail credentials authenticated in n8n for email sending
• Slack workspace and bot token for team notifications
• Slack credentials configured in n8n for channel posting
• Job application data source or form that can POST data to the webhook URL
• Resume files hosted on accessible URLs or encoded in base64 format

Difficulty Level

Intermediate. This workflow requires understanding of API authentication, conditional logic, and integration between multiple external services. Users should be comfortable configuring credentials for OpenAI, Google Sheets, Gmail, and Slack. Basic knowledge of JSON data formatting and webhook concepts is helpful but not strictly required. The workflow can be adapted by users with moderate n8n experience.

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

What This Workflow Does

This n8n workflow automates cross-border revenue tax mapping and compliance by collecting transaction data, calculating taxes according to regional regulations, detecting anomalies, and generating compliance reports. It streamlines financial reconciliation processes and reduces manual data entry errors while ensuring accurate tax documentation across multiple jurisdictions.

How It Works

The workflow operates on a scheduled trigger that runs daily to process financial transactions. It retrieves transaction data from your database, applies tax calculation rules based on revenue source location, identifies unusual patterns or discrepancies, and generates compliance documentation. Results are aggregated into summaries and distributed via email and Slack notifications, with detailed reports stored in Google Drive for audit purposes.

Use Cases

• Daily financial reconciliation across multiple currency transactions and payment gateways
• Automated tax calculation based on customer location, product type, and applicable regional tax rates
• Anomaly detection in revenue streams to identify potential fraud, refund patterns, or unusual transactions
• Monthly compliance report generation for tax authorities in different jurisdictions
• Real-time alerts for transactions exceeding tax thresholds or requiring manual review

Nodes Used

• Schedule Trigger – Initiates the workflow at specified intervals
• Set – Defines variables and tax configuration parameters
• HTTP Request – Fetches transaction data from external APIs or databases
• Code – Implements custom tax calculation and validation logic
• Aggregate – Combines multiple transaction records into summary datasets
• Filter – Removes irrelevant transactions or identifies flagged items
• If – Creates conditional branches for different tax scenarios
• Postgres – Queries and updates transaction records in your database
• Summarize – Creates compliance and financial summary reports
• Gmail – Sends tax reports and notifications via email
• Google Drive – Stores compliance documentation and historical records
• Slack – Delivers real-time alerts and status updates to team channels
• Split Out – Distributes processed data to multiple downstream systems
• Sticky Note – Documents workflow logic and configuration notes

Prerequisites

• Active Google Workspace account with Gmail, Sheets, and Drive access
• API credentials configured for Google services authentication
• Access to transaction database with read and write permissions
• PostgreSQL or compatible database connection configured
• Tax rule configuration document specifying rates and thresholds by jurisdiction
• Slack workspace with appropriate channel permissions for notifications
• Understanding of your specific regional tax requirements and compliance rules

Difficulty Level

Advanced. This workflow requires knowledge of tax regulations, database queries, API integration, and custom code implementation. Users should be comfortable configuring database connections, writing JavaScript for tax calculations, and managing multiple third-party integrations. Customization is recommended to match your specific business structure and local tax requirements.

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

What This Workflow Does

This intelligent workflow automates customer churn prediction and retention outreach by combining data analysis with AI-powered personalization. It continuously monitors customer behavior patterns, identifies those at risk of leaving, and triggers targeted retention campaigns through automated emails—all without manual intervention.

How It Works

The workflow operates on a scheduled trigger that runs at regular intervals to keep your retention efforts active and timely. Here’s the step-by-step process:

• A scheduled trigger initiates the workflow at predetermined intervals
• An HTTP request retrieves customer data from your CRM system
• PostgreSQL queries extract usage patterns and engagement metrics from your database
• Customer data is merged and prepared for analysis
• OpenAI analyzes the aggregated data to calculate churn risk scores for each customer
• A conditional node filters customers who meet the high-risk threshold
• Personalized retention emails are automatically sent via Gmail to at-risk customers
• Campaign results and customer interactions are logged to Google Sheets for tracking and optimization

Use Cases

• SaaS Retention: Identify underutilized accounts and send feature education campaigns to increase engagement and prevent cancellations
• E-commerce Customer Loyalty: Detect declining purchase frequency and trigger personalized discount offers before customers switch to competitors
• Subscription Box Services: Monitor engagement metrics and automatically send exclusive perks to customers showing signs of disengagement
• Professional Services: Track client project activity and proactively reach out with upsell opportunities to at-risk accounts
• B2B Account Management: Combine usage data with support ticket volume to identify accounts needing immediate attention and personalized outreach

Nodes Used

• Sticky Note: Provides workflow documentation and reference notes
• Schedule Trigger: Executes the workflow on a recurring schedule
• HTTP Request: Fetches customer data from external CRM systems
• Code: Processes and transforms data with custom logic
• PostgreSQL: Queries customer usage logs and behavioral data
• Merge: Combines data from multiple sources into a unified dataset
• OpenAI: Analyzes customer behavior to calculate churn risk predictions
• If: Routes high-risk customers to retention actions
• Gmail: Sends personalized retention emails to at-risk customers
• Google Sheets: Logs campaign results and tracks retention metrics

Prerequisites

• Active n8n instance with workflow automation capabilities
• PostgreSQL database with customer usage data and engagement metrics
• CRM system with accessible API or HTTP endpoint for customer data
• OpenAI API key with GPT access for churn analysis
• Gmail account configured for automated email sending
• Google Sheets account for logging campaign results
• Customer data containing engagement metrics, support tickets, and activity history
• Basic understanding of workflow logic and conditional routing

Difficulty Level

Intermediate: This workflow requires familiarity with API integrations, database queries, and conditional logic. Setup involves configuring multiple authentication credentials and mapping data fields across systems. Users should be comfortable with JSON data structures and basic SQL queries. Customization may be needed to match your specific customer data schema and CRM structure.

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

What This Workflow Does

This automated workflow revolutionizes inventory management by combining artificial intelligence with intelligent supplier selection. It predicts future customer demand, identifies potential stock shortages before they occur, and automatically requests competitive quotes from multiple suppliers to secure the best pricing and delivery terms.

How It Works

The workflow operates through a systematic seven-step process designed to minimize manual intervention while optimizing inventory levels:

• Data Collection: Aggregates sales data from point-of-sale systems, database records, weather patterns, and social media trends to build a comprehensive demand picture
• AI-Powered Forecasting: Analyzes collected data using machine learning algorithms to predict customer demand for the next seven days
• Stock Analysis: Identifies items at risk of running out and calculates optimal reorder quantities
• Supplier Requests: Automatically sends quote requests to multiple pre-configured vendors
• Smart Selection: Evaluates supplier responses based on price, delivery time, reliability ratings, and inventory availability
• Order Placement: Places purchase orders with the optimal supplier automatically
• Notifications: Sends alerts to your team via Slack with order details and supplier information

Use Cases

• Retail Chains: Large retailers can synchronize inventory across multiple locations, automatically replenishing high-turnover items based on local demand patterns and seasonal trends
• E-Commerce Businesses: Online stores benefit from predictive ordering that accounts for traffic spikes, promotional events, and customer behavior analytics to maintain optimal stock levels
• Food and Beverage Distribution: Fresh goods suppliers can reduce spoilage by accurately predicting demand and coordinating just-in-time deliveries from multiple vendors
• Manufacturing Supply Chain: Production facilities can automate raw material ordering based on forecast demand, ensuring assembly lines never experience unexpected delays
• Seasonal Product Management: Businesses selling seasonal items can leverage weather data and trend analysis to predict peaks and valleys in customer demand

Nodes Used

• Sticky Note: Documentation and workflow comments
• Schedule Trigger: Runs the workflow on a recurring schedule (daily, weekly, or custom intervals)
• HTTP Request: Fetches data from external APIs and sends requests to supplier systems
• MySQL: Queries and stores historical sales data, inventory levels, and supplier information
• Merge: Combines data from multiple sources into unified datasets
• Code: Executes custom JavaScript logic for demand calculations and supplier scoring
• If: Conditional branching based on stock levels and forecast thresholds
• Split in Batches: Processes multiple suppliers and orders in parallel batches
• Slack: Sends notifications to team channels with order summaries and alerts

Prerequisites

• Active n8n instance with workflow automation capabilities
• MySQL database with sales history, inventory records, and supplier contact information
• API access to your point-of-sale or e-commerce platform for real-time sales data
• Supplier APIs or contact methods configured for quote requests
• Slack workspace and bot token for team notifications
• External data sources for weather and trend analysis (optional but recommended)
• Basic understanding of database queries and HTTP API communication

Difficulty Level

Intermediate to Advanced: This workflow requires familiarity with database management, API integration, and conditional logic. Users should be comfortable configuring multiple external connections and writing custom JavaScript for demand forecasting algorithms. Implementation time typically ranges from 4-8 hours depending on your existing systems and data sources.

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

What This Workflow Does

This workflow automates the entire employee leave request approval process using artificial intelligence and calendar integration. It streamlines leave submissions, generates professional summaries, routes approval decisions, and automatically schedules calendar events. The system eliminates manual processing delays and ensures consistent communication between employees and human resources departments.

How It Works

The leave approval system follows a structured automation sequence:

• Employee submits a leave request through the form trigger interface
• The AI agent analyzes the request and generates a professional summary
• OpenAI language model processes the request details and recommends actions
• A structured output parser extracts and formats the decision data
• The system conditionally routes the request based on approval status
• Approved requests automatically create calendar events in Google Calendar
• Email notifications are sent to relevant parties through Gmail integration
• All decisions are logged in sticky notes for record-keeping and audit trails

Use Cases

• Large corporations managing hundreds of leave requests monthly across multiple departments
• Remote-first companies needing transparent and automated approval workflows
• HR departments reducing manual review time while maintaining consistent policy enforcement
• Organizations requiring automatic calendar blocking to prevent scheduling conflicts during employee absences
• Companies implementing AI-assisted decision-making while maintaining human oversight in the approval chain

Nodes Used

• formTrigger: Captures employee leave request submissions with relevant details
• @n8n/agent: Orchestrates the AI decision-making process for leave evaluations
• @n8n/lmChatOpenAi: Generates intelligent summaries and recommendations using OpenAI language models
• @n8n/outputParserStructured: Formats and structures the AI output into usable approval decisions
• gmail: Sends approval or discussion notifications to employees and HR staff
• if: Routes requests based on approval status and conditional logic
• googleCalendarTool: Automatically creates and blocks calendar time for approved leave requests
• stickyNote: Documents decisions and maintains audit trails for compliance

Prerequisites

• Active n8n instance with workflow execution capabilities
• OpenAI API key for the language model functionality
• Gmail account configured with SMTP credentials for email notifications
• Google Calendar integration with appropriate API permissions
• Form builder access to create the employee submission interface
• User roles and permissions configured for HR personnel and employees

Difficulty Level

Intermediate. This workflow combines multiple integrations and conditional logic, requiring familiarity with AI nodes, email services, and calendar APIs. Users should have basic experience with n8n workflow building and API authentication before implementing this template.

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

What This Workflow Does

This automation streamlines the entire employee onboarding process by automatically creating offer letters, setting up Google Workspace accounts, and populating employee information into Google Sheets. It eliminates manual data entry and document creation, reducing onboarding time from hours to minutes while ensuring consistency and accuracy across all new hire documentation.

How It Works

The workflow begins when candidate data is submitted through a webhook, capturing essential information including personal details, banking information, and job specifications. The system then processes this data through multiple automated steps:

• Data validation and field mapping ensures all information is correctly structured
• PDF generation creates professional offer letters customized with candidate details using PdfBro
• Gmail integration sends the generated documents to candidates automatically
• Google Gemini AI processes and extracts key information from the submission
• Google Workspace Admin tools create new employee accounts with appropriate permissions
• Google Sheets automatically records all employee data for centralized tracking and reporting

Use Cases

• Enterprise HR departments processing multiple new hires weekly, needing automated document generation and account provisioning
• Staffing agencies managing high-volume onboarding for contract and permanent placements across multiple organizations
• Growing startups standardizing their onboarding process as they scale from manual to automated operations
• Organizations requiring compliance documentation that needs consistent formatting, signatures, and audit trails for every new employee
• Multi-location companies ensuring uniform onboarding procedures across different departments and geographic regions

Nodes Used

• Webhook – Receives candidate data from external applications or forms
• Set – Configures and maps data fields for processing
• PdfBro – Generates professional PDF documents with dynamic content
• Gmail Trigger – Monitors incoming emails for onboarding requests
• Google Gemini – AI-powered data extraction and processing
• Google Sheets – Records and organizes employee information
• Gmail – Sends automated communications and documents
• Code – Custom logic for complex data transformations
• Agent – Orchestrates multi-step processes with intelligent routing
• If – Conditional logic for branching workflows based on data conditions
• Sticky Note – Documentation and workflow annotation
• Google Workspace Admin – Creates and configures user accounts and permissions

Prerequisites

• Active n8n instance with workflow execution capabilities
• Google Cloud Project with Google Workspace Admin API enabled
• Gmail account with SMTP access configured for sending documents
• Google Sheets document prepared with employee data columns
• PdfBro account or integration for PDF generation
• Google Gemini API access for AI-powered data processing
• Candidate data source that can trigger the webhook endpoint

Difficulty Level

This workflow is classified as advanced. It requires familiarity with multiple Google services, API authentication, PDF templating concepts, and basic workflow logic. Users should have experience configuring OAuth connections, understanding JSON data structures, and troubleshooting multi-node integrations. Prior experience with Google Workspace administration and Gmail automation is beneficial.

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