Workflow Templates

N8N for Beginners: Looping Over Items Description This workflow is designed for n8n beginners to understand how n8n handles looping (iteration) over multiple items. It highlights two key behaviors: Built-In Looping:** By default, most n8n nodes iterate over each item in an input array. Explicit Looping:* The *Loop Over Items* node allows controlled iteration, enabling *custom batch processing** and multi-step workflows. This workflow demonstrates the difference between processing an unsplit array of strings (single item) vs. a split array (multiple items). Setup 1. Input Data To begin, paste the following JSON into the Manual Trigger node: { "urls": [ "https://www.reddit.com", "https://www.n8n.io/", "https://n8n.io/", "https://supabase.com/", "https://duckduckgo.com/" ] } 📌 Steps to Paste Data: Double-click** the "Manual Trigger" node. Click "Edit Output" (top-right corner). Paste the JSON and Save. The node turns purple, indicating that test data is pinned. 1. Click "Test Workflow" button at the bottom of the canvas Explanation of the n8n Nodes in the Workflow | Node Name | Purpose | Documentation Link | |-----------|---------|--------------------| | Manual Trigger | Starts the workflow manually and sends test data | Docs | | Split Out | Converts an array of strings into separate JSON objects | Docs | | Loop Over Items (Loop Over Items 1) | Demonstrates how an unsplit array is treated as one item | Docs | | Loop Over Items (Loop Over Items 2) | Iterates over each item separately | Docs | | Wait | Introduces a delay per iteration (set to 1 second) | Docs | | Code | Adds a constant parameter (param1) to each item | Docs | | NoOp (Result Nodes) | Displays output for inspection | Docs | Execution Details 1. How the Workflow Runs Manual Trigger starts execution** with the pasted JSON data. The workflow follows two paths: Unsplit Array Path → Loop Over Items 1 Processes the entire array as a single item. Result1 & Result5: Show that the array was not split. Split Array Path → Split Out → Loop Over Items 2 Splits the array into separate objects. Result2, Result3, Result4: Show that each item is processed individually. A Wait node (1 sec delay) demonstrates controlled execution. Code nodes modify the JSON, adding a parameter (param1). 2. What You Will See | Node | Expected Output | |------|---------------| | Result1 & Result5 | The entire array is processed as one item. | | Result2, Result3, Result4 | The array is split and processed as individual items. | | Wait Node | Adds a 1-second delay per item in Loop Over Items 2. | Use Cases This workflow is useful for: ✅ API Data Processing: Loop through API responses containing arrays. ✅ Web Scraping: Process multiple URLs individually. ✅ Task Automation: Execute a sequence of actions per item. ✅ Workflow Optimization: Control execution order, delays, and dependencies. Notes Sticky notes are included in the workflow for easy reference. The Wait node is optional—remove it for faster execution. This template is structured for beginners but serves as a building block for more advanced automations.

Video Guide I prepared a detailed guide that showed the whole process of building a resume analyzer. Who is this for? This workflow is ideal for recruitment agencies, HR professionals, and hiring managers looking to automate the initial screening of CVs. It is especially useful for organizations handling large volumes of applications and seeking to streamline their recruitment process. What problem does this workflow solve? Manually screening resumes is time-consuming and prone to human error. This workflow automates the process, providing consistent and objective analysis of CVs against job descriptions. It helps filter out unsuitable candidates early, reducing workload and improving the overall efficiency of the recruitment process. What this workflow does This workflow automates the resume screening process using OpenAI for analysis. It provides a matching score, a summary of candidate suitability, and key insights into why the candidate fits (or doesn’t fit) the job. Retrieve Resume: The workflow downloads CVs from a direct link (e.g., Supabase storage or Dropbox). Extract Data: Extracts text data from PDF or DOC files for analysis. Analyze with OpenAI: Sends the extracted data and job description to OpenAI to: Generate a matching score. Summarize candidate strengths and weaknesses. Provide actionable insights into their suitability for the job. Setup Preparation Create Accounts: N8N: For workflow automation. OpenAI: For AI-powered CV analysis. Get CV Link: Upload CV files to Supabase storage or Dropbox to generate a direct link for processing. Prepare Artifacts for OpenAI: Define Metrics: Identify the metrics you want from the analysis (e.g., matching percentage, strengths, weaknesses). Generate JSON Schema: Use OpenAI to structure responses, ensuring compatibility with your database. Write a Prompt: Provide OpenAI with a clear and detailed prompt to ensure accurate analysis. N8N Scenario Download File: Fetch the CV using its direct URL. Extract Data: Use N8N’s PDF or text extraction nodes to retrieve text from the CV. Send to OpenAI: URL: POST to OpenAI’s API for analysis. Parameters: Include the extracted CV data and job description. Use JSON Schema to structure the response. Summary This workflow provides a seamless, automated solution for CV screening, helping recruitment agencies and HR teams save time while maintaining consistency in candidate evaluation. It enables organizations to focus on the most suitable candidates, improving the overall hiring process.

Find LinkedIn Professionals with Google Search and Airtable Who is this for? This workflow is perfect for sales professionals, recruiters, business development teams, and marketers who need to build targeted prospect lists from LinkedIn. Whether you're looking for specific job titles, industry professionals, or experts in particular locations, this template automates the tedious process of manual LinkedIn searching. Follow me for more What problem is this workflow solving? Finding qualified prospects on LinkedIn manually is time-consuming and inefficient. Traditional methods involve: Manually searching LinkedIn with limited search capabilities Copy-pasting profile information one by one Struggling with LinkedIn's search limitations and restrictions Difficulty organizing and tracking prospect data No systematic way to avoid duplicate contacts This workflow solves these challenges by leveraging Google's powerful search capabilities to find LinkedIn profiles at scale, automatically extracting key information, and organizing everything in a structured database. What this workflow does The workflow performs intelligent LinkedIn prospect discovery through these key steps: Keyword-Based Search: Uses Google Custom Search API to find LinkedIn profiles matching your specific criteria (job titles, industries, locations) Smart Data Extraction: Automatically parses profile titles, descriptions, URLs, and search snippets from Google results Structured Storage: Saves all prospect data to Airtable with proper field mapping and automatic deduplication Pagination Handling: Automatically processes multiple pages of search results to maximize prospect discovery Rate Limiting: Includes built-in delays to respect API limits and ensure reliable operation Key features: Deduplication**: Prevents storing duplicate LinkedIn profiles Batch Processing**: Handles large prospect lists efficiently Customizable Search**: Easily modify keywords to target different professional segments Clean Data Output**: Structured data ready for outreach campaigns Setup Prerequisites You'll need accounts with the following services: Google Cloud Console** (for Custom Search API) Airtable** (free tier works) n8n** (cloud or self-hosted) Step 1: Google Custom Search Setup Go to Google Cloud Console Create a new project or select existing one Enable the Custom Search API Create credentials (API Key) Set up a Custom Search Engine at Google CSE Configure it to search the entire web Copy your Search Engine ID (cx parameter) Bonus: Youtube Set-up Guide Step 2: Airtable Base Setup Create a new Airtable base with a table named "LinkedIn Prospects" containing these fields: Title (Single line text) - LinkedIn profile headline linkedin_url (URL) - Direct link to LinkedIn profile Search (Single line text) - Original search terms used Description (Long text) - Profile description/summary Snippet (Long text) - Google search result snippet Step 3: n8n Credentials Configuration Set up these credentials in n8n: Google Custom Search API: Type: HTTP Query Auth Name: Google Query Auth Query Parameter Name: key Value: Your Google API key Airtable: Type: Airtable Personal Access Token Token: Your Airtable personal access token Configure the base and table IDs in the Airtable node Step 4: Workflow Configuration Import this workflow template Update the "⚙️ CUSTOMIZE YOUR SEARCH KEYWORDS HERE" node with your target keywords Configure the Airtable node with your base and table information Test the workflow with a small keyword set first How to customize this workflow to your needs Targeting Different Industries Modify the search keywords in the yellow configuration node: // For technology professionals "Software Engineer React" "Product Manager SaaS" "Data Scientist Machine Learning" // For sales professionals "Account Executive Enterprise" "Sales Director B2B" "Business Development Manager" // For marketing professionals "Digital Marketing Manager" "Content Marketing Specialist" "Growth Marketing Lead" Geographic Targeting Add location keywords to narrow your search: "Marketing Manager London" "Sales Director New York" "Software Engineer Berlin" Company Size Targeting Include company type indicators: "CFO Startup" "VP Engineering Fortune 500" "Marketing Director SMB" Adjusting Search Volume Modify the Maxresults parameter in the "Configure Search Settings" node: Set to 10 for quick tests Set to 50-100 for comprehensive searches Maximum recommended: 100 per search to respect API limits Industry-Specific Customization For Recruiters: Target specific job titles and seniority levels Add skills-based keywords ("Python Developer", "React Specialist") Include experience indicators ("Senior", "Lead", "Principal") For Sales Teams: Focus on decision-maker titles ("Director", "VP", "C-Level") Target specific company sizes or industries Include location-based searches for territory management For Marketers: Search for industry influencers and thought leaders Target specific professional communities Look for content creators and industry experts Advanced Filtering Add conditional logic after the search results to filter prospects based on: Profile description keywords Title patterns Company information (when available in snippets) Integration Extensions Connect additional tools to enhance your prospect research: Email finder tools** (Hunter.io, Apollo) for contact discovery CRM integration** (HubSpot, Salesforce) for automatic lead creation Enrichment services** (Clearbit, ZoomInfo) for additional prospect data Slack/Teams notifications** for real-time prospect alerts Data Quality Improvements Enhance the workflow with additional processing: Duplicate detection** across multiple search terms Profile validation** to ensure active LinkedIn profiles Keyword scoring** to rank prospect relevance Export formatting** for specific CRM requirements This template provides a solid foundation that can be adapted for virtually any B2B prospect research need, making it an essential tool for modern sales and marketing teams.

Who is this template for? This workflow template is designed for any professionals seeking relevent data from database using natural language. How it works Each time user ask's question using the n8n chat interface, the workflow runs. Then the message is processed by AI Agent using relevent tools - Execute SQL Query, Get DB Schema and Tables List and Get Table Definition, if required. Agent uses these tool to form and run sql query which are necessary to answer the questions. Once AI Agent has the data, it uses it to form answer and returns it to the user. Set up instructions Complete the Set up credentials step when you first open the workflow. You'll need a Postgresql Credentials, and OpenAI api key. Template was created in n8n v1.77.0

Overview This workflow helps you compare Claude 3.5 Sonnet and Gemini 2.0 Flash when extracting data from a PDF This workflow extracts and processes the data within a PDF in one single step, instead of calling an OCR and then an LLM” How it works The initial 2 steps download the PDF and convert it to base64. This base64 string is then sent to both Claude 3.5 Sonnet and Gemini 2.0 Flash to extract information. This workflow is made to let you compare results, latency, and cost (in their dedicated dashboard). How to use it Set up your Google Drive if not already done Select a document on your Google Drive Modify the prompt in "Define Prompt" to extract the information you need and transform it as wanted. Get a Claude API key and/or Gemini API key Note that you can deactivate one of the 2 API calls if you don't want to try both Test the Workflow

Description This workflow automates email categorization in Gmail using the Gmail API and OpenAI's language model. It periodically checks for new emails, reads their content, and categorizes them based on existing Gmail labels. If no matching label is found, the workflow creates a new label and assigns it to the email. Key Features Polling for Emails**: The workflow triggers every 5 minutes to check for new emails using the Gmail Trigger node. Reading Labels**: Existing Gmail labels are fetched to determine the most relevant match for email categorization. Dynamic Labeling**: If no existing label matches, a new label is created dynamically based on the email's content. OpenAI Integration**: The workflow uses OpenAI's Chat model to analyze email content and suggest or create appropriate labels. Email Categorization**: Labels are applied to emails, ensuring they are organized in Gmail's structure. The workflow also removes less relevant emails (e.g., ads) from the inbox. Nodes in Use Gmail Trigger: Polls Gmail every 5 minutes for new emails. Gmail - Read Labels: Fetches all existing Gmail labels. Gmail - Get Message: Retrieves the full content of a specific email. Gmail - Add Label to Message: Assigns a chosen label to the email. Gmail - Create Label: Creates a new label if necessary. OpenAI Chat Model: Analyzes email content for categorization. Memory Buffer: Retains context for email analysis across multiple iterations. Wait Node: Adds a buffer period to manage email processing. Prerequisites Gmail API Setup**: Ensure Gmail OAuth2 credentials are configured in n8n. OpenAI API Key**: Configure OpenAI credentials for email analysis. Labeling Standards**: Maintain a consistent Gmail label structure for better organization. Instructions Add your Gmail API credentials to the Gmail nodes. Add your OpenAI API credentials to the OpenAI Chat Model node. Activate the workflow. It will start polling for new emails every 5 minutes. Monitor and refine the categorization logic if necessary to ensure alignment with Gmail's organizational needs. Use Case Ideal for individuals or teams handling high email volumes who want to maintain an organized inbox and automate repetitive categorization tasks. Note: You can improve the prompt to get better results from the agent by giving it more personal rules on how to categorize.

Community Node Disclaimer: This workflow uses KlickTipp community nodes. How It Works: Jotform Webinar Registry Integration: This workflow streamlines the process of handling webinar registrations submitted via JotForm. It ensures the data is correctly formatted and seamlessly integrates with KlickTipp. Data Transformation: Input data is validated and transformed to meet KlickTipp’s API requirements, including formatting phone numbers, converting dates, and validating URLs. Key Features JotForm Trigger: Captures new form submissions, including participant details and webinar preferences. Data Processing: Standardizes and validates input fields Converts phone numbers to numeric-only format with international prefixes. Transforms dates into UNIX timestamps. Validates LinkedIn URLs and applies fallback URLs if validation fails. Scales numerical fields, such as work experience, for specific use cases. Subscriber Management in KlickTipp: Adds or updates participants as subscribers in KlickTipp. Includes custom field mappings, such as: Personal information (name, email, phone number). Webinar details (chosen webinar, start date/time). Preferences (reminder intervals, questions for presenters). Tags contacts for segmentation: Adds fixed and dynamic tags to contacts. Error Handling: Validates critical fields like phone numbers, URLs, and dates to prevent incorrect data submissions. Setup Instructions Install and Configure Nodes: Set up the JotForm and KlickTipp nodes in your n8n instance. Authenticate your JotForm and KlickTipp accounts. Custom Field Preparation in KlickTipp: Create the necessary custom fields to match the data structure: | Name | Datentyp | | - | - | | Jotform_URL_Linkedin | URL | | Jotform_Workexperience_in_Years | Dezimalzahl | | Jotform_Webinar_start_timestamp | Datum & Zeit | | Jotform_Questions/Notes | Absatz | | Jotform_webinar | Zeile | | Jotform_reminder | Zeile | After creating fields, allow 10-15 minutes for them to sync. If fields don’t appear, reconnect your KlickTipp credentials. Field Mapping and Adjustments: Verify and customize field assignments in the workflow to align with your specific form and subscriber list setup. Workflow Logic Trigger via JotForm Submission: A new form submission from JotForm initiates the workflow Data Transformation: Processes raw form data to ensure compatibility with KlickTipp’s API. Add to KlickTipp Subscriber List: Adds participants to the designated KlickTipp list, including webinar-specific details. Get all tags from KlickTipp and create a list: Fetches all existing Tags and turns them into an array Define tags to dynamically set for contacts: Definiton of variables that are received from the form submission and should be converted into tags Merge tags of both lists: Checks whether the list of existing tags in KlickTipp contains the tags which should be dynamically set based on the form submission Tag creation and tagging contacts: Creates new tags if it previously did not exist and then tags the contact Benefits Efficient lead generation: Contacts from forms are automatically imported into KlickTipp and can be used immediately, saving time and increasing the conversion rate. Automated processes: Experts can start workflows directly, such as welcome emails or course admissions, reducing administrative effort. Error-free data management: The template ensures precise data mapping, avoids manual corrections and reinforces a professional appearance. Testing and Deployment: Test the workflow by filling the form on Jotform and verifying data updates in KlickTipp. Notes: Customization: Update field mappings within the KlickTipp nodes to align with your account setup. This ensures accurate data syncing. Resources: Jotform KlickTipp Knowledge Base help article Use KlickTipp Community Node in n8n Automate Workflows: KlickTipp Integration in n8n

Community Node Disclaimer: This workflow uses KlickTipp community nodes. How It Works Gravity Forms Customer Feedback Form Integration: This workflow streamlines the process of handling customer feedback submitted via Gravity Forms. It ensures the data is correctly formatted and seamlessly integrates with KlickTipp. Data Transformation: Input data is validated and transformed to meet KlickTipp’s API requirements, including formatting phone numbers and converting dates. Key Features Gravity Forms Trigger Captures new form submissions from Gravity Forms via a webhook and initiates the workflow. Data Processing and Transformation Formats and validates essential data: Converts phone numbers to numeric-only format with international prefixes. Transforms dates (e.g., birthdays) to UNIX timestamps. Calculates and scales numeric responses (e.g., webinar ratings). Parses webinar selections into timestamps for structured scheduling. Subscriber Management in KlickTipp Adds or updates contacts in a KlickTipp subscriber list. Includes custom field mappings such as: Personal details (name, email, birthday, phone number). Feedback and preferences (e.g., webinar ratings, chosen sessions). Structured answers from form responses. Tags contacts for segmentation: Adds fixed and dynamic tags to contacts. Error Handling Ensures invalid or empty data is handled gracefully, preventing workflow interruptions. Setup Instructions Install and Configure Nodes: Set up the Webhook, Set, and KlickTipp nodes in your n8n instance. Authenticate your Gravity Forms and KlickTipp accounts. Prepare Custom Fields in KlickTipp: Create fields in KlickTipp to align with the form submission data, such as: | Name | Datentyp | |-----------------------------------|----------------| | Gravityforms_URL_Linkedin | URL | | Gravityforms_kurs/webinar_zeitpunkt | Datum & Zeit | | Gravityforms_kurs/webinar_bewertung | Dezimalzahl | | Gravityforms_feedback | Absatz | | Gravityforms_kontaktaufnahme | Zeile | After creating fields, allow 10-15 minutes for them to sync. If fields don’t appear, reconnect your KlickTipp credentials. Field Mapping and Adjustments: Verify and customize field assignments in the workflow to align with your specific form and subscriber list setup. Workflow Logic Trigger via Gravity Forms Submission: The workflow begins when a new form submission is received through the webhook. Transform Data for KlickTipp: Formats and validates raw form data for compatibility with KlickTipp’s API. Add to KlickTipp Subscriber List: Adds processed data as a new subscriber or updates an existing one. Get all tags from KlickTipp and create a list: Fetches all existing Tags and turns them into an array Define tags to dynamically set for contacts: Definiton of variables that are received from the form submission and should be converted into tags Merge tags of both lists: Checks whether the list of existing tags in KlickTipp contains the tags which should be dynamically set based on the form submission Tag creation and tagging contacts: Creates new tags if it previously did not exist and then tags the contact Benefits Efficient lead generation: Contacts from forms are automatically imported into KlickTipp and can be used immediately, saving time and increasing the conversion rate. Automated processes: Experts can start workflows directly, such as welcome emails or course admissions, reducing administrative effort. Error-free data management: The template ensures precise data mapping, avoids manual corrections and reinforces a professional appearance. Testing and Deployment Test the workflow by filling the form on Gravity Forms and verifying data updates in KlickTipp. Notes Customization: Update field mappings within the KlickTipp nodes to align with your account setup. This ensures accurate data syncing. Resources: Gravity Forms KlickTipp Knowledge Base help article Use KlickTipp Community Node in n8n Automate Workflows: KlickTipp Integration in n8n

Who is this for? This workflow is ideal for IT operations teams or system administrators who use ServiceNow to track incidents and Slack for team communication. It provides real-time updates on new ServiceNow incidents directly in a designated Slack channel, ensuring timely response and collaboration. What problem is this workflow solving? / Use case Manually monitoring ServiceNow for new incidents can be time-consuming and prone to delays. This workflow automates the process, ensuring that team members are instantly notified of new incidents, complete with all relevant details, in a Slack channel. It enhances operational efficiency and incident response time. What this workflow does Schedule or Manual Trigger: The workflow can be triggered manually or set to run automatically every 5 minutes. Retrieve New Incidents: Fetches incidents created in ServiceNow within the last 5 minutes. Error Handling: Posts an error message in Slack if there are issues connecting to ServiceNow. Incident Processing: If new incidents are found, they are sorted in ascending order by their number. Detailed incident information is formatted and sent to a specified Slack channel. No Incidents: If no new incidents are found, the workflow does nothing. Setup ServiceNow API Credentials: Configure ServiceNow Basic Authentication in the workflow to connect to your ServiceNow instance. Slack API Credentials: Add your Slack API credentials to enable message posting. Slack Channel Configuration: Define the Slack channel where notifications should be sent. Ensure the channel ID is correctly set in the Slack node. Adjust the Schedule: Modify the schedule in the Schedule Trigger node to suit your requirements. How to customize this workflow to your needs Notification Format: Customize the Slack message format to include additional or fewer details. Update the Blocks section in the Slack node for personalized messages. Incident Query Parameters: Adjust the sysparm_query parameter in the ServiceNow node to filter incidents based on specific criteria. Error Handling: Modify the error message in the Slack node for more detailed troubleshooting information. Features Real-Time Notifications**: Immediate updates on new ServiceNow incidents. Error Handling**: Alerts in Slack if the workflow encounters issues connecting to ServiceNow. Customizable Notifications**: Flexibility to modify incident details sent to Slack. This workflow streamlines incident management and fosters collaboration by delivering actionable updates directly to your team.

Who is this for? This workflow template is designed for AI enthusiasts, developers, and privacy-conscious users who want to leverage the power of local large language models (LLMs) without sending data to external services. It's particularly valuable for those running Ollama locally who want intelligent routing between different specialized models. What problem is this workflow solving? When working with multiple local LLMs, each with different strengths and capabilities, it can be challenging to manually select the right model for each specific task. This workflow automatically analyzes user prompts and routes them to the most appropriate specialized Ollama model, ensuring optimal performance without requiring technical knowledge from the end user. What this workflow does This intelligent router: Analyzes incoming user prompts to determine the nature of the request Automatically selects the optimal Ollama model from your local collection based on task requirements Routes requests between specialized models for different tasks: Text-only models (qwq, llama3.2, phi4) for various reasoning and conversation tasks Code-specific models (qwen2.5-coder) for programming assistance Vision-capable models (granite3.2-vision, llama3.2-vision) for image analysis Maintains conversation memory for consistent interactions Processes everything locally for complete privacy and data security Setup Ensure you have Ollama installed and running locally Pull the required models mentioned in the workflow using Ollama CLI (e.g., ollama pull phi4) Configure the Ollama API credentials in n8n (default: http://127.0.0.1:11434) Activate the workflow and start interacting through the chat interface How to customize this workflow to your needs Add or remove models from the router's decision framework based on your specific Ollama collection Adjust the system prompts in the LLM Router to prioritize different model selection criteria Modify the decision tree logic to better suit your specific use cases Add additional preprocessing steps for specialized inputs This workflow demonstrates how n8n can be used to create sophisticated AI orchestration systems that respect user privacy by keeping everything local while still providing intelligent model selection capabilities.

Workflow Documentation: Auto-Retry Engine – Error Recovery Workflow Detailed Description The Auto-Retry Engine: Error Recovery Workflow is designed to automate the process of identifying and retrying failed executions in n8n workflows. By leveraging scheduled triggers, API integrations, and conditional logic, this workflow ensures that any failed executions are automatically retried on an hourly basis. This reduces manual intervention, improves system reliability, and ensures smoother workflow operations. Who is this for? This workflow is ideal for: Automation Engineers**: Managing and maintaining workflows with minimal manual intervention. DevOps Teams**: Ensuring high availability and reliability of automated processes. IT Administrators**: Reducing downtime and improving system performance by automating error recovery. What problem does this workflow solve? Manual Error Handling**: Eliminates the need for manual monitoring and retrying of failed executions. Improved Reliability**: Automatically retries failed executions, reducing downtime and improving workflow success rates. Time Efficiency**: Saves time by automating repetitive error recovery tasks, allowing teams to focus on higher-priority work. What this workflow does This workflow automates the following steps: Scheduled Monitoring: Checks for failed executions hourly using a schedule trigger. Error Filtering: Identifies executions that have failed and filters out those that have already been successfully retried. Authentication: Logs into the n8n instance using API credentials to retrieve session details. Automatic Retry: Retries the failed executions using the n8n API. Batch Processing: Processes multiple failed executions in batches to avoid overloading the system. Setup Prerequisites To use this workflow, you’ll need: n8n Account**: To create and run the workflow. n8n API Credentials**: For logging into the n8n instance and retrying executions. HTTP Request Node**: Configured to interact with the n8n API. Schedule Trigger**: Set to run the workflow hourly. Setup Process Configure Schedule Trigger Set the trigger to run hourly to check for failed executions. Set Login Credentials Add your n8n instance URL, username, and password in the Set Node. Integrate n8n API Use the HTTP Request node to log into the n8n instance and retrieve session details. Retry Failed Executions Configure the HTTP Request node to retry failed executions using the session details. Batch Processing Use the Split in Batches node to process multiple failed executions in batches. How to customize this workflow Tailor the workflow to fit your specific needs: Adjust Schedule Frequency** Modify the schedule trigger to run at different intervals (e.g., every 30 minutes). Add Notifications** Integrate email or Slack notifications to alert teams about failed retries. Refine Error Filtering** Customize the filtering logic to exclude specific types of failed executions. Scale Batch Size** Adjust the batch size in the Split in Batches node to optimize performance. Conclusion The Auto-Retry Engine: Error Recovery Workflow is a powerful tool for automating error recovery in n8n workflows. By reducing manual intervention and ensuring failed executions are retried automatically, this workflow enhances system reliability and operational efficiency. Whether you're managing a few workflows or a complex automation ecosystem, this workflow ensures your processes run smoothly and consistently.

Use Case Following up at the right time is one of the most important parts of sales. This workflow uses Gmail to send outreach emails to Hubspot contacts that have already been contacted only once more than a month ago, and records the engagement in Hubspot. Setup Setup HubSpot Oauth2 creds (Be careful with scopes. They have to be exact, not less or more. Yes, it’s not simple, but it’s well documented in the n8n docs. Be smarter than me, read the docs) Setup Gmail creds. Change the email variables in the Set keys node How to adjust this template There's plenty to do here because the approach here is really just a starting point. Most important here is to figure out what your rules are to follow up. After a month? More than once? Also, remember to update the follow-up email! Unless you want to sell n8n 😉