Workflow Templates

How it works It’s very important to come prepared to Sales calls. This often means a lot of manual research about the person you’re calling with. This workflow delivers a summary of the latest social media activity (LinkedIn + X) for businesses you are about to interact with each day. Scans Your Calendar**: Each morning, it reviews your Google Calendar for any scheduled meetings or calls with companies based on each attendee email address. Fetches Latest Posts**: For each identified company, it fetches recent LinkedIn and X posts and summerizes them using AI to deliver a qucik overview for a busy sales rep. Delivers Insights**: You receive personalized emails via Gmail, each dedicated to a company you’re meeting with that day, containing a reminder of the meeting and a summary of company's recent social media activity. Setup steps The workflow requires you to have the following accounts set up in their respective nodes: Google Calendar GMail Clearbit OpenAI Besides those, you will need an account on the RapidAPI platform and subscribe to the following APIs: Fresh LinkedIn Profile Data Twitter Email example

How it works It’s very important to come prepared to Sales calls. This often means a lot of manual research about the person you’re calling with. This workflow delivers the latest social media activity (LinkedIn + X) for businesses you are about to interact with each day. Scans Your Calendar**: Each morning, it reviews your Google Calendar for any scheduled meetings or calls with companies based on each attendee email address. Fetches Latest Posts**: For each identified company, it fetches recent LinkedIn and X posts Delivers Insight**s: You receive personalized emails via Gmail, each dedicated to a company you’re meeting with that day, containing a reminder of the meeting, list of posts categorized by the social media platform, and direct links to posts. Setup steps The workflow requires you to have the following accounts set up in their respective nodes: Google Calendar GMail Clearbit Besides those, you will need an account on the RapidAPI platform and subscribe to the following APIs: Fresh LinkedIn Profile Data Twitter Email example

Automated weekly report that summarizes technology stack changes, trends, and insights from your tracked companies. 🚀 What It Does Compiles weekly technology updates Highlights significant changes Identifies emerging trends Provides actionable insights Delivers scheduled reports 🎯 Perfect For CTOs and technical leaders Sales and marketing teams Business intelligence Technology consultants Market researchers ⚙️ Key Benefits ✅ Weekly digest of changes ✅ Trend analysis ✅ Competitive intelligence ✅ Time-saving automation ✅ Data-driven decisions 🔧 What You Need BuiltWith API access n8n instance Email service (for delivery) Google Sheets (for data storage) 📊 Report Includes New technology adoptions Technology removals Industry trends Competitive analysis Custom metrics 🛠️ Setup & Support Quick Setup Get your first report in 15 minutes with our step-by-step guide 📺 Watch Tutorial 💼 Get Expert Support 📧 Direct Help Stay ahead of technology trends with a comprehensive weekly digest of your industry's technology landscape.

This n8n template leverages n8n's multi-form feature to build a 2 part job application submission journey which aims to eliminate the need for applicants to re-enter data found on their CVs/Resumes. How it works The application submission process starts with an n8n form trigger to accept CV files in the form of PDFs. The PDF is validated using the text classifier node to determine if it is a valid CV else the applicant is asked to reupload. A basic LLM node is used to extract relevant information from the CV as data capture. A copy of the original job post is included to ensure relevancy. Applicant's data is then sent to an ATS for processing. For our demo, we used airtable because we could attach PDFs to rows. Finally, a second form trigger is used for the actual application form. However, it is prefilled to save the applicant's time and allow them to amend any of the generated application fields. How to use Ensure to change the redirect URL in the form ending node to use the host domain of your n8n instance. Requirements OpenAI for LLM Airtable to capture applicant data Customising the workflow Application form is pretty basic for this demonstration but could be extended to ask more in-depth questions. If it fits the job, why not ask applicants to upload portfolio works and have AI describe/caption them.

This n8n template can monitor and detect changes to a webpage's contents and notify you only when a change occurs. Great to keep an eye on and track publicly available documents such as company TOS, government policy or competitor pages. How it works A scheduled trigger is used so we can run everyday to automate this process. A website page is then fetched with the HTTP request node and the contents we want to track are extracted using the HTML node. To detect changes, we generate a hash on the contents with the cryptography node and compare it with previously seen hashes using the "remove duplicates" node. If the hash was seen before, the workflow stops here. Finally, when new changes are detected a copy of the contents are uploaded to Google Drive and a logged into a Google sheet. A notification email can also be sent if action is required. How to use Update the URL you want to track in the node named "variables" and ensure the HTML node has updated selectors to get the content you want. Ensure the timezone is set correctly when using the Scheduled Trigger node. Requirements Google Sheets, Drive and Gmail for storing and notifying about changes. Webpages should ideally be publicly accessible. If not, you may need to switch the HTTP request node with a webscraping service. Customising this workflow Not using Google? Easier swap to other Service providers such as Miscrosoft365. Need more URLs? Try modifing the variables node to accept multiple URLs though the HTML node will need to be customised.

Description AI-Powered Multi-language Customer Support In this guide, we'll walk you through setting up a comprehensive AI-driven workflow that handles customer messages in any language through WhatsApp and email channels, providing intelligent translation, summarization, and automated responses. Ready to revolutionize your customer support? Let's get started! What's the Goal? Automatically handle customer messages** from WhatsApp and email in any language Translate and validate** incoming messages with smart language detection Generate intelligent summaries** with priority classification for support teams Provide automated responses** back to customers via their preferred channel Log all interactions** to database for tracking and analytics Send notifications** to admin team for high-priority cases Deliver 24/7 multilingual customer support** without manual effort Integrate seamlessly** with WhatsApp Business API and email systems By the end, you'll have a fully automated customer support system that handles multilingual communications, prioritizes urgent cases, and maintains comprehensive interaction logs. Why Does It Matter? Manual handling of multilingual customer support can be overwhelming and inefficient. Here's why this workflow is a game-changer: Break Global Language Barriers**: Handle customer inquiries in any language effortlessly Never Miss Important Messages**: Priority detection ensures urgent cases get immediate attention Save 80% of Manual Work**: Automation handles routine inquiries and escalates complex ones 24/7 Availability**: Respond to customers anytime, enhancing satisfaction and retention Professional Customer Experience**: Consistent, well-formatted responses in the customer's language Complete Audit Trail**: Database logging provides insights and accountability Scalable Solution**: Handle growing customer base without proportional staff increase Think of it as your always-on, multilingual customer support team that never sleeps and never misses a beat. How It Works Here's the step-by-step magic behind the automation: Step 1: Multi-Channel Message Capture WhatsApp Trigger**: Captures incoming WhatsApp messages via Business API webhook Email Trigger (IMAP)**: Monitors designated customer support email for new messages Both channels feed into the same processing pipeline for consistent handling Step 2: Data Normalization & Validation Data Normalizer & Validator**: Standardizes message format regardless of source channel Extracts key information: sender details, message content, timestamp, channel source Validates data integrity and handles malformed inputs gracefully Step 3: Smart Language Translation Smart Language Translator**: Automatically detects source language and translates to English Preserves original message context and cultural nuances Stores both original and translated versions for reference Step 4: Enhanced Summary & Priority Processing Enhanced Summary & Priority Processor**: Uses AI to analyze translated content Generates concise summaries highlighting key customer concerns Priority Classification**: Automatically tags messages as: 🔴 High Priority: Urgent issues, complaints, billing problems 🟡 Medium Priority: Product inquiries, general support 🟢 Low Priority: Thank you messages, general feedback Creates structured output with priority flags for support team triage Step 5: Message Source Intelligence Check Message Source**: Determines optimal response channel and method Routes WhatsApp messages back to WhatsApp, emails back to email Maintains conversation context and threading Step 6: Automated Customer Response Customer WhatsApp Auto-Response**: Sends acknowledgment via WhatsApp Customer Email Auto-Response**: Sends professional email replies Responses include: Confirmation of message receipt Estimated response time based on priority Reference number for tracking Next steps or immediate solutions for common issues Step 7: Database Logging & Analytics Log to Database**: Stores complete interaction history including: Original message and translation Priority classification and reasoning Response sent and timestamp Customer contact information Channel and source metadata Enables analytics, reporting, and quality assurance Step 8: Admin Notifications & Alerts Admin Email Notification**: Immediate email alerts for high-priority cases Admin WhatsApp Alert**: SMS/WhatsApp notifications for urgent escalations Workflow Completion & Metrics**: Performance tracking and completion confirmations Workflow Architecture ┌─────────────────┐ ┌──────────────────┐ │ WhatsApp │ │ Email Trigger │ │ Trigger │ │ (IMAP) │ └─────────┬───────┘ └─────────┬────────┘ │ │ └──────────┬───────────┘ │ ┌──────────▼──────────┐ │ Data Normalizer & │ │ Validator │ └──────────┬──────────┘ │ ┌──────────▼──────────┐ │ Smart Language │ │ Translator │ └──────────┬──────────┘ │ ┌──────────▼──────────┐ │ Enhanced Summary & │ │ Priority Processor │ └──────────┬──────────┘ │ ┌──────────▼──────────┐ │ Check Message │ │ Source │ └─────────┬┬──────────┘ ┌┘└┐ ┌──────────▼┐ ┌▼──────────┐ │ Customer │ │ Customer │ │ WhatsApp │ │ Email │ │ Response │ │ Response │ └──────────┬┘ └┬──────────┘ └┬─┬┘ ┌─────────▼─▼─────────┐ │ Log to Database │ └─────────┬───────────┘ │ ┌─────────▼───────────┐ │ Admin Email │ │ Notification │ └─────────┬───────────┘ │ ┌─────────▼───────────┐ │ Admin WhatsApp │ │ Alert │ └─────────┬───────────┘ │ ┌─────────▼───────────┐ │ Workflow Completion │ │ & Metrics │ └─────────────────────┘ How to Use the Workflow? Importing a workflow in n8n is straightforward and allows you to use pre-built or shared workflows to save time. Below is a step-by-step guide to importing the Multi-language Customer Support workflow in n8n. Steps to Import a Workflow in n8n 1. Obtain the Workflow JSON Source the Workflow: Workflows are typically shared as JSON files or code snippets. You might receive them from: The n8n community (e.g., n8n.io workflows page) A colleague or tutorial (e.g., a .json file or copied JSON code) Exported from another n8n instance Format**: Ensure you have the workflow in JSON format, either as a file (e.g., customer-support-workflow.json) or as text copied to your clipboard 2. Access the n8n Workflow Editor Log in to n8n: Open your n8n instance (via n8n Cloud or your self-hosted instance) Navigate to the Workflows tab in the n8n dashboard Open a New Workflow: Click Add Workflow to create a blank workflow, or open an existing workflow if you want to merge the imported workflow 3. Import the Workflow Option 1: Import via JSON Code (Clipboard): In the n8n editor, click the three dots (⋯) in the top-right corner to open the menu Select Import from Clipboard Paste the JSON code of the workflow into the provided text box Click Import to load the workflow into the editor Option 2: Import via JSON File: In the n8n editor, click the three dots (⋯) in the top-right corner Select Import from File Choose the .json file from your computer Click Open to import the workflow Configuration Requirements Essential Setup Notes: WhatsApp Integration: Configure WhatsApp Business API credentials in the WhatsApp Trigger node Set up webhook URL in your WhatsApp Business account Test connection with a sample message Email Configuration: Set up IMAP credentials for your customer support email in the Email Trigger node Configure SMTP settings for outbound email responses Ensure proper email authentication (SPF, DKIM records) Translation Services: Add Google Translate API credentials in the Smart Language Translator node Alternative: Configure Azure Translator or AWS Translate based on preference Set up language detection and translation parameters Database Connection: Configure database credentials in the "Log to Database" node Create required tables for storing customer interactions: CREATE TABLE customer_interactions ( id SERIAL PRIMARY KEY, customer_contact VARCHAR(255), channel VARCHAR(50), original_message TEXT, translated_message TEXT, summary TEXT, priority VARCHAR(20), response_sent TEXT, timestamp TIMESTAMP DEFAULT CURRENT_TIMESTAMP ); Admin Notifications: Set up admin email addresses in notification nodes Configure WhatsApp/SMS credentials for urgent alerts Customize notification templates and thresholds Priority Classification Rules: Customize JavaScript code in "Enhanced Summary & Priority Processor" node Define keywords and patterns for priority detection: // High Priority Keywords const urgentKeywords = ['urgent', 'emergency', 'billing issue', 'not working', 'broken', 'refund', 'complaint']; // Medium Priority Keywords const mediumKeywords = ['question', 'how to', 'support', 'help', 'information']; // Classification logic if (urgentKeywords.some(keyword => message.toLowerCase().includes(keyword))) { priority = 'HIGH'; } else if (mediumKeywords.some(keyword => message.toLowerCase().includes(keyword))) { priority = 'MEDIUM'; } else { priority = 'LOW'; } Response Templates: Customize auto-response templates in both WhatsApp and Email response nodes Include your company branding and contact information Set up response templates for different priority levels and common scenarios Testing and Deployment: Test Each Channel: Send test messages via WhatsApp and email to verify end-to-end flow Verify Translations: Test with messages in different languages Check Database Logging: Confirm all interactions are properly stored Test Admin Notifications: Verify alerts are sent for high-priority cases Monitor Performance: Set up workflow execution monitoring and error handling Your Multi-language Customer Support workflow is now ready to handle customer communications 24/7 across multiple channels with intelligent automation and human oversight where needed!

What this workflow does Runs automatically every Monday morning at 8 AM Collects your Meta Ads data from the last 7 days for a given account (date range is configurable) Formats the data, aggregating it at the campaign, ad set, and ad levels Generates AI-driven analysis and insights on your results, providing actionable recommendations Renders the report as a visually appealing PDF with charts and tables Sends the report via Slack (you can also add email or WhatsApp) A sample for the first page of the report: Setup Guide Create an account of pdforge and use the pre-made Meta Ads template. Connect Meta Ads, OpenAI and Slack to n8n Set your Ad Account Id and date range (choose from 'last_7d', 'last_14d', 'last30d') (opcional) Customize the scheduling date and time Requirements Meta Ads (via Facebook Graph API): Documentation pdforge access: Integration guide AI API access (e.g. via OpenAI, Anthropic, Google or Ollama) Slack acces (via OAuth2): Documentation Feel free to contact me via Linkedin, if you have any questions! 👋🏻

This n8n workflow is a fun way to query and search over your credentials on your n8n instance. Good to know Your credentials should remain safe as this workflow does not decrypt or use any decrypted data. Example Usage "Which workflows are using Slack and Google Calendar?" "Which workflows have AI in their name but are not using openAI?" How it works Using the n8n API, it fetches all workflow data on the instance. Workflow data contains references to credentials used so this will be extracted. With some necessary reformatting, the workflows and their credentials metadata are stored to a SQLite database. Next, an AI agent is used with a custom SQL tool that reads the SQLite database created in the previous step. The AI agent is instructed to perform SQL queries against our workflow credential table when asked about credentials by the user. Requirements You'll need an n8n API key. Please note that only workflows will be scoped to your API key. Customising the workflow Add extra table fields to the SQLite database to answer even more complex queries such as: workflow status to differentiate between active and inactive workflows.

AI evaluation in n8n This is a template for n8n's evaluation feature. Evaluation is a technique for getting confidence that your AI workflow performs reliably, by running a test dataset containing different inputs through the workflow. By calculating a metric (score) for each input, you can see where the workflow is performing well and where it isn't. How it works This template shows how to calculate a workflow evaluation metric: whether a category matches the expected one. The workflow takes support tickets and generates a category and priority, which is then compared with the correct answers in the dataset. We use an evaluation trigger to read in our dataset It is wired up in parallel with the regular trigger so that the workflow can be started from either one. More info Once the category is generated by the agent, we check whether it matches the expected one in the dataset Finally we pass this information back to n8n as a metric

Who is this for? This workflow is designed for Customer Success Managers (CSM), sales, support, or marketing teams using HubSpot CRM who want to automate customer engagement tracking when new emails arrive. It’s ideal for businesses looking to streamline CRM updates without manual data entry. Problem Solved / Use Case Manually logging email interactions in HubSpot is time-consuming. This workflow automatically parses incoming emails, checks if the sender exists in HubSpot, and either: Creates a new contact + logs the email as an engagement (if the sender is new). Logs the email as an engagement for an existing contact. What This Workflow Does Triggers when a new email arrives in a connected IMAP inbox. Parses the email using AI (OpenAI) to extract structured data. Searches HubSpot for the sender’s email address. Updates HubSpot: Creates a contact (if missing) and logs the email as an engagement. Or logs the engagement for an existing contact. Setup Configure Email Account: Replace the default IMAP node with your email provider HubSpot Credentials: Add your HubSpot API key in the HubSpot nodes. OpenAI Integration: Ensure your OpenAI API key is set for email parsing. Customization Tips Improve AI Prompt**: Modify the OpenAI prompt to extract specific email data (e.g., customer intent). Add Filters**: Exclude auto-replies or spam by adding a filter node. Extend Functionality**: Use the parsed data to trigger follow-up tasks (e.g., Slack alerts, tickets). Need Help? Contact thomas@pollup.net for workflow modifications or help. Discover my other workflows here

This workflow automatically checks the status of your websites using UptimeRobot API. If any site is down or unstable, it will: Generate a natural-language alert message using GPT-4o Push the message to a LINE group (with funny IT-style encouragement) Log all DOWN status entries into your Supabase database Wait 30 minutes before repeating 🔧 How It Works Schedule Trigger – Runs on a fixed interval (every few minutes). UptimeRobot Node – Fetches website monitor data. Code Node (Filter) – Filters only websites with status 8 (may be down) or 9 (down). IF Node – If any site is down, proceed. LangChain LLM Node – Formats alert with a humorous message using GPT-4o. Line Notify (HTTP Request) – Sends the alert to your LINE group. Loop Over Items – Loops through all monitors. Filter Down (Status = 9) – Selects only “fully down” sites. Supabase Node – Logs these into synlora_uptime_down table. Wait Node – Delays next alert by 30 minutes to avoid spamming. ⚙️ Setup Steps Required: 🔗 UptimeRobot API Key 📲 LINE Channel Access Token and Group ID 🧠 OpenAI Key (GPT-4o Mini) 🗃️ Supabase Project & Table Step-by-step: Go to UptimeRobot → Get API key and ensure monitors are set up. Create a Supabase table with fields: website, status, uptime_id. Create a LINE Messaging API bot, join it to your group, and get: Access Token Group ID (userId or groupId) Add your OpenAI API Key for GPT-4o Mini (or switch to your preferred LLM). Import the workflow JSON into n8n. Set credentials in all necessary nodes. Activate the workflow.

Who is this for? This workflow is for professionals and teams who want to automate LinkedIn message replies with intelligent, human-like responses — without losing control over tone or accuracy. Ideal for founders, sales teams, DevRel, or community managers handling high-volume inbound messages. What problem is this workflow solving? Responding to every LinkedIn message manually is slow and inconsistent. Basic AI bots generate replies without context or nuance. This subworkflow solves both problems by using structured message routing from Notion and profile insights from UniPile to craft smart, context-aware responses. What this workflow does This workflow takes the sender’s message and profile (from LinkedIn Auto Message Router with Request Detection) and references your centralized Notion database of message types. It uses that to either match the message to a known response or generate a new one using OpenAI's GPT model — all while following professional tone guidelines. This is the third workflow in a 3-part automation system: Receives data from LinkedIn Auto Message Router with Request Detection Uses UniPile LinkedIn Profile Lookup Subworkflow to enrich responses based on follower count or org data Example Use Case If a message comes from someone with low reach (e.g., under 1,000 followers), the AI politely deflects a meeting request. If an influencer reaches out, the AI immediately offers a booking link. Your team controls this logic by updating the Notion database — no edits to the workflow required. Setup Connect this workflow as a subworkflow in your router or Slack approval flow Store your Notion API key and database ID in n8n Provide the following parent inputs: message – The LinkedIn message text sender – Name of the sender chatid – Session ID (optional for memory) linkedinprofile – Enriched array with LinkedIn context (follower count, connection info, etc.) Add your preferred AI model credentials (supports OpenAI, Gemini, or Ollama) Optional: Customize system prompt to better match your brand voice How to customize this workflow to your needs Update the Notion schema to include industry-specific categories or actions Change the AI tone (e.g., humorous, more corporate, etc.) Add conditional logic for auto-sending messages without Slack approval Extend to support multiple platforms (e.g., email, X/Twitter, Instagram DMs)