Workflow Templates

How it works This comprehensive recruitment automation workflow transforms your hiring process from manual screening to intelligent candidate management. The system begins by automatically collecting CVs from multiple job boards and career platforms, immediately parsing each submission using advanced AI technology to extract key information including skills, experience levels, educational background, and career progression patterns. Once parsed, the workflow employs predictive scoring algorithms that evaluate each candidate against your specific job requirements and company culture criteria. This multi-dimensional analysis considers technical skills alignment, experience relevance, cultural fit indicators, and career trajectory patterns to generate compatibility scores with remarkable accuracy. The system then seamlessly transitions qualified candidates into automated interview scheduling, coordinating availability across hiring managers, team members, and candidates while optimizing for timezone considerations and calendar conflicts. Finally, successful candidates enter a personalized onboarding workflow that adapts to their role, department, and experience level, ensuring smooth integration into your organization. Target audience and problem solved This workflow is designed for HR departments, talent acquisition teams, and growing companies struggling with time-intensive recruitment processes. It specifically addresses the challenges of manual CV screening, subjective candidate evaluation, scheduling conflicts, and inconsistent onboarding experiences. Organizations processing high volumes of applications or seeking to eliminate recruitment bias while maintaining quality standards will benefit most from this automation. Set up steps Prerequisites: Ensure you have API access to your chosen AI parsing service (OpenAI, Affinda, or equivalent), active accounts on target job boards, and administrative access to your calendar and ATS systems. Configure job board integrations: Connect your LinkedIn Recruiter, Indeed, and Glassdoor accounts using their respective APIs. Set up webhook endpoints to automatically capture new CV submissions and configure filtering criteria based on job titles, locations, and basic qualifications. Establish AI parsing service: Choose and configure your CV analysis provider (OpenAI for natural language processing, Affinda for specialized CV parsing, or alternative services). Set up API credentials and define extraction templates for skills, experience, education, and custom fields relevant to your industry. Integrate calendar systems: Connect Google Calendar, Outlook, or your preferred scheduling platform. Configure availability windows for all hiring team members, set interview duration templates, and establish buffer times between meetings. Synchronize ATS platform: Link your Applicant Tracking System (Workday, BambooHR, Greenhouse, etc.) to ensure seamless candidate data flow. Map workflow fields to your ATS schema and establish status update triggers. Connect interview tools: Integrate video conferencing platforms (Zoom, Microsoft Teams, Google Meet) for automatic meeting room creation and invitation distribution. Configure recording settings and waiting room preferences. Link HRMS for onboarding: Connect your Human Resource Management System to trigger personalized onboarding sequences based on role type, department, and seniority level. Key Features 🧠 Advanced CV analysis**: Leverages machine learning to automatically extract and categorize skills, experience, education, certifications, and career progression patterns with 95% accuracy 📊 Multi-criteria scoring**: Implements customizable evaluation matrices considering technical skills, soft skills, experience relevance, cultural fit indicators, and growth potential 📅 Intelligent scheduling**: Automatically coordinates complex interview schedules across multiple stakeholders, considering time zones, availability preferences, and interview type requirements 🎯 Precise candidate matching**: Generates compatibility percentages based on job requirements, team dynamics, and long-term career alignment factors ⚡ Accelerated recruitment cycle**: Reduces time-to-hire by up to 60% through automated screening, intelligent prioritization, and streamlined communication workflows 👥 Collaborative evaluation**: Enables structured feedback collection from multiple interviewers with standardized scoring rubrics and consensus-building tools 📱 Enhanced candidate experience**: Provides mobile-optimized interfaces for application tracking, interview scheduling, and communication throughout the recruitment journey 🔄 Continuous optimization**: Automatically tracks and analyzes recruitment metrics to continuously improve scoring algorithms and process efficiency Customization options The workflow offers extensive customization capabilities including adjustable scoring weights for different criteria, industry-specific skill taxonomies, custom interview formats, and role-based onboarding paths. Organizations can configure approval workflows, set up custom notification templates, and establish specific integration parameters to match their unique recruitment processes and company culture. This automation solution transforms recruitment from a time-intensive manual process into a strategic, data-driven system that improves both hiring quality and candidate experience while significantly reducing administrative overhead.

Workflow Purpose This workflow periodically checks a service's availability and sends an SMS notification if the service is down. High-Level Steps Schedule Trigger: The workflow is triggered at a specified interval, such as every minute. HTTP Request: An HTTP request is sent to the URL of the service being monitored. If: The HTTP status code of the response is checked. If the status code is 200 (OK), the workflow ends. If the status code is not 200, indicating a potential issue, an SMS notification is sent using Twilio. Setup Setting up this workflow is relatively straightforward and should only take a few minutes: Create a new n8n workflow. Add the nodes: Schedule Trigger, HTTP Request, If, and Twilio. Configure the nodes: Schedule Trigger: Specify the desired interval. HTTP Request: Enter the URL of the service to be monitored. If: Set the condition to check for a status code other than 200. Twilio: Enter the Twilio account credentials and the phone numbers for sending and receiving the SMS notification. Connect the nodes: Connect the nodes as shown in the workflow diagram. Activate the workflow: Save the workflow and activate it. Additional Notes The workflow can be customized by changing the interval, the URL, the Twilio credentials, and the SMS message. This workflow is a simple example, and more complex workflows can be created to meet specific needs.

📰 This AI-powered agent performs real-time sentiment analysis on Tesla (TSLA) news to support trading decisions. It aggregates headlines from 5 trusted sources and uses DeepSeek Chat to classify sentiment and generate structured summaries. This tool is a critical sub-agent in the broader Tesla Quant Trading AI Agent system. ⚠️ Not standalone — this agent is designed to be executed by the Tesla Quant Trading AI Agent. ⚙️ Requires: DeepSeek Chat API Key 🔌 Workflow Role This tool processes Tesla-related news and produces output like: { "sentiment": "bullish", "summary": "Tesla stock rallied today after strong delivery numbers and Cybertruck updates. Analysts remain optimistic.", "topHeadlines": [ "Tesla beats Q2 delivery forecast – Yahoo Finance", "Cybertruck ramps up in Texas – Electrek", "Berlin Gigafactory expands battery production – CleanTechnica" ] } Its output feeds directly into the master trading agent’s final trade report. 📰 News Sources Used This agent collects real-time headlines from: Google News (filtered by “Tesla” or “TSLA”) Yahoo Finance (TSLA-specific feed) Electrek (Tesla archive) CleanTechnica (Tesla sustainability news) TeslaNorth (app/product release updates) These five tools are always queried together to ensure market-wide signal coverage. 🤖 What the Agent Does Pulls headlines from all 5 Tesla-specific RSS feeds Uses DeepSeek Chat to: Analyze narrative tone (bullish / bearish / neutral) Identify macro/financial drivers Generate a 2–3 sentence summary Return top 3–5 headlines Outputs structured JSON for downstream use 🛠️ Setup Instructions 1. Install & Name Import this file and name it: Tesla_News_and_Sentiment_Analyst_Tool 2. Add DeepSeek API Credentials Go to: Credentials → Add New → DeepSeek API Save as: DeepSeek account 3. Internet Access Required Ensure RSS feeds can fetch live headlines Works best with a cloud-hosted n8n instance or tunnel-enabled local install 4. Must Be Triggered by Parent Triggered via Execute Workflow by the Tesla Quant Trading AI Agent Requires these inputs: message: optional query context sessionId: passed to maintain short-term memory across executions 🧠 Agent Architecture | Node Name | Function | | ---------------------------------- | ------------------------------------------------ | | DeepSeek Chat Model | Performs AI-based sentiment analysis | | Tesla News and Sentiment Analyst | Combines results, formats output in strict JSON | | Simple Memory | Stores session-level context (short-term memory) | | 5x RSS nodes | Aggregate Tesla news from trusted media outlets | 📌 Sticky Notes Included 🟢 Trigger from Parent Workflow – Executed only by main TSLA agent 🟠 News Feeds Overview – Lists and explains each of the 5 feeds 🧠 DeepSeek Chat Notes – Describes LLM behavior and parsing role 🔵 Short-Term Memory – Buffers sentiment context during user session 📘 Sentiment Analyst Agent – Summarizes key responsibilities 📎 Licensing & Attribution © 2025 Treasurium Capital Limited Company This architecture, workflow structure, and prompt design are licensed for educational and operational use only. Commercial resale or rebranding prohibited without authorization. 🔗 Creator: Don Jayamaha 🔗 Templates: https://n8n.io/creators/don-the-gem-dealer/ 🚀 Power your TSLA trading with AI-driven sentiment—built with DeepSeek Chat and 5 trusted news sources. This tool is required by the Tesla Quant Trading AI Agent.

WhatsApp Flows Encrypted Data Exchange Workflow Summary This workflow enables secure end-to-end encrypted data exchange with WhatsApp Flows for interactive applications inside Whatsapp. It implements the WhatsApp Business Encryption protocol using RSA for key exchange and AES-GCM for payload encryption, providing a secure channel for sensitive data transmission while interfacing with WhatsApp's Business API. This follows the official WhatsApp Business Encryption specifications to establish an encrypted GraphQL-powered data exchange channel between your business and the WhatsApp consumer client. How It Works Encryption Flow Webhook Reception: Receives encrypted data from WhatsApp containing: encrypted_flow_data: The AES-encrypted payload encrypted_aes_key: The RSA-encrypted AES key initial_vector: Initialization vector for AES decryption Decryption Process: The workflow decrypts the AES key using an RSA private key Then uses this AES key to decrypt the payload data The inverted IV is used for response encryption Data Processing: The workflow parses the decrypted JSON data Routes requests based on the screen parameter. Response Generation: Generates appropriate response data based on the request type Encrypts the response using the same AES key and inverted IV Returns the base64-encoded encrypted response Key Components Webhook Endpoint**: Entry point for encrypted WhatsApp requests Decryption Pipeline**: RSA and AES decryption components Business Logic Router**: Screen-based routing for different functionality Encryption Pipeline**: Secure response encryption How to Use Deploy the Workflow: Import the workflow JSON into your n8n instance Set Up WhatsApp Integration: Configure your WhatsApp Business API to send requests to your n8n webhook URL Ensure your WhatsApp integration is set up to encrypt data using the public key pair of the private key used in this workflow Test the Flow: Send an encrypted test message from WhatsApp to verify connectivity Check if appointment data is being retrieved correctly Validate that seat selection is functioning as expected Production Use: Monitor the workflow performance in production Set up error notification if needed Requirements Authentication Keys RSA Private Key: Required for decrypting the AES key (included in the workflow) WhatsApp Business Public Key: Must be registered with the WhatsApp Business API PostgreSQL Credentials: For accessing appointment data from the database WhatsApp Business Encryption Setup As specified in the WhatsApp Business Encryption documentation: Generate a 2048-bit RSA Key Pair: The private key remains with your business (used in this workflow) The public key is shared with WhatsApp Register the Public Key with WhatsApp: Use the WhatsApp Cloud API to register your public key Set up the public key using the /v17.0/{WhatsApp-Business-Account-ID}/whatsapp_business_encryption endpoint Key Registration API Call: POST /v17.0/{WhatsApp-Business-Account-ID}/whatsapp_business_encryption { "business_public_key": "YOUR_PUBLIC_KEY" } Verification: Verify your public key is registered using a GET request to the same endpoint Ensure the key status is "active"

This template extracts all customers from shopify using GraphQL and the shopify admin API and sync them into a Baserow table. Setup Notes Update the Endpoint in GraphQL node to reflect your Shopify store. In Baserow create a shopify database with a customer table in Baserow. Create columns in the Baserow customer table for first_name, last_name, and email. It takes about 1 second per row to insert.

This n8n template allows you to instantly generate QR codes from any text or URL by simply sending a webhook request. It's a versatile tool for creating dynamic QR codes for various purposes, from marketing campaigns to event registrations, directly integrated into your automated workflows. 🔧 How it works Receive Data Webhook: This node acts as the entry point for the workflow. It listens for incoming POST requests and expects a JSON body with a data property containing the text or URL you want to encode into the QR code. Generate QR Code: This node makes an HTTP GET request to the QR Server API (api.qrserver.com) to generate the QR code image. The content from your webhook is passed as the data parameter to the API. Respond with QR Code: This node sends the response from the QR Server API back to the service that initiated the webhook. The QR Server API directly returns the image data, so your webhook response will be the QR code image itself. 👤 Who is it for? This workflow is ideal for: Marketers: Generate QR codes for product links, event registrations, or promotional materials on the fly. Developers: Integrate QR code generation into applications, websites, or internal tools. Event Organizers: Create dynamic QR codes for ticketing, information access, or check-ins. Businesses: Streamline processes requiring physical-to-digital transitions, like menu access or contact sharing. Automation Enthusiasts: Add QR code generation capabilities to any workflow. 📑 Data Structure When you trigger the webhook, send a POST request with a JSON body structured as follows: { "data": "https://www.yourwebsite.com/your-specific-page-or-text-to-encode" } The workflow will return the QR code image directly in the response. ⚙️ Setup Instructions Import Workflow: In your n8n editor, click "Import from JSON" and paste the provided workflow JSON. Configure Webhook Path: Double-click the Receive Data Webhook node. In the 'Path' field, set a unique and descriptive path (e.g., /generate-qr). Customize QR Code (Optional): Double-click the Generate QR Code node. You can adjust the size parameter in the URL (e.g., size=200x200 for a larger QR code) or add other parameters supported by the QR Server API (e.g., bgcolor, color, qzone). Activate Workflow: Save and activate the workflow. 📝 Tips Handling the Image Output: Since the QR Server API directly returns the image, the webhook response will be the image data. Depending on your use case, you might want to: Save to File/Cloud: Insert a node (e.g., Write Binary File, Amazon S3, Google Drive) after Generate QR Code to save the image to a file system or cloud storage. Embed in HTML/Email: If you're building an HTML response or sending an email, you might need to convert the image data to a Base64 string or provide a URL to a saved image. Error Handling: Enhance workflow robustness by adding an Error Trigger node. This allows you to catch any issues during QR code generation and set up notifications or logging. Dynamic Size/Color: You can extend the Receive Data Webhook to accept parameters for size, color, or bgcolor in the incoming JSON. Then, dynamically pass these to the url of the Generate QR Code node to create highly customizable QR codes. Input Validation: For more advanced use cases, you could add a Function node after the webhook to validate the incoming data to ensure it's in a valid format (e.g., a URL).

Task Read a list of customers from a GoogleSheet and create them in Shopify using Shopify's Admin API (GraphQL). Why ? Generate test users for development stores. Migrate customers from other platforms. Easy intro to Shopify's GraphQL API. Setup Setting up Google Sheets access Follow the instructions in the N8N Docs for granting Oauth2 access to Google services. You'll need to grant API access to Google Sheets and Google Drive (to list available sheets). Setting up Shopify access Shopify's Admin API uses 'Header Auth' with a key of X-Shopify-Access-Token and a value of your shopify access token which starts with shpat_ . How to generate a Shopify Access Token To generate a Shopify Access Token create an app, grant the app the necessary scopes, then generate a token. From inside a store do the following : click Settings (nav link) click Apps and sales channels (nav link) click Develop Apps (button) click Create App (button) give the app a name click configure Admin API Scopes (button) at a minimum grant read_customers and write_customers scope. Grant additional scopes if you plan on accessing other parts of the API. click save To generate the token click install app (button) click install on the dialog that pops up (button) click 'reveal token once' (button) copy the token into a password vault or somewhere secure. Template Updates To test this out you'll need to make the following changes : 1) Create a header credential where the key is X-Shopify-Access-Token and the value is your Shopify Access Token (it starts with shpat_ 2) In the GraphQL node change the endpoint URL to your store. Something like https://{your store goes here}.myshopify.com/admin/api/2025-04/graphql.json Google Sheet Structure Columns can be in any order, because the rows will be mapped to fields in a json object. N8N will treat the first row in the sheet as a column name, so at a minimum use the column names below in row 1 of your sheet. first_name : Any string last_name : Any string email : Valid email mobile_phone : International mobile phone format with no spaces eg. +61414708406 (Shopify will reject anything else). Example CSV "first_name","last_name","email","mobile_phone" "Bob","Smith","bob@example.com","+61414999999"

Automating Company Data Enrichment and HubSpot Integration Use Case This automation enriches company data based on email domain and LinkedIn profile, calculates an ICP (Ideal Customer Profile) score, and updates the corresponding company record in HubSpot. It’s ideal for onboarding, qualification, and CRM enrichment. What This Automation Does Input Parameters Contact email**: Used to derive the company domain. Company domain**: Primary web domain of the company. Company LinkedIn* *(optional): LinkedIn URL for enrichment accuracy. Airtop Profile (connected to LinkedIn)**: An authenticated Airtop Profile. What It Outputs Full company profile (name, tagline, website, headquarters) Employee count ICP score based on AI/tech profile, scale, agency type, and location Updates/creates record in HubSpot with all enriched attributes How It Works Input Validation: Filters out non-corporate domains like Gmail, Yahoo, or .edu. Enrichment Trigger: Launches Airtop workflows to extract and analyze data from LinkedIn and calculate the ICP score. Data Mapping: Compiles structured fields including: Overview, location (city, state, country) Company website and domain LinkedIn URL, employee count ICP score HubSpot Sync: Sends all the enriched fields to the designated HubSpot object for upsertion. Setup Requirements Airtop API Key Airtop Profile with active LinkedIn authentication HubSpot integration enabled for object updates Next Steps Use in Webforms**: Trigger this on signup to auto-populate CRM records. Enrich Manually Entered Contacts**: Use with list-based workflows for batch enrichment. Sync to Other CRMs**: Replace HubSpot step with Salesforce, Pipedrive, etc. for flexible integration. Read more about comapny data enrichment

What this template does This workflow uses the Amadeus API, every day to check for bargain flights for an itinerary and price target of your choice. It then automatically emails you once it found a match. Setup Create an api account on https://developers.amadeus.com/ In Amadeus Flight Search, connect to Oauth2 API: -- Grant Type - Client Credentials -- Access Token URL - https://test.api.amadeus.com/v1/security/oauth2/token -- Client ID/Secret - from your account Set your details in Gmail Set your desired Origin/Destination airports in FromTo Set the dates ahead you wish to search in Get Dates (default is 7 days and 14 days) Set the price target in Under Price How to test it After completing the setup steps above, just hit 'Test workflow'!

Gmail AI Email Manager - Setup Guide 🎯 Workflow Overview This workflow will create an intelligent Gmail email manager that can: Monitor incoming emails via webhook Analyze email content using AI Categorize emails automatically Generate smart responses Take actions based on email content Send notifications for important emails 📋 Pre-Setup Checklist Before we build the workflow, let me gather the necessary information and validate our approach. Phase 1: Discovery & Planning [ ] Search for Gmail nodes [ ] Find AI analysis nodes [ ] Identify webhook trigger options [ ] Check notification nodes Phase 2: Configuration Requirements [ ] Gmail API credentials [ ] AI service (OpenAI/Claude) API key [ ] Webhook URL setup [ ] Email classification rules 🔧 Setup Instructions Step 1: Gmail API Setup Go to Google Cloud Console Create new project or select existing Enable Gmail API Create OAuth 2.0 credentials Add authorized redirect URI: https://your-n8n-instance.com/rest/oauth2-credential/callback Step 2: AI Service Setup Choose one of the following: OpenAI**: Get API key from platform.openai.com Claude**: Get API key from console.anthropic.com Local AI**: Set up Ollama or similar Step 3: n8n Credentials Gmail OAuth2: Add client ID, secret, and scopes AI Service: Add API key Webhook: Configure webhook URL Gmail AI Email Manager - Setup Guide 🔧 Quick Setup Checklist 1. Google Cloud Console [ ] Enable Gmail API [ ] Create OAuth2 credentials [ ] Add redirect URI: https://your-n8n.com/rest/oauth2-credential/callback [ ] Set up Gmail push notifications with Pub/Sub 2. API Keys [ ] Get OpenAI API key from platform.openai.com [ ] Create Google Sheets for logging (optional) 3. n8n Credentials [ ] Gmail OAuth2: Client ID, Secret, Scopes: gmail.readonly,gmail.modify,gmail.compose [ ] OpenAI API: Your API key 4. Gmail Labels (Create these) [ ] URGENT (red) [ ] IMPORTANT (orange) [ ] PROMOTIONAL (purple) [ ] PERSONAL (green) [ ] WORK (blue) [ ] SPAM (gray) 5. Update Workflow Values [ ] High Priority Alert: Change notification email [ ] Spreadsheet Log: Update sheet ID (if using) [ ] Webhook: Copy URL after saving workflow 6. Test [ ] Save & activate workflow [ ] Send test email to Gmail [ ] Check execution log [ ] Verify auto-categorization works That's it! Your AI email manager is ready! 🚀

This n8n workflow demonstrates how to automate indexing of images to build a object-based image search. By utilising a Detr-Resnet-50 Object Classification model, we can identify objects within an image and store these associations in Elasticsearch along with a reference to the image. How it works An image is imported into the workflow via HTTP request node. The image is then sent to Cloudflare's Worker AI API where the service runs the image through the Detr-Resnet-50 object classification model. The API returns the object associations with their positions in the image, labels and confidence score of the classification. Confidence scores of less the 0.9 are discarded for brevity. The image's URL and its associations are then index in an ElasticSearch server ready for searching. Requirements A Cloudflare account with Workers AI enabled to access the object classification model. An ElasticSearch instance to store the image url and related associations. Extending this workflow Further enrich your indexed data with additional attributes or metrics relevant to your users. Use a vectorstore to provide similarity search over the images.

Who's it for Content creators, social media managers, and marketing teams who want to automatically extract the most engaging clips from long-form YouTube videos and identify content with high viral potential. What it does This workflow analyzes any YouTube video using Vizard AI's clipping technology and automatically generates up to 8 short clips with viral score ratings. It then filters for the highest-scoring clips (9/10 or above) and posts them to a designated Slack channel for team review and distribution. How it works Video submission: Enter a YouTube URL through a user-friendly form AI analysis: Submits the video to Vizard AI for automated clipping and viral score analysis Smart polling: Waits for processing completion and retrieves results Quality filtering: Only surfaces clips with viral scores of 9/10 or higher Team notification: Posts results to Slack with clip titles, scores, and download links Requirements Vizard AI API credentials (sign up at vizard.ai) Slack workspace with OAuth app configured How to set up Configure Vizard AI credentials: Add your Vizard AI API key to the HTTP Request nodes Set up Slack integration: Configure the Slack OAuth2 credentials and select your target channel Customize filtering: Adjust the viral score threshold in the filter node (currently set to 9/10) Test the workflow: Submit a test YouTube URL to ensure everything works properly How to customize the workflow Adjust clip quantity**: Modify the maxClipNumber parameter (currently 8) in the initial API request Change viral score threshold**: Update the filter condition to match your quality standards Extend with automation**: Connect to social media posting tools or caption generation workflows for full automation Add scheduling**: Integrate with webhook triggers, scheduled triggers, or RSS feeds for batch processing videos