Automated job applications & status tracking with LinkedIn, Indeed & Google Sheets
Apply to jobs automatically from Google Sheets with status tracking Who's it for Job seekers who want to streamline their application process, save time on repetitive tasks, and never miss following up on applications. Perfect for anyone managing multiple job applications across different platforms. What it does This workflow automatically applies to jobs from a Google Sheet, tracks application status, and keeps you updated with notifications. It handles the entire application lifecycle from submission to status monitoring. Key features: Reads job listings from Google Sheets with filtering by priority and status Automatically applies to jobs on LinkedIn, Indeed, and other platforms Updates application status in real-time Checks application status every 2 days and notifies you of changes Sends email notifications for successful applications and status updates Prevents duplicate applications and manages rate limiting How it works The workflow runs on two main schedules: Daily Application Process (9 AM, weekdays): Reads your job list from Google Sheets Filters for jobs marked as "Not Applied" with Medium/High priority Processes each job individually to prevent rate limiting Applies to jobs using platform-specific APIs (LinkedIn, Indeed, etc.) Updates the sheet with application status and reference ID Sends confirmation email for each application Status Monitoring (Every 2 days at 10 AM): Checks all jobs with "Applied" status Queries job platforms for application status updates Updates the sheet if status has changed Sends notification emails for status changes (interviews, rejections, etc.) Requirements Google account with Google Sheets access Gmail account for notifications Resume stored online (Google Drive, Dropbox, etc.) API access to job platforms (LinkedIn, Indeed) - optional for basic version n8n instance (self-hosted or cloud) How to set up Step 1: Create Your Job Tracking Sheet Create a Google Sheet with these exact column headers: | JobID | Company | Position | Status | AppliedDate | LastChecked | ApplicationID | Notes | Job_URL | Priority | |--------|---------|----------|--------|--------------|--------------|----------------|-------|---------|----------| | JOB001 | Google | Software Engineer | Not Applied | | | | | https://careers.google.com/jobs/123 | High | | JOB002 | Microsoft | Product Manager | Not Applied | | | | | https://careers.microsoft.com/jobs/456 | Medium | Column explanations: Job_ID: Unique identifier (JOB001, JOB002, etc.) Company: Company name Position: Job title Status: Not Applied, Applied, Under Review, Interview Scheduled, Rejected, Offer Applied_Date: Auto-filled when application is submitted Last_Checked: Auto-updated during status checks Application_ID: Platform reference ID (auto-generated) Notes: Additional information or application notes Job_URL: Direct link to job posting Priority: High, Medium, Low (Low priority jobs are skipped) Step 2: Configure Google Sheets Access In n8n, go to Credentials → Add Credential Select Google Sheets OAuth2 API Follow the OAuth setup process to authorize n8n Test the connection with your job tracking sheet Step 3: Set Up Gmail Notifications Add another credential for Gmail OAuth2 API Authorize n8n to send emails from your Gmail account Test by sending a sample email Step 4: Update Workflow Configuration In the "Set Configuration" node, update these values: spreadsheetId: Your Google Sheet ID (found in the URL) resumeUrl: Direct link to your resume (make sure it's publicly accessible) yourEmail: Your email address for notifications coverLetterTemplate: Customize your cover letter template Step 5: Customize Application Logic For basic version (no API access): The workflow includes placeholder HTTP requests that you can replace with actual job platform integrations. For advanced version (with API access): Replace LinkedIn/Indeed HTTP nodes with actual API calls Add your API credentials to n8n's credential store Update the platform detection logic for additional job boards Step 6: Test and Activate Add 1-2 test jobs to your sheet with "Not Applied" status Run the workflow manually to test Check that the sheet gets updated and you receive notifications Activate the workflow to run automatically How to customize the workflow Adding New Job Platforms Update Platform Detection: Modify the "Check Platform Type" node to recognize new job board URLs Add New Application Node: Create HTTP request nodes for new platforms Update Status Checking: Add status check logic for the new platform Customizing Application Strategy Rate Limiting: Add "Wait" nodes between applications (recommended: 5-10 minutes) Application Timing: Modify the cron schedule to apply during optimal hours Priority Filtering: Adjust the filter conditions to match your criteria Multiple Resumes: Use conditional logic to select different resumes based on job type Enhanced Notifications Slack Integration: Replace Gmail nodes with Slack for team notifications Discord Webhooks: Send updates to Discord channels SMS Notifications: Use Twilio for urgent status updates Dashboard Updates: Connect to Notion, Airtable, or other productivity tools Advanced Features AI-Powered Personalization: Use OpenAI to generate custom cover letters Job Scoring: Implement scoring logic based on job requirements vs. your skills Interview Scheduling: Auto-schedule interviews when status changes Follow-up Automation: Send follow-up emails after specific time periods Important Notes Platform Compliance Always respect rate limits to avoid being blocked Follow each platform's Terms of Service Use official APIs when available instead of web scraping Don't spam job boards with excessive applications Data Privacy Store credentials securely using n8n's credential store Don't hardcode API keys or personal information in nodes Regularly review and clean up old application data Ensure your resume link is secure but accessible Quality Control Start with a small number of jobs to test the workflow Review application success rates and adjust strategy Monitor for errors and set up proper error handling Keep your job list updated and remove expired postings This workflow transforms job searching from a manual, time-consuming process into an automated system that maximizes your application efficiency while maintaining quality and compliance.
By VipinWTranslate text from English to German
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By Harshil AgrawalAutomate AI video ad generation with Google Veo 3, Gemini, and Airtable
This n8n template from Intuz provides a complete and automated solution for transforming a static product image and a creative idea into a dynamic, AI-generated video ad. Using Google's state-of-the-art Veo 3 model, this workflow manages the entire creative process from concept to a final, downloadable video file. Who's this workflow for? E-commerce Brands & Marketers Advertising Agencies Social Media Content Creators Product Managers How it works Submit a Creative Brief: The workflow starts when a user submits a creative idea via a simple web form (e.g., "A Pepsi can exploding into a vibrant disco party"). Upload a Product Image: The user is then prompted to upload a corresponding image (e.g., a high-quality photo of the Pepsi can). Log the Project in Airtable: The idea and the uploaded image are saved to an Airtable base, which acts as the central tracking system for all video generation projects. AI Creative Analysis: Google Gemini analyzes both the user's text prompt and the uploaded image. It acts as an "AI Creative Director," generating a detailed video brief that reinterprets the static image according to the user's creative vision. Generate Video with Veo 3: The detailed creative brief is sent to Google's Veo 3 AI video generation model. The workflow initiates a long-running task to create the video. Retrieve the Final Video: After a brief waiting period, the workflow polls the Veo 3 API to retrieve the finished video, converts it into a binary file, and makes it available for download directly from the n8n execution log. Key Requirements to Use This Template n8n Instance & Required Nodes: An active n8n account (Cloud or self-hosted). This workflow uses the official n8n LangChain integration (@n8n/n8n-nodes-langchain). If you are using a self-hosted version of n8n, please ensure this package is installed. Google Cloud Account: A Google Cloud Project with the Vertex AI API enabled. You must have access to both the Gemini and Veo 3 models within your project. You will need a Gemini API Key and a Google OAuth2 Credential configured for the Vertex AI scope. Airtable Account: An Airtable base with a table set up to track the video projects. It should have columns for Image Prompt, Image (Attachment), Video (Attachment/URL), and Status. Setup Instructions Airtable Configuration (Crucial): In the Create a record, Get a record, and Update record nodes, connect your Airtable credentials and update the Base ID and Table ID to match your setup. In the Uploading Image in Airtable (HTTP Request) node, you must edit the URL and the "Authorization" header to include your Base ID, Table ID, and Personal Access Token. Google AI Configuration (Gemini & Veo): In the Analyze image (Google Gemini) node, select your Gemini API credentials. In both the Generate Video Veo 3 and Get the the Video (HTTP Request) nodes: You must replace [Project ID] and [Location] in the URLs with your own Google Cloud Project ID and region (e.g., us-central1). Select your Google OAuth2 credentials for authentication. Customize Video Parameters (Optional): In the Parse Request (Code) node, you can modify the JavaScript code to change video generation settings like aspectRatio, durationSeconds, and resolution. Execute the Workflow: Activate the workflow. Open the Form URL from the Prompt your Idea node to start the process. Sample Videos Connect with us Website: https://www.intuz.com/services Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz For Custom Workflow Automation Click here- Get Started
By Intuz Create, update, and get an object from Bubble
This workflow allows you to create, update, and get an object from Bubble. Bubble node: This node will create a new object of the type Doc in Bubble. If you want to create an object with a different type, use that type instead. Bubble1 node: This node will update the object that we created using the previous node. Bubble2 node: This node will retrieve the information of the object that we created earlier.
By Harshil Agrawal💬 Daily WhatsApp group summarizer – GPT-4o, Google Sheets & Evolution API
Hey! I’m Amanda ❤️ I made this little workflow with care for people like you who are part of busy WhatsApp groups and want a simple way to keep track of everything. It connects to Evolution API, collects all the group messages throughout the day, stores them in Google Sheets, and uses GPT-4o to generate a daily summary. The summary is saved as a document in Google Drive — ready to read, share, or archive. It’s perfect for teams, communities, classes, or any group that talks a lot but doesn’t want to miss important info. --- What it does Collects WhatsApp group messages using Evolution API Saves the messages in Google Sheets (organized by date) Creates a clean, structured summary using GPT-4o Saves the summary in Google Drive as a doc Can run daily at a set time (fully automated) --- How to set it up Connect your Evolution API and provide the group ID Use this Google Sheets template Connect Google Sheets and Google Drive in n8n Add your OpenAI API key (Optional) Adjust the AI prompt for a custom tone or structure --- ✅ Works on both n8n Cloud and Self-hosted 🔐 All credentials stay safe in n8n --- Want to customize this for your group or business? ❤️ Buy Workflows: https://iloveflows.gumroad.com 💬 Hire My Services: +5517991557874 (WhatsApp) --- --- Tradução em Português (pt-br): Oi! Eu sou a Amanda 💬 Se você participa de grupos movimentados no WhatsApp e quer transformar tudo isso em resumos diários organizadinhos, esse fluxo foi feito com todo carinho pra você! Ele conecta com a API da Evolution, coleta as mensagens trocadas em grupos, armazena tudo no Google Sheets, e no fim do dia gera um resumo completo usando GPT-4o. Esse resumo é salvo como documento no seu Google Drive — pronto pra ser lido, compartilhado ou arquivado. Ideal pra equipes, comunidades, projetos colaborativos ou até grupos de estudos 📚 --- O que o fluxo faz Monitora e salva conversas do grupo no Google Sheets Gera resumos diários com IA (formato estruturado e pronto pra leitura) Salva o resumo como documento no seu Google Drive Funciona com qualquer grupo conectado à sua conta Evolution Pode ser agendado pra rodar automaticamente todo fim de dia --- Como configurar Conecte sua API Evolution e informe o ID do grupo Use essa planilha modelo para armazenar as mensagens Conecte sua conta do Google (Sheets + Drive) Adicione sua chave da OpenAI Personalize o prompt do resumo (opcional) --- ✅ Compatível com n8n Cloud e Auto-hospedado 🔐 Tudo seguro, simples e sem complicações --- Quer adaptar esse fluxo pro seu sistema? ❤️ Buy Workflows: https://iloveflows.gumroad.com 💬 Hire My Services: +5517991557874 (WhatsApp)
By Amanda BenksArchive Spotify's discover weekly playlist
This workflow will archive your Spotify Discover Weekly playlist to an archive playlist named "Discover Weekly Archive" which you must create yourself. If you want to change the name of the archive playlist, you can edit value2 in the "Find Archive Playlist" node. It is configured to run at 8am on Mondays, a conservative value in case you forgot to set your GENERIC_TIMEZONE environment variable (see the docs here). Special thanks to erin2722 for creating the Spotify node and harshil1712 for help with the workflow logic. To use this workflow, you'll need to: Create then select your credentials in each Spotify node Create the archive playlist yourself Optionally, you may choose to: Edit the archive playlist name in the "Find Archive Playlist" node Adjust the Cron node with an earlier time if you know GENERIC_TIMEZONE is set Setup an error workflow like this one to be notified if anything goes wrong
By TreyCreate consistent AI characters with Google Nano Banana & upscaling via Kie.ai
Google NanoBanana Model Image Editor for Consistent AI Influencer Creation with Kie AI Image Generation & Enhancement Workflow This n8n template demonstrates how to use Kie.ai's powerful image generation models to create and enhance images using AI, with automated story creation, image upscaling, and organized file management through Google Drive and Sheets. Use cases include: AI-powered content creation for social media, automated story visualization with consistent characters, marketing material generation, and high-quality image enhancement workflows. Good to know The workflow uses Kie.ai's google/nano-banana-edit model for image generation and nano-banana-upscale for 4x image enhancement Images are automatically organized in Google Drive with timestamped folders Progress is tracked in Google Sheets with status updates throughout the process The workflow includes face enhancement during upscaling for better portrait results All generated content is automatically saved and organized for easy access How it works Project Setup: Creates a timestamped folder structure in Google Drive and initializes a Google Sheet for tracking Story Generation: Uses OpenAI GPT-4 to create detailed prompts for image generation based on predefined templates Image Creation: Sends the AI-generated prompt along with 5 reference images to Kie.ai's nano-banana-edit model Status Monitoring: Polls the Kie.ai API to monitor task completion with automatic retry logic Image Enhancement: Upscales the generated image 4x using nano-banana-upscale with face enhancement File Management: Downloads, uploads, and organizes all generated content in the appropriate Google Drive folders Progress Tracking: Updates Google Sheets with status information and image URLs throughout the entire process Key Features Automated Story Creation: AI-powered prompt generation for consistent, cinematic image creation Multi-Stage Processing: Image generation followed by intelligent upscaling Smart Organization: Automatic folder creation with timestamps and file management Progress Tracking: Real-time status updates in Google Sheets Error Handling: Built-in retry logic and failure state management Face Enhancement: Specialized enhancement for portrait images during upscaling How to use Manual Trigger: The workflow starts with a manual trigger (easily replaceable with webhooks, forms, or scheduled triggers) Automatic Processing: Once triggered, the entire pipeline runs automatically Monitor Progress: Check the Google Sheet for real-time status updates Access Results: Find your generated and enhanced images in the organized Google Drive folders Requirements Kie.ai Account: For AI image generation and upscaling services OpenAI API: For intelligent prompt generation (GPT-4 mini) Google Drive: For file storage and organization Google Sheets: For progress tracking and status monitoring Customizing this workflow This workflow is highly adaptable for various use cases: Content Creation: Modify prompts for different styles (fashion, product photography, architectural visualization) Batch Processing: Add loops to process multiple prompts or reference images Social Media: Integrate with social platforms for automatic posting E-commerce: Adapt for product visualization and marketing materials Storytelling: Create sequential images for visual narratives or storyboards The modular design makes it easy to add additional processing steps, change AI models, or integrate with other services as needed. Workflow Components Folder Management: Dynamic folder creation with timestamp naming AI Integration: OpenAI for prompts, Kie.ai for image processing File Processing: Binary handling, URL management, and format conversion Status Tracking: Multi-stage progress monitoring with Google Sheets Error Handling: Comprehensive retry and failure management systems
By Muhammad Farooq IqbalPersonalized tour package recommendations with GPT-4o, Pinecone & Lovable UI
Personalized Tour Package Recommendations via n8n + Pinecone + Lovable UI I've created an intelligent Travel Itinerary Planner that connects a Lovable front-end UI with a smart backend powered by n8n, Pinecone, and OpenAI to deliver personalized tour packages based on natural language queries. What It Does Users type in their travel destination and duration (e.g., "Paris 5 days trip" or "Bali Trip for 7 Days, would love water sports, adventures and trekking included, also some historical monuments") through a Lovable UI. This triggers a webhook in n8n, which processes the request, searches vectorized tour data in Pinecone, and generates a personalized itinerary using OpenAI’s GPT. The results are then structured and sent back to the frontend UI for display in an interactive, reorderable format. Workflow Architecture Lovable UI ➝ Webhook ➝ Tour Recommendation Agent ➝ Vector Search ➝ OpenAI Response ➝ Structured Output ➝ Response to Lovable Tools & Components Used Webhook Acts as the entry point between the Lovable frontend and n8n. Captures the user query (destination, duration) and forwards it into the workflow. OpenAI Chat Model To interpret the user query. To generate a user-friendly, structured tour package from the matched results. Simple Memory Keeps chat state and context for follow-up queries (extendable for future features like multi-step planning or saved itineraries). Question Answering with Vector Store Searches vector embeddings of pre-loaded tour data. Finds the most relevant tour packages by comparing query embeddings. Pinecone Vector Store Stores tour packages and activity data in vectorized format. Enables fast and scalable semantic search across destinations, themes (e.g., "adventure", "cultural"), and duration. OpenAI Embeddings Embeds all tour and activity documents stored in Pinecone. Converts input user queries into embedding vectors for semantic search. Structured Output Parser Parses the final OpenAI-generated response into a consistent, frontend-consumable JSON format. Frontend (Lovable UI) User types in destination or their travel package needs in the Tour Search. Lovable queries the n8n workflow. Displays beautifully structured, editable itineraries. How to Set It Up Webhook Setup in n8n Create a POST webhook node. Set Webhook URL and connect it with Lovable frontend. Pinecone & Embeddings Convert your static tour package documents (PDFs, JSON, CSV, etc.) into embeddings using OpenAI. Store the embeddings in a Pinecone namespace (e.g., kuala-lumpur-3-days). Configure “Answer with Vector Store” Tool Connect the tool to your Pinecone instance and pass query embedding for matching. Connect to OpenAI Chat Use the GPT model to process query + context from Pinecone to generate an engaging itinerary description. Optionally chain a second model to format it into UI-consumable output. Output Parser & Return Use Structured Output Parser to parse the response and pass it to Respond to Webhook node for UI display. Ideal Use Cases Smart itinerary planning for OTAs or DMCs Personalized travel recommendations in chatbots or apps Travel advisors and agents automating package generation Benefits Highly relevant, contextual travel suggestions Natural query understanding via OpenAI Seamless frontend-backend integration via Webhook If you’re building personalized experiences for travelers using AI, give this approach a try! Let me know if you’d like the JSON for this workflow or help setting up the Pinecone data pipeline.
By Mohan GopalReceive updates for the position of the ISS and push it to a Firbase
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By Harshil AgrawalEvaluations metric: answer similarity
This n8n template demonstrates how to calculate the evaluation metric "Similarity" which in this scenario, measures the consistency of the agent. The scoring approach is adapted from the open-source evaluations project RAGAS and you can see the source here https://github.com/explodinggradients/ragas/blob/main/ragas/src/ragas/metrics/answersimilarity.py How it works This evaluation works best where questions are close-ended or about facts where the answer can have little to no deviation. For our scoring, we generate embeddings for both the AI's response and ground truth and calculate the cosine similarity between them. A high score indicates LLM consistency with expected results whereas a low score could signal model hallucination. Requirements n8n version 1.94+ Check out this Google Sheet for a sample data https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing
By JimleukLearn JavaScript data processing with code node: filtering, analysis & export examples
Overview A comprehensive educational workflow that demonstrates practical JavaScript usage in n8n's Code node through real-world business scenarios. Perfect for learning data manipulation, transformation, and automation patterns that you can immediately apply to client projects. What This Template Teaches: Data Filtering & Transformation - Filter employees by age, calculate bonuses, format contact information Statistical Analysis - Generate team statistics, averages, role distributions, and KPIs Multi-Format Export - Create CSV files, email lists, and API-ready payloads from raw data n8n Best Practices - Proper JSON handling, return formats, and data flow patterns How It Works: Manual Trigger starts the workflow with sample employee data Set Sample Data provides realistic business data (employees with roles, salaries, ages) Three Code Node Examples process the same data differently: Filter & Transform: Creates adult employee list with calculated bonuses Calculate Stats: Generates comprehensive team analytics and reports Format for Export: Prepares data for external systems (APIs, emails, CSV) Key Learning Points: Access input data using items[0].json.propertyName Return proper n8n format with [{ json: data }] structure Use JSON.parse() for string-to-object conversion Apply JavaScript array methods (filter, map, reduce) for data processing Handle multiple output scenarios and data aggregation Perfect For: n8n beginners learning Code node fundamentals Developers transitioning to n8n automation Client demos showing data processing capabilities Team training and onboarding sessions Foundation for building custom business automation workflows Business Use Cases: Transform this template for lead qualification, customer segmentation, report generation, data enrichment, and API integrations. Each Code node pattern can be adapted for different industries and automation needs.
By David OlusolaBuild a RAG knowledge chatbot with OpenAI, Google Drive, and Supabase
🚀 Build Your Own Knowledge Chatbot Using Google Drive Create a smart chatbot that answers questions using your Google Drive PDFs—perfect for support, internal docs, education, or research. 🛠️ Quick Setup Guide Step 1: Prerequisites n8n instance (cloud or self-hosted) Google Drive account (with PDFs) Supabase account (vector database) OpenAI API key PostgreSQL database (for chat memory) else remove the node Step 2: Supabase Setup Create supabase account (its free) Create a project Copy the sql and paste it in supabase sql editor SQL -- Enable the pgvector extension to work with embedding vectors create extension vector; -- Create a table to store your documents create table documents ( id bigserial primary key, content text, -- corresponds to Document.pageContent metadata jsonb, -- corresponds to Document.metadata embedding vector(1536) -- 1536 works for OpenAI embeddings, change if needed ); -- Create a function to search for documents create function match_documents ( query_embedding vector(1536), match_count int default null, filter jsonb DEFAULT '{}' ) returns table ( id bigint, content text, metadata jsonb, similarity float ) language plpgsql as $$ variableconflict usecolumn begin return query select id, content, metadata, 1 - (documents.embedding <=> query_embedding) as similarity from documents where metadata @> filter order by documents.embedding <=> query_embedding limit match_count; end; $$; Step 3: Import & Configure n8n Workflow Import this template into n8n Add credentials: OpenAI API key Google Drive OAuth2 Supabase URL & service key PostgreSQL connection Set your Google Drive folder ID in triggers Step 4: Test & Use Add a PDF to your Drive folder → check Supabase for new entries Start the workflow and chat → ask questions about your documents. "What can you help me with?" Multi-turn chat → context is maintained per user ⚡ Features Auto-syncs new/updated PDFs from Google Drive Extracts, chunks, and vectorizes text Finds relevant info and answers questions Maintains chat history per user 📝 Troubleshooting Check folder permissions & IDs if no docs found Verify API keys & Supabase setup for errors Ensure PostgreSQL is connected for chat memory Tags: RAG, Chatbot, Google Drive, Supabase, OpenAI, n8n Setup Time: ~20 minutes
By Babish Shrestha