Workflow Templates

Shows how it is possible to use the data of a command line tool which returns JSON. Example shows how: to bring data in flow to use data directly in a node Note that the 'execute command' node is not available on n8n Cloud.

A goal for 2022 is to write 1 thing I do each day. This workflow will automatically remind you on telegram to write something you did yesterday, optionally you can enable the second workflow which will allow you to reply to the message and have it recorded in a google sheet. Note: Make sure to configure your Telegram credentials!

This workflow allows you to create transcription jobs for all your audio and video files stored in AWS S3. AWS S3: This node will retrieve all the files from an S3 bucket you specify. AWS Transcribe: This node will create a transcription job for the files that get returned by the previous node.

Task: Merge two datasets into one based on matching rules Why: A powerful capability of n8n is to easily branch out the workflow in order to process different datasets. Even more powerful is the ability to join them back together with SQL-like joining logic. Main use cases: Appending data sets Keep only new items Keep only existing items

This workflow allows you to receive updates when a new contact is added in Autopilot and add them to a base in Airtable. Autopilot Trigger node: The Autopilot Trigger node will trigger the workflow when a new contact is added in Autopilot. Set node: We use the Set node to ensure that only the data that we set in this node gets passed on to the next nodes in the workflow. Airtable node: This node will store the data coming from the previous node in a table in Airtable.

Auto-post curated remote jobs to Slack with BrowserAct and OpenRouter This workflow acts as an intelligent job board curator for your Slack community. It scrapes multiple sources (e.g., Dice, Indeed), uses AI to filter out spam and low-quality listings based on your specific profile, formats the best jobs into professional posts, and publishes them automatically on a schedule. Target Audience Community managers running job boards, recruiters, and developers building niche job aggregators. How it works Scheduled Fetch: Every week (or your chosen interval), the workflow triggers. Targeting: It reads your configured user profile (Skills, Location, Salary) and list of target job sites. Scraping: BrowserAct scrapes the latest job listings from the specified sites (e.g., Dice, Indeed). AI Curation: An AI Agent (using OpenAI/GPT-4) reviews each job against your profile. It normalizes salaries, scores relevance, and filters out mismatches or low-quality descriptions. Format Content: The AI writes a structured summary for the top matches, including "Why it fits" analysis. Publish: The workflow sends the curated digest to your Slack channel. [Image of AI job curator workflow diagram] How to set up Configure Credentials: Connect your Slack, BrowserAct, and OpenRouter accounts in n8n. Prepare BrowserAct: Ensure you have the Job Board Aggregator template saved in your BrowserAct account. Configure Profile: Open the Add a Resume node and update the variables (Location, Skill, Income, Details, Target_Sites) to match your needs. Configure Slack: Update the Send a message to the Slack channel node with your Slack Channel ID. Activate: Turn on the workflow. [Image of n8n integration architecture] Requirements BrowserAct* account with the *Job Board Aggregator** template. Slack** account (Bot Token). OpenRouter** account (or compatible LLM credentials). How to customize the workflow Add More Sources: Add URLs to the Target_Sites array in the Add a Resume node. Refine Filters: Update the system prompt in the Analyze the jobs agent to be stricter about seniority or specific technologies. Change Frequency: Adjust the Weekly Trigger to run daily if you want more frequent updates. Need Help? How to Find Your BrowserAct API Key & Workflow ID How to Connect n8n to BrowserAct How to Use & Customize BrowserAct Templates Workflow Guidance and Showcase Video How to Automate Your Job Hunt: n8n + AI Resume Matcher & Slack Alerts

How it works • Fetches IT-related tenders from the French BOAMP API (filter: informatique) • Scores each tender with OpenAI (pertinence, budget, stack, GO/NO-GO) • Routes to Supabase as hot (≥75) or archived • Run the SQL from the "Supabase Schema" sticky note in the workflow before use Set up steps • Create a Supabase project and run the SQL from the "Supabase Schema" sticky note - ~5 min • Add OpenAI and Supabase credentials in n8n • Activate the workflow - runs every 4h, or trigger manually/webhook

AI Event Feedback Analyzer with Google Forms, GPT, Slack & Docs Who is this for? Event planners, webinar hosts, conference organizers, and marketers who collect attendee feedback and want instant actionable insights without manual analysis. What problem is this workflow solving? Post-event feedback analysis is slow and manual: Sorting 100s of forms takes hours Missing sentiment patterns or testimonials No real-time team alerts or historical logs This workflow automates sentiment analysis + distribution across Slack and Google Docs. What this workflow does Trigger**: Google Forms → Sheets webhook (works with Typeform too) AI Analysis**: GPT-4o extracts: Sentiment score, key likes/improvements, golden quotes Slack Alert**: "#eventfeedback: 4.2/5 'Loved networking' → Action: More breaks" Google Docs Log**: Appends "{{Event}} Feedback Summary" with bullets + NPS trends Bonus**: 50+ responses → "Avg NPS 4.2 | Top 3 fixes ranked" Setup (3 minutes) Google Forms** → Sheets (native integration) Slack channel + OpenAI API key** (GPT-4o-mini recommended) Google Docs ID** (env var DOCS_ID) Fully configurable—no code changes needed. How to customize to your needs Forms**: Swap Google Forms for Typeform/Webhook AI**: Adjust sentiment thresholds or add custom categories Channels**: Add Teams/Email + multiple Slack rooms Metrics**: Track NPS, CSAT, or custom scores Scale**: Aggregate by event/date for multi-conference orgs ROI: 30% faster feedback loops** 15% NPS uplift** (proven 500+ runs) Zero manual analysis** Need help customizing?: Contact me for consulting and support: LinkedIn / Message Keywords: event management, sentiment analysis, post-event feedback, conference feedback

How It Works Automates daily tenant analytics, churn risk evaluation, and proactive retention by unifying tenant data from multiple sources, applying GPT-4–based risk scoring, detecting early churn indicators, routing high-risk tenants to retention specialists, and initiating targeted engagement campaigns. It retrieves tenant profiles, service requests, and feedback data, performs GPT-4 analysis with detailed churn risk insights, assesses engagement levels, escalates high-risk tenants to dedicated communication teams, delivers personalized loyalty incentives and engagement emails, and updates CRM systems and retention dashboards. Designed for property management companies and SaaS providers. Setup Steps Configure tenant data sources. Connect OpenAI GPT-4 API for risk analysis and churn prediction. Set up Gmail, Slack, and CRM credentials for communication and tracking. Define churn risk thresholds, retention messaging templates, and reward programs. Prerequisites Tenant/customer data source; service request system; feedback collection tool; Use Cases Property management automating tenant retention across portfolios; Customization Adjust churn risk algorithms and thresholds, Benefits Predicts churn before it happens, enables proactive retention

📊 Description Automate personalized LinkedIn outreach at scale using AI and real prospect data. 🤖📧 This workflow pulls leads from Google Sheets, generates human-like LinkedIn messages with Azure OpenAI, and sends them safely via the ConnectSafely LinkedIn API. It intelligently avoids duplicate messages, validates delivery, and updates message status back into your sheet automatically. Perfect for consistent, non-salesy B2B outreach with zero manual effort. What This Template Does ⏰ Triggers automatically on a daily schedule to start LinkedIn outreach. 📄 Fetches prospect details from Google Sheets for processing. 🔁 Loops through prospects in controlled batches to avoid API limits. 🧠 Uses AI to generate personalized LinkedIn messages based on role, company, industry, and activity. ✅ Checks if a message already exists to prevent duplicates. 💾 Saves generated messages back to Google Sheets for tracking. 🔍 Fetches LinkedIn profile data and profile URNs via ConnectSafely. 💬 Sends personalized LinkedIn messages safely using the ConnectSafely API. 📊 Updates Google Sheets with message delivery status and LinkedIn profile links. Key Benefits ✅ Fully automated LinkedIn outreach with no manual copywriting ✅ AI-driven personalization for higher reply rates ✅ Prevents duplicate messages automatically ✅ Centralized tracking inside Google Sheets ✅ Safe LinkedIn messaging using ConnectSafely APIs ✅ Scalable daily outreach without risking account limits Features Scheduled trigger for daily LinkedIn outreach Google Sheets integration for lead management Azure OpenAI (GPT-4o-mini) for AI message generation Batch processing for rate-limit safety Conditional logic to validate message creation ConnectSafely LinkedIn API for profile lookup and message sending Requirements Google Sheets account with prospect data Azure OpenAI credentials (GPT-4o-mini access) ConnectSafely LinkedIn API credentials n8n instance with scheduled workflows enabled Target Audience B2B founders and agency owners doing LinkedIn outreach Sales and lead generation teams Growth marketers running outbound campaigns Automation consultants building LinkedIn workflows

🎵 AI Spotify Playlist Generator (Telegram → Spotify) instantly create a curated Spotify playlist based on a single song recommendation sent via Telegram. This workflow uses an AI Agent to generate similar tracks, creates a new playlist, sends you the link immediately, and then populates the playlist in the background. ✨ Features Instant Feedback: Creates the Spotify playlist and sends the URL back to your Telegram chat immediately, before the AI finishes processing. AI Curation: Uses an AI Agent (via OpenRouter) to act as a "Greatest DJ," generating 25 songs similar to your input. Smart Searching: Automatically searches Spotify for the generated tracks. Error Handling: Includes logic to skip tracks that cannot be found on Spotify. Rate Limiting: Includes a wait loop to ensure Spotify API rate limits are respected during population. 🛠️ Prerequisites To use this workflow, you need: n8n: An active instance of n8n. Spotify Developer Account: You need a Client ID and Client Secret to authenticate the Spotify node. Telegram Bot: A bot token created via @BotFather. OpenRouter Account: An API key for OpenRouter to access the LLM (Language Model). Note: You can easily swap the OpenRouter node for an OpenAI or Anthropic node if preferred. 🔄 How it Works Trigger: You send a message to your Telegram Bot (e.g., "Daft Punk - One More Time"). Create Playlist: The workflow immediately creates a new empty playlist on your Spotify account named with your username and the prompt. Reply: The bot replies to you with the link to the new playlist. AI Generation: The prompt is sent to an AI Agent which generates a JSON list of ~25 similar tracks and artists. Processing: The workflow splits the list into individual items. It loops through every item. It searches Spotify for the specific Track + Artist. If found, it adds the track to the playlist. It waits 1 second between adds to prevent API errors. ⚙️ Setup Instructions Credentials: Set up your Telegram API credentials in the Trigger and Send Message nodes. Set up your Spotify OAuth2 credentials in the Create, Search, and Add Item nodes. Set up your OpenRouter API credentials in the Chat Model node. Model Selection: The template is configured to use openai/gpt-5-nano via OpenRouter. If this model is unavailable to you, simply open the OpenRouter Chat Model node and change the model to openai/gpt-4o or meta-llama/llama-3-70b-instruct. Activate: Save the workflow and click Activate. Open your Telegram bot and send it a song name! 📦 Dependencies n8n-nodes-base.telegramTrigger @n8n/n8n-nodes-langchain.agent n8n-nodes-base.spotify n8n-nodes-base.splitOut n8n-nodes-base.splitInBatches

Track brand visibility on Perplexity and ChatGPT with BrowserAct & OpenRouter Introduction This workflow acts as a "Generative Engine Optimization" (GEO) tracker. It automatically monitors how your brand is being recommended on AI-powered search engines by simulating real user queries on Perplexity and ChatGPT, analyzing the responses for visibility and sentiment, and reporting the findings to Slack. Target Audience Brand managers, SEO specialists, and marketing teams who need to monitor their "share of voice" in AI search results. How it works Scheduling: A Weekly Trigger initiates the workflow to ensure regular monitoring of your brand's presence. Context Setup: A Set node defines the target Brand name and a brief Description of the value proposition. Query Generation: An AI Agent (using OpenRouter/GPT-4o) reads the brand details and generates two distinct search queries: Research Query:** Targeted at Perplexity (e.g., "Top rated tools for X in 2025"). Conversational Query:** Targeted at ChatGPT (e.g., "I need advice on X, what do you recommend?"). Parallel Execution: The workflow splits into two parallel paths to maximize efficiency. Data Extraction: Two separate BrowserAct nodes execute the generated queries on Perplexity and ChatGPT respectively. They scrape the full text of the AI's response. Synchronization: A Merge node waits for both scraping tasks to complete before proceeding. Analysis: A second AI Agent acts as a "GEO Analyst." It compares the scraped answers against your Brand Name to determine if the brand was "Visible" (recommended), "Invisible" (ignored), or "Hallucinated." It also grades the sentiment. Reporting: A Slack node posts a formatted report detailing the visibility status on both platforms. How to set up Configure Credentials: Connect your BrowserAct, OpenRouter, and Slack accounts in n8n. Prepare BrowserAct: Ensure the AI Search Visibility Tracker (Perplexity & ChatGPT) template is saved in your BrowserAct account. Define Brand: Open the Add Brand & Description node. Update the Brand field with your company name and the Description field with your core offering. Select Slack Channel: Open the Send team update node and select the channel where reports should be posted. Requirements BrowserAct Account:* Required for scraping the AI platforms. Template: *AI Search Visibility Tracker (Perplexity & ChatGPT)**. OpenRouter Account:** Required for generating queries and analyzing the sentiment of the results. Slack Account:** Required for receiving the final visibility report. How to customize the workflow Add More Engines: Clone the BrowserAct node to add checks for Google Gemini or Claude, then connect them to the Merge node. Track Competitors: Modify the Add Brand & Description node to input a competitor's name instead of your own to see how AI recommends them. Store History: Add a Google Sheets node before the Slack step to log the "Sentiment Score" and "Visibility Status" over time for trend analysis. Need Help? How to Find Your BrowserAct API Key & Workflow ID How to Connect n8n to BrowserAct How to Use & Customize BrowserAct Templates Workflow Guidance and Showcase Video AI SEO Reporting: Automated Brand Mentions Tracking for Teams