Workflow Templates

Use Case Whenever someone shows interest in your offerings by subscribing to a list in ConvertKit it could be a potential new customer. Typically you need to gather more detailed information about them (data enrichment) and finally update their profile in your CRM system to better manage and nurture your relationship with them. This workflow does this all for you! What this workflow does The workflow runs every time a user is subscribed to a ConvertKit list. It then filters out personal emails, before enriching the email. If the email is attached to a company it enriches the company and upserts it in your Hubspot CRM. Setup Add Clearbit, Hubspot, and ConvertKit credentials. Click on Test workflow. Subscribe to a list on ConvertKit to trigger the workflow. Be aware that you can adapt this workflow to work with your enrichment tool, CRM, and email automation tool of choice.

Purpose This workflow enables you to listen to your recent favorites in very hight quality offline without sacrificing all of your storage. How it works This workflow automatically creates a playlist in Spotify named "Downloads" which periodically gets updated so it always contains only a defined amount of the latest liked songs. This enables only the Downloads playlist to set for automatic downloading and thus free up space on the device. Setup The workflow is ready to go. Just select your Spotify credentials and activate the workflow. In Spotify just enable automatic downloads on the automatically created Downloads folder after the first workflow run. Current limitations This setup currently supports a maximum of 50 songs in the Downloads Playlist. This is due to the paylod limits defined by Spotify encountered in the Get liked songs node. Implementing batching would solve the issue.

Smart Supplier Health Monitor with ScrapeGraphAI Risk Detection and Multi-Channel Alerts 🎯 Target Audience Procurement managers and directors Supply chain risk analysts CFOs and financial controllers Vendor management teams Enterprise risk managers Operations managers Contract administrators Business continuity planners 🚀 Problem Statement Manual supplier monitoring is reactive and time-consuming, often missing early warning signs of financial distress that could disrupt your supply chain. This template solves the challenge of proactive supplier health surveillance by automatically monitoring financial indicators, news sentiment, and market conditions to predict supplier risks before they impact your business operations. 🔧 How it Works This workflow automatically monitors your critical suppliers' financial health using AI-powered web scraping, analyzes multiple risk factors, identifies alternative suppliers when needed, and sends intelligent alerts through multiple channels to ensure your procurement team can act quickly on emerging risks. Key Components Weekly Health Check Scheduler - Automated trigger based on supplier criticality levels Supplier Database Loader - Dynamic supplier portfolio management with risk-based monitoring frequency ScrapeGraphAI Website Analyzer - AI-powered extraction of financial health indicators from company websites Financial News Scraper - Intelligent monitoring of financial news and sentiment analysis Advanced Risk Scorer - Industry-adjusted risk calculation with failure probability modeling Alternative Supplier Finder - Automated identification and ranking of backup suppliers Multi-Channel Alert System - Email, Slack, and API notifications with escalation rules 📊 Risk Analysis Specifications The template performs comprehensive financial health analysis with the following parameters: | Risk Factor | Weight | Score Impact | Description | |-------------|--------|--------------|-------------| | Financial Issues | 40% | +0-24 points | Revenue decline, debt levels, cash flow problems | | Operational Risks | 30% | +0-18 points | Management changes, restructuring, capacity issues | | Market Risks | 20% | +0-12 points | Industry disruption, regulatory changes, competition | | Reputational Risks | 10% | +0-6 points | Negative news, legal issues, public sentiment | Industry Risk Multipliers: Technology: 1.1x (Higher volatility) Manufacturing: 1.0x (Baseline) Energy: 1.2x (Regulatory risks) Financial: 1.3x (Market sensitivity) Logistics: 0.9x (Generally stable) Risk Levels & Actions: Critical Risk**: Score ≥ 75 (CEO/CFO escalation, immediate transition planning) High Risk**: Score ≥ 55 (Procurement director escalation, backup activation) Medium Risk**: Score ≥ 35 (Manager review, increased monitoring) Low Risk**: Score < 35 (Standard monitoring) 🏢 Supplier Management Features | Feature | Critical Suppliers | High Priority | Medium Priority | |---------|-------------------|---------------|-----------------| | Monitoring Frequency | Weekly | Bi-weekly | Monthly | | Risk Threshold | 35+ points | 40+ points | 50+ points | | Alert Recipients | C-Level + Directors | Directors + Managers | Managers only | | Alternative Suppliers | 3+ pre-qualified | 2+ identified | 1+ researched | | Transition Timeline | 24-48 hours | 1-2 weeks | 1-3 months | 🛠️ Setup Instructions Estimated setup time: 25-30 minutes Prerequisites n8n instance with community nodes enabled ScrapeGraphAI API account and credentials Gmail account for email alerts (or alternative email service) Slack workspace with webhook or bot token Supplier database or CRM system API access Basic understanding of procurement processes Step-by-Step Configuration 1. Configure ScrapeGraphAI Credentials Sign up for ScrapeGraphAI API account Navigate to Credentials in your n8n instance Add new ScrapeGraphAI API credentials with your API key Test the connection to ensure proper functionality 2. Set up Email Integration Add Gmail OAuth2 credentials in n8n Configure sender email and authentication Test email delivery with sample message Set up email templates for different risk levels 3. Configure Slack Integration Create Slack webhook URL or bot token Add Slack credentials to n8n Configure target channels for different alert types Customize Slack message formatting and buttons 4. Load Supplier Database Update the "Supplier Database Loader" node with your supplier data Configure supplier categories, contract values, and criticality levels Set monitoring frequencies based on supplier importance Add supplier website URLs and contact information 5. Customize Risk Parameters Adjust industry risk multipliers for your business context Modify risk scoring thresholds based on risk tolerance Configure economic factor adjustments Set failure probability calculation parameters 6. Configure Alternative Supplier Database Populate the alternative supplier database in the "Alternative Supplier Finder" node Add supplier ratings, capacities, and specialties Configure geographic coverage and certification requirements Set suitability scoring parameters 7. Set up Procurement System Integration Configure the procurement system webhook endpoint Add API authentication credentials Test webhook payload delivery Set up automated data synchronization 8. Test and Validate Run test scenarios with sample supplier data Verify ScrapeGraphAI extraction accuracy Check risk scoring calculations and thresholds Confirm all alert channels are working properly Test alternative supplier recommendations 🔄 Workflow Customization Options Modify Risk Analysis Add custom risk indicators specific to your industry Implement sector-specific economic adjustments Configure contract-specific risk factors Add ESG (Environmental, Social, Governance) scoring Extend Data Sources Integrate credit rating agency APIs (Dun & Bradstreet, Experian) Add financial database connections (Bloomberg, Reuters) Include social media sentiment analysis Connect to government regulatory databases Enhance Alternative Supplier Management Add automated supplier qualification workflows Implement dynamic pricing comparison Create supplier performance scorecards Add geographic risk assessment Advanced Analytics Implement predictive failure modeling Add supplier portfolio optimization Create supply chain risk heatmaps Generate automated compliance reports 📈 Use Cases Supply Chain Risk Management**: Proactive monitoring of supplier financial stability Procurement Optimization**: Data-driven supplier selection and management Business Continuity Planning**: Automated backup supplier identification Financial Risk Assessment**: Early warning system for supplier defaults Contract Management**: Risk-based contract renewal and negotiation Vendor Diversification**: Strategic supplier portfolio management 🚨 Important Notes Respect ScrapeGraphAI API rate limits and terms of service Implement appropriate delays between supplier assessments Keep all API credentials secure and rotate them regularly Monitor API usage to manage costs effectively Ensure compliance with data privacy regulations (GDPR, CCPA) Regularly update supplier databases and contact information Review and adjust risk parameters based on market conditions Maintain confidentiality of supplier financial information 🔧 Troubleshooting Common Issues: ScrapeGraphAI extraction errors: Check API key validity and rate limits Email delivery failures: Verify Gmail credentials and permissions Slack notification failures: Check webhook URL and channel permissions False positive alerts: Adjust risk scoring thresholds and industry multipliers Missing supplier data: Verify website URLs and accessibility Alternative supplier errors: Check supplier database completeness Monitoring Best Practices: Set up workflow execution monitoring and error alerts Regularly review and update supplier information Monitor API usage and costs across all integrations Validate risk scoring accuracy with historical data Test disaster recovery and backup procedures Support Resources: ScrapeGraphAI documentation and API reference n8n community forums for workflow assistance Procurement best practices and industry standards Financial risk assessment methodologies Supply chain management resources and tools

Description🔍 This n8n workflow is a complete marketing automation system that connects to your CDP (Customer Data Platform), selects which flows to send, and delivers personalized emails using Brevo. It's modular and extensible — you can also add SMS, push notifications, Telegram messages, or other channels. To build a full marketing automation system, you need four key components: Workflow Automation – using n8n (this workflow) CDP – store and manage user data (e.g., NocoDB, Metabase, Power BI, etc.) Database – track transactions, templates, and send statuses (e.g., NocoDB) BI / Analytics – monitor performance by flows, journeys, and sent events This workflow represents the Workflow Automation layer. You can connect it to your own data stack or use the included example databases (cdp-ecrm, n8n-templates-ecrm, and n8n-transaction-ecrm) to get started quickly. 👤 Who’s it for? Growth & CRM teams managing user engagement flows Ecommerce marketers running time-sensitive email journeys Marketing automation pros using low-code CRM stacks Data teams building custom campaign triggers from CDPs ✅ Features 🔁 Two modular flows: "Insert user_id" and "Sending Email" 🧠 Select flow using flow_id from templates in NocoDB ✏️ Insert user data into n8n-transaction-ecrm with processing status 🔍 Filter duplicate users by user_id to avoid over-sending 📧 Validate email fields and flag disposables 📨 Send personalized emails using Brevo template parameters 📊 Track delivery with sent_result, sent_at, and status updates 🕒 Runs every 30 minutes via schedule trigger 🛠 How to Use Set your flow In the Setup Flow node, change the flow_id to match a row in your n8n-templates-ecrm table. Prepare your tables in NocoDB cdp-ecrm: contains users (user_id, email, first_name, phone_number) n8n-templates-ecrm: contains flows with metadata n8n-transaction-ecrm: stores and updates user send status Configure credentials NocoDB API Token Brevo (Sendinblue) API Key Trigger the flows Run “Insert user_id” manually or on a schedule to prepare users “Sending Email” runs automatically every 30 minutes 📌 Notes Disposable email domains are filtered using regex Status: 0-processing → just inserted 1-sending → ready to send 2-sent → email sent successfully 3-no-email → missing email address 4-disposal-email → disposable or banned email Easily duplicate the "Insert user_id" flow to add more campaigns

:car: Business Value Proposition Accelerates ISO 26262 compliance for automotive/industrial systems by automating safety analysis while maintaining rigorous audit standards. :gear: How It Works graph TD A[Engineer uploadssystem description] --> B(LLM identifies hazards) B --> C(LLM scores risks per ISO 26262) C --> D(Generates mitigation strategies) D --> E(Produces audit-ready reports) :chart_with_upwards_trend: Key Benefits Time 50-70% faster than manual HAZOP/FMEA sessions Instant report generation vs. weeks of documentation Risk Mitigation Pre-validated templates reduce human error Auto-generated traceability simplifies audits :warning: Governance Controls Human-in-the-loop: All LLM outputs require engineer sign-off Version tracking: Full history of modifications Audit mode: Export all decision rationales :computer: Technical Requirements Runs on existing n8n instances Docker deployment (<1hr setup) Integrates with JAMA/DOORS (optional) :wrench: Setup and Usage Prerequisites Docker (Install Guide) Docker Compose (Install Guide) n8n instance (Free Self-Hosted or Cloud - Paid) OpenAI API key (Get Key) Enterprise-ready deployment: When supported by IT infrastructure teams, this solution transforms into a scalable AI safety assistant, providing real-time HARA guidance akin to engineering Co-pilot tools. :arrow_down: Installation and :play_or_pause_button: Running the Workflow For installation procedures and usage of workflow, refer the repository :warning: Validation & Limitations AI-Assisted Analysis Considerations | Advantage | Mitigation Strategy | Implementation Example | |-----------|---------------------|------------------------| | Rapid hazard identification | Human validation layer | Manual review nodes in workflow | | Consistent S/E/C scoring | Rule-based validation | ASIL-D → Redundancy check | | Edge case coverage | Cross-reference with historical data | Integration with incident databases | Critical Validation Steps AI Output Review node in n8n Example: (by code) { "type": "function", "parameters": { "functionCode": "if ($input.item.json.ASIL === 'D' && !$input.item.json.redundancy) throw new Error('ASIL D requires redundancy');" } } Version Control Prompt versions tied to ISO standard editions (e.g., ISO26262:2018-v1.2) Git-tracked changes to ai_models/training_data/ Audit trails Providing a log structure for audit trails Log structure /logs/ └── YYYY-MM-DD/ ├── hazards_approved.log └── hazards_rejected.log

Who is this for? This workflow is designed for travel bloggers, content creators, social media managers, and anyone who wants to transform their travel photos into engaging written narratives. It's perfect for travelers looking to create compelling stories from their photo collections without spending hours crafting content manually, families wanting to document memorable trips, and digital nomads who need to produce travel content efficiently. What problem is this workflow solving? Converting travel photos into engaging stories is time-consuming and requires both creative writing skills and the ability to analyze visual content meaningfully. This workflow solves the challenge of: Transforming visual memories into compelling written narratives Organizing photos chronologically to create logical story flow Generating professional-quality travel content without writing expertise Analyzing photo content to extract meaningful themes and emotions Creating day-by-day structured narratives from unorganized photo collections Reducing the time spent on manual content creation for travel documentation What this workflow does This AI-powered photo storyteller takes your travel photos and automatically generates immersive, first-person travel narratives. The workflow: Accepts multiple photos through a webhook endpoint Uses OpenAI Vision API (GPT-4o) to analyze each photo's content, emotions, and themes Automatically organizes photos chronologically by date and timestamp Groups photos by travel days and extracts daily themes Leverages GPT-4.1 (minimum required) to craft engaging, first-person travel stories with creative day titles Generates structured narratives with sensory details, cultural observations, and emotional insights Outputs JSON formatted content ready for formatting Creates day-by-day story structure with memorable moments and reflective conclusions Setup Required Credentials: OpenAI API key configured in n8n for both Vision Analysis and Story Generation nodes Ensure you have sufficient OpenAI credits for image analysis and text generation Webhook Configuration: The workflow creates a webhook endpoint at /tripteller-upload Configure your photo upload interface to POST photos array to this endpoint Photos should be sent as base64 encoded data with filename and metadata Photo Requirements: Supported formats: Standard image formats (JPEG, PNG, etc.) Photos should include timestamp metadata for chronological organization Caution Do not upload all photos at once. Start with a small number of photos, like 5 at a time. How to customize this workflow to your needs Story Style Customization: Modify the system prompt in the "Generate Travel Story" node to adjust writing tone (nostalgic, adventurous, poetic, etc.) Customize the story structure by editing the output format requirements Add specific cultural or geographical context prompts for location-specific storytelling Photo Analysis Enhancement: Adjust the Vision Analysis node prompt to focus on specific elements (architecture, food, people, landscapes) Modify the grouping logic in the "Group Photos by Day" node for different time-based organization Add location extraction from EXIF data for geographical context Output Format Adjustment: Customize the final response structure in the "Format Final Response" node Add integration with publishing platforms (blog APIs, social media, etc.) Include additional metadata like location tags, travel duration, or trip statistics Performance Optimization: Adjust the execution timeout based on your typical photo volume Modify the parallel processing approach for large photo collections Add progress tracking for longer processing workflows

A n8n workflow designed to shorten URLs using Dub.co API. How it works: It shortens a url using Dub.co API, with the ability to use custom domains and projects. It updates the current shortened url if the slug has been already used. Estimated Time: Around 15 minutes. Requirements: A Dub.co account. Configuration: Configure the "API Auth" node to add your Dub.co API key, project slug, and the long URL. There some extras that you're able to configure too. You will be able to do that by clicking the "API Auth" node and filling the fields. Detailed Instructions: Sticky notes within the workflow provide extensive setup information and guidance. Keywords: n8n workflow, dub.co, dub.sh, url shortener, short urls, short links

This template is an error handler that will log n8n workflow errors to a Monday.com board for troubleshooting and tracking. Prerequisites Monday account and Monday credential Create a board on Monday for error logging, with the following columns and types: Timestamp (text) Error Message (text) Stack Trace (long text) Determine the column IDs using Monday's instructions Setup Edit the Monday nodes to use your credential Edit the node labeled CREATE ERROR ITEM to point to your error log board and group name Edit the column IDs in the "Column Values" field of the UPDATE node to match the IDs of the fields on your error log board To trigger error logging, select this automation as the error workflow on any automation For more detailed logging, add Stop and Error nodes in your workflow to send specific error messages to your board.

This workflow creates/updates ClickUp tasks when Notion database pages are created/updated. All fields in the Notion database are mapped to a ClickUp property. Notion database will require setup before the workflow can be used. See the list of fields available in the setup below. Prerequisites Notion account and Notion credentials. ClickUp account and ClickUp credentials. How it works When a new database page is created in Notion, the workflow creates a new task in ClickUp with all required fields. The new ClickUp task's ID is saved in the Notion database page's "ClickUp ID" field. Then, when the database page is updated in Notion, the workflow updates the specific ClickUp task identified by the "ClickUp ID" field in Notion. Setup This workflow requires that you set up a Notion database. To do so, follow the steps below: In Notion, create a new database. Add the following columns to the database: Task name (renamed from "Name") Status (with type "Select" with the following options: "to do", "in progress", "review", "revision", "complete") Deadline (with type "Date") ClickUp ID (with type "Text") Add any other fields you require. Share the database to n8n. By default, the workflow will fill all the fields provided above, except for any other additional fields you add.

Who is this template for? This template is designed for teams who need to automate data retrieval from SharePoint lists using n8n. It is ideal for users who want to authenticate via OAuth and then use the token to access SharePoint API endpoints, pulling in list data directly into n8n. How it works The template first generates an OAuth token using the Microsoft OAuth API. This token is then used to authenticate requests to the SharePoint List API, allowing the workflow to fetch data from a specified SharePoint list. By following the n8n workflow, the user can configure the necessary credentials and endpoints to automate SharePoint data access securely. Setup steps Step 1: Replace {tenant_id}, {client_id}, and {client_secret} with your Azure AD details for OAuth authentication. Step 2: Specify the SharePoint list API endpoint in the template (under "SharePoint List Fetch" node). Step 3: Configure the SharePoint list URL and make adjustments for specific data fields if necessary.

Effortlessly optimize your workflow by automatically save all files you are receiving on Telegram to a Google Drive Folder. How it works Retrieve a message sent to your Telegram Bot containing a file Upload the file to your Google Drive Folder Set up Steps Create a Telegram Account and a Telegram Bot and connect your Telegram Bot to n8n by following the official n8n instructions Create a Google Drive Folder Connect your Google Drive with n8n following the official n8n instructions Set the right folder in the Google Drive node Use case examples Backup and Recovery Cross-Platform Access File Organization and Management File Collaboration and Sharing Storage Space Management

📊 Real-Time Flight Data Analytics Bot with Dynamic Chart Generation via Telegram 🚀 Template Overview This advanced n8n workflow creates an intelligent Telegram bot that transforms raw CSV flight data into stunning, interactive visualizations. Users can generate professional charts on-demand through a conversational interface, making data analytics accessible to anyone via messaging. Key Innovation: Combines real-time data processing, Chart.js visualization engine, and Telegram's messaging platform to deliver instant business intelligence insights. 🎯 What This Template Does Transform your flight booking data into actionable insights with four powerful visualization types: 📈 Bar Charts**: Top 10 busiest airlines by flight volume 🥧 Pie Charts**: Flight duration distribution (Short/Medium/Long-haul) 🍩 Doughnut Charts**: Price range segmentation with average pricing 📊 Line Charts**: Price trend analysis across flight durations Each chart includes auto-generated insights, percentages, and key business metrics delivered instantly to users' phones. 🏗️ Technical Architecture Core Components Telegram Webhook Trigger: Captures user interactions and button clicks Smart Routing Engine: Conditional logic for command detection and chart selection CSV Data Pipeline: File reading → parsing → JSON transformation Chart Generation Engine: JavaScript-powered data processing with Chart.js Image Rendering Service: QuickChart API for high-quality PNG generation Response Delivery: Binary image transmission back to Telegram Data Flow Architecture User Input → Command Detection → CSV Processing → Data Aggregation → Chart Configuration → Image Generation → Telegram Delivery 🛠️ Setup Requirements Prerequisites n8n instance** (self-hosted or cloud) Telegram Bot Token** from @BotFather CSV dataset** with flight information Internet connectivity** for QuickChart API Dataset Source This template uses the Airlines Flights Data dataset from GitHub: 🔗 Dataset: Airlines Flights Data by Rohit Grewal Required Data Schema Your CSV file should contain these columns: airline,flight,source_city,departure_time,arrival_time,duration,price,class,destination_city,stops File Structure /data/ └── flights.csv (download from GitHub dataset above) ⚙️ Configuration Steps 1. Telegram Bot Setup Create a new bot via @BotFather on Telegram Copy your bot token Configure the Telegram Trigger node with your token Set webhook URL in your n8n instance 2. Data Preparation Download the dataset from Airlines Flights Data Upload the CSV file to /data/flights.csv in your n8n instance Ensure UTF-8 encoding Verify column headers match the dataset schema Test file accessibility from n8n 3. Workflow Activation Import the workflow JSON Configure all Telegram nodes with your bot token Test the /start command Activate the workflow 🔧 Technical Implementation Details Chart Generation Process Bar Chart Logic: // Aggregate airline counts const airlineCounts = {}; flights.forEach(flight => { const airline = flight.airline || 'Unknown'; airlineCounts[airline] = (airlineCounts[airline] || 0) + 1; }); // Generate Chart.js configuration const chartConfig = { type: 'bar', data: { labels, datasets }, options: { responsive: true, plugins: {...} } }; Dynamic Color Schemes: Bar Charts: Professional blue gradient palette Pie Charts: Duration-based color coding (light→dark blue) Doughnut Charts: Price-tier specific colors (green→purple) Line Charts: Trend-focused red gradient with smooth curves Performance Optimizations Efficient Data Processing: Single-pass aggregations with O(n) complexity Smart Caching: QuickChart handles image caching automatically Minimal Memory Usage: Stream processing for large datasets Error Handling: Graceful fallbacks for missing data fields Advanced Features Auto-Generated Insights: Statistical calculations (percentages, averages, totals) Trend analysis and pattern detection Business intelligence summaries Contextual recommendations User Experience Enhancements: Reply keyboards for easy navigation Visual progress indicators Error recovery mechanisms Mobile-optimized chart dimensions (800x600px) 📈 Use Cases & Business Applications Airlines & Travel Companies Fleet Analysis**: Monitor airline performance and market share Pricing Strategy**: Analyze competitor pricing across routes Operational Insights**: Track duration patterns and efficiency Data Analytics Teams Self-Service BI**: Enable non-technical users to generate reports Mobile Dashboards**: Access insights anywhere via Telegram Rapid Prototyping**: Quick data exploration without complex tools Business Intelligence Executive Reporting**: Instant charts for presentations Market Research**: Compare industry trends and benchmarks Performance Monitoring**: Track KPIs in real-time 🎨 Customization Options Adding New Chart Types Create new Switch condition Add corresponding data processing node Configure Chart.js options Update user interface menu Data Source Extensions Replace CSV with database connections Add real-time API integrations Implement data refresh mechanisms Support multiple file formats Visual Customizations // Custom color palette backgroundColor: ['#your-colors'], // Advanced styling borderRadius: 8, borderSkipped: false, // Animation effects animation: { duration: 2000, easing: 'easeInOutQuart' } 🔒 Security & Best Practices Data Protection Validate CSV input format Sanitize user inputs Implement rate limiting Secure file access permissions Error Handling Graceful degradation for API failures User-friendly error messages Automatic retry mechanisms Comprehensive logging 📊 Expected Outputs Sample Generated Insights "✈️ Vistara leads with 350+ flights, capturing 23.4% market share" "📈 Long-haul flights dominate at 61.1% of total bookings" "💰 Budget category (₹0-10K) represents 47.5% of all bookings" "📊 Average prices peak at ₹14K for 6-8 hour duration flights" Performance Metrics Response Time**: <3 seconds for chart generation Image Quality**: 800x600px high-resolution PNG Data Capacity**: Handles 10K+ records efficiently Concurrent Users**: Scales with n8n instance capacity 🚀 Getting Started Download the workflow JSON Import into your n8n instance Configure Telegram bot credentials Upload your flight data CSV Test with /start command Deploy and share with your team 💡 Pro Tips Data Quality**: Clean data produces better insights Mobile First**: Charts are optimized for mobile viewing Batch Processing**: Handles large datasets efficiently Extensible Design**: Easy to add new visualization types Ready to transform your data into actionable insights? Import this template and start generating professional charts in minutes! 🚀