Workflow Templates

This n8n workflow automates the enrichment of a company list by discovering and extracting each company’s official LinkedIn URL using Bright Data’s search capabilities and Google Gemini AI for HTML parsing and result interpretation. Who is this template for? This workflow is ideal for sales, business development, and data research professionals who need to collect official LinkedIn company profiles for multiple organizations, starting from a list of company names in Google Sheets. It’s especially useful for teams who want to automate sourcing LinkedIn URLs, enrich their prospect database, or validate company data at scale. How it works Manual Trigger: The workflow is started manually (useful for controlled batch runs and testing). Read Company Names: Company names are loaded from a specified Google Sheets table. Loop Over Each Company: Each company is processed one-by-one: A custom Google Search URL is generated for each name. A Bright Data Web Unlocker request is sent to fetch Google search results for “site:linkedin.com [company name]”. Parse LinkedIn Profile URL Using AI: Google Gemini (or your specified LLM) analyzes the fetched search page and extracts the most likely official LinkedIn company profile. Result Handling: If a profile is found, it’s stored in the results. If not, an empty result is created, but you can add custom logic (notifications, retries, etc.). Batch Data Enrichment: All found company URLs are bundled into a single request for further enrichment from a Bright Data dataset. Export: The workflow appends the final, structured data for each company to another sheet in your Google Sheets file. Setup instructions 1. Replace API Keys: Insert your Bright Data API key in these nodes: Bright Data Web Request - Google Search for Company LinkedIn URL HTTP Request - Post API call to Bright Data Snapshot Progress HTTP Request - Getting data from Bright Data 2. Connect Google Sheets: Set up your Google Sheets credentials and specify the sheet for reading input and writing output. 3. Customize Output Structure: Adjust the Python code node (see sticky note in the template) if you want to include additional or fewer fields in your output. 4. Adjust for Scale or Error Handling: You can modify the logic for “not found” results (e.g., to notify a Slack channel or retry failed companies). 5. Run the Workflow: Start manually, monitor the run, and check your Google Sheet for results. Customization guidance Change Input/Output Sheets: Update the sheet names or columns if your source/target spreadsheet has a different structure. Use Another AI Model: Replace the Google Gemini node with another LLM node if preferred. Integrate Alerts: Add Slack or email nodes to notify your team when a LinkedIn profile is not found or when the process is complete.

Overview Advanced AI-powered stock analysis workflow that combines multi-timeframe technical analysis with real-time news sentiment to generate actionable BUY/SELL/HOLD recommendations. Uses sophisticated algorithms to process price data, news sentiment, and market context for informed trading decisions. Core Features Multi-Timeframe Technical Analysis 4-Hour Charts** - Intraday trend analysis and entry timing Daily Charts** - Primary trend identification and key levels Weekly Charts** - Long-term context and major trend direction Moving Average Analysis** - 5, 10, and 20-period trend indicators Support/Resistance Levels** - Dynamic price level identification Volume Analysis** - Trading activity and momentum confirmation AI-Powered News Sentiment Analysis Real-Time News Processing** - Latest market-moving headlines Sentiment Scoring** - Numerical sentiment rating (-1 to +1 scale) Impact Assessment** - News relevance to stock performance Multi-Source Analysis** - Comprehensive news coverage evaluation Context-Aware Processing** - Financial market-specific sentiment analysis Intelligent Recommendation Engine Professional Trading Logic** - Multi-timeframe alignment analysis Risk/Reward Calculations** - Minimum 1:2 ratio requirements Entry/Exit Price Targets** - Specific actionable price levels Stop-Loss Recommendations** - Risk management guidelines Confidence Scoring** - Recommendation strength assessment Technical Capabilities Data Sources & APIs TwelveData API** - Professional-grade price and volume data NewsAPI Integration** - Comprehensive news coverage Perplexity AI** - Additional sentiment context and analysis Chart-Img API** - Visual chart generation for analysis Real-Time Processing** - Live market data integration AI Models & Analysis GPT-4 Integration** - Advanced natural language processing Custom Sentiment Engine** - Financial market-tuned sentiment analysis Multi-Model Approach** - Cross-validation of recommendations Algorithmic Trading Logic** - Professional-grade decision frameworks Visual Analysis Tools Interactive Charts** - TradingView-style chart generation Technical Indicators** - Visual representation of analysis Dark Theme Support** - Professional trading interface Multiple Timeframes** - Comprehensive visual analysis Use Cases & Applications Individual Traders Day Trading Signals** - Short-term entry/exit recommendations Swing Trading Analysis** - Multi-day position guidance Risk Management** - Stop-loss and position sizing advice Market Timing** - Optimal entry point identification Investment Research Due Diligence** - Comprehensive stock analysis Sentiment Monitoring** - News impact assessment Technical Screening** - Multi-criteria stock evaluation Portfolio Optimization** - Individual stock recommendations Automated Trading Systems Signal Generation** - Systematic buy/sell/hold alerts Risk Controls** - Automated stop-loss calculations Multi-Asset Analysis** - Scalable across stock universe Backtesting Support** - Historical recommendation validation Financial Advisors & Analysts Client Reporting** - Professional analysis documentation Research Automation** - Streamlined analysis workflow Decision Support** - Data-driven recommendation framework Market Commentary** - AI-generated insights and rationale Key Benefits Professional-Grade Analysis Institutional Quality** - Bank-level analytical frameworks Multi-Dimensional** - Technical + fundamental + sentiment analysis Real-Time Processing** - Live market data integration Objective Decision Making** - Removes emotional bias from analysis Time Efficiency Instant Analysis** - Seconds vs hours of manual research Automated Processing** - Continuous market monitoring Scalable Operations** - Analyze multiple stocks simultaneously 24/7 Availability** - Round-the-clock market analysis Risk Management Built-in Stop Losses** - Automatic risk level calculation Position Sizing** - Risk-appropriate recommendation sizing Multi-Timeframe Validation** - Reduces false signals Conservative Approach** - Defaults to HOLD when uncertain Setup Requirements API Keys Needed TwelveData API - Free tier available at twelvedata.com NewsAPI Key - Free tier available at newsapi.org OpenAI API - For GPT-4 analysis capabilities Perplexity API - Additional sentiment analysis Chart-Img API - Optional chart visualization (chart-img.com) Configuration Steps API Integration - Add your API keys to respective nodes Symbol Format - Supports company names or stock symbols Risk Parameters - Customize stop-loss and target calculations Notification Setup - Configure alert delivery methods Testing & Validation - Verify API connections and data flow Advanced Features Natural Language Processing Company Name Recognition** - Automatic symbol conversion Context Understanding** - Market-aware news interpretation Multi-Language Support** - Global news source analysis Entity Extraction** - Key information identification Error Handling & Reliability API Failure Recovery** - Graceful degradation strategies Data Validation** - Input/output quality checks Rate Limit Management** - Automatic throttling controls Backup Data Sources** - Redundant information feeds Customization Options Timeframe Selection** - Adjustable analysis periods Risk Tolerance** - Configurable risk/reward ratios Sentiment Weighting** - Balance technical vs fundamental analysis Alert Thresholds** - Custom trigger conditions Important Disclaimers This tool provides educational and informational analysis only. All trading decisions should: Consider your personal risk tolerance and financial situation Be validated with additional research and professional advice Account for market volatility and potential losses Follow proper risk management principles Performance Optimization Speed Enhancements Parallel Processing** - Simultaneous data retrieval Caching Strategies** - Reduced API call frequency Efficient Algorithms** - Optimized calculation methods Memory Management** - Scalable resource usage Accuracy Improvements Multi-Source Validation** - Cross-reference data points Historical Backtesting** - Performance validation Continuous Learning** - Algorithm refinement Market Adaptation** - Evolving analysis criteria Transform your investment research with AI-powered analysis that combines the speed of automation with the depth of professional-grade financial analysis.

This n8n template lets you summarize team member activity on Slack for the past week and generates a report. For remote teams, chat is a crucial communication tool to ensure work gets done but with so many conversations happening at once and in multiple threads, ideas, information and decisions usually live in the moment and get lost just as quickly - and all together forgotten by the weekend! Using this template, this doesn't have to be the case. Have AI crawl through last week's activity, summarize all threads and generate a casual and snappy report to bring the team back into focus for the current week. A project manager's dream! How it works A scheduled trigger is set to run every Monday at 6am to gather all team channel messages within the last week. Each message thread are grouped by user and data mined for replies. Combined, an AI analyses the raw messages to pull out interesting observations and highlights. The summarized threads of the user are then combined together and passed to another AI agent to generate a higher level overview of their week. These are referred to as the individual reports. Next, all individual reports are summarized together into a team weekly report. This allows understanding of group and similar activities. Finally, the team weekly report is posted back to the channel. The timing is important as it should be the first message of the week and ready for the team to glance over coffee. How to use Ideally works best per project and where most of the comms happens on a single channel. Avoid combining channels and instead duplicate this workflow for more channels. You may need to filter for specific team members if you want specific team updates. Customise the report to suit your organisation, team or the channel. You may prefer to be more formal if clients or external stakeholders are also present. Requirements Slack for chat platform Gemini for LLM (or switch for other models) Customising this workflow If the slack channel is busy enough already, consider posting the final report to email. Pull in project metrics to include in your report. As extra context, it may be interesting to tie the messages to production performance. Use an AI Agent to query for knowledgebase or tickets relevant to the messages. This may be useful for attaching links or references to add context. Channel not so busy or way too busy for 1 week? Play with the scheduled trigger and set an interval which works for your team.

Boost Sales with Automated Magento 2 Product and Coupon Notifications This n8n workflow automatically posts new Magento products & coupons to Telegram while preventing duplicates. Key benefits: ✅ Increase conversions with time-sensitive alerts (creates urgency) ✅ Reduce missed opportunities with 24/7 monitoring ✅ Improve customer engagement through rich media posts ✅ Save hours per week by automating manual posting Why This Works: Triggers impulse buys with real-time notifications Eliminates human error in duplicate posting Scales effortlessly as your catalog grows Provides analytics through database tracking Perfect for e-commerce stores wanting to: Announce new arrivals instantly Promote limited-time offers effectively Maintain consistent social presence Track performance through MySQL This workflow automatically: ✅ Detects new products AND coupons in Magento ✅ Prevents duplicate postings with MySQL tracking ✅ Posts rich formatted alerts to Telegram ✅ Runs on a customizable schedule ✨ Key Features For Products: Product name, price, and image Direct store link Media gallery support For Coupons: Coupon code and status Usage limits (times used/available) Active/inactive status indicator Core System: 🔒 MySQL duplicate prevention⏰ 1-hour schedule (customizable)📱 Telegram notifications with Markdown 🛠️ Configuration Guide Database Setup CREATE TABLE IF NOT EXISTS posted_items (item_id INT PRIMARY KEY, item_type ENUM('product', 'coupon') NOT NULL, item_value VARCHAR(255), posted BOOLEAN DEFAULT FALSE, created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP); Required Credentials Magento API (HTTP Header Auth) MySQL Database Telegram Bot Sticky Notes `❗ IMPORTANT SETUP NOTES ❗ For products: Ensure 'url_key' exists in custom_attributes For coupons: Magento REST API must expose coupon rules MySQL user needs INSERT/SELECT privileges Telegram bot must be added to your channel first 🔄 SCHEDULING: - Default: Checks every 1 hours at :00 - Adjust in Schedule Trigger node ` ⚙️ Technical Details Workflow Logic: Checks for new products/coupons via Magento API Verifies against MySQL database Only posts if record doesn't exist Updates database after successful post Error Handling: Automatic skip if product/coupon exists Empty result handling Connection timeout protection 🌟 Why This Template? Complete Solution**: Handles both products AND coupons Battle-Tested**: Prevents all duplicates reliably Ready-to-Use**: Just add your credentials Fully Customizable**: Easy to modify for different needs Perfect for e-commerce stores using Magento 2 who want automated, duplicate-free social notifications!

Video Guide I prepared a detailed guide that shows the whole process of building an AI tool to analyze Instagram Reels using n8n. Youtube Link Who is this for? This workflow is ideal for social media analysts, digital marketers, and content creators who want to leverage data-driven insights from their Instagram Reels. It's particularly useful for those looking to automate the analysis of video performance to inform strategy and content creation. What problem does this workflow solve? Analyzing video performance on Instagram can be tedious and time-consuming, requiring multiple steps and data extraction. This workflow automates the process of fetching, analyzing, and recording insights from Instagram Reels, making it simpler for users to track engagement metrics without manual intervention. What this workflow does This workflow integrates several services to analyze Instagram Reels, allowing users to: Automatically fetch recent Reels from specified creators. Analyze the most-watched videos for insights. Store and manage data in Airtable for easy access and reporting. Initial Trigger: The process begins with a manual trigger that can later be modified for scheduled automation. Data Retrieval: It connects to Airtable to fetch a list of creators and their respective Instagram Reels. Video Analysis: It handles the fetching, downloading, and uploading of videos for analysis using an external service, simplifying performance tracking through a structured query process. Record Management: It saves relevant metrics and insights into Airtable, ensuring that users can access and organize their video analytics effectively. Setup Create accounts: Set up Airtable, Edify, n8n, and Gemini accounts. Prepare triggers and modules: Replace credentials in each node accordingly. Configure data flow: Ensure modules are set to fetch and analyze the correct data fields as outlined in the guide. Test the workflow: Run the scenario manually to confirm that data is fetched and analyzed correctly.

N8N Automated Twitter Reply Bot Workflow For latest version, check: dziura.online/automation Latest documentation can be find here You must have Apify community node installed before pasting the JSON to your workflow.  Overview This n8n workflow creates an intelligent Twitter/X reply bot that automatically scrapes tweets based on keywords or communities, analyzes them using AI, generates contextually appropriate replies, and posts them while avoiding duplicates. The bot operates on a schedule with intelligent timing and retry mechanisms. Key Features Automated tweet scraping** from Twitter/X using Apify actors AI-powered reply generation** using LLM (Large Language Model) Duplicate prevention** via MongoDB storage Smart scheduling** with timezone awareness and natural posting patterns Retry mechanism** with failure tracking Telegram notifications** for status updates Manual trigger** option via Telegram command Required Credentials & Setup 1\. Telegram Bot Create a bot via @BotFather on Telegram Get your Telegram chat ID to receive status messages Credential needed**: Telegram account (Bot token) 2\. MongoDB Database Set up a MongoDB database to store replied tweets and prevent duplicates Create a collection (default name: collection\_name) Credential needed**: MongoDB account (Connection string) Tutorial**: MongoDB Connection Guide 3\. Apify Account Sign up at Apify.com Primary actors used**: Search Actor: api-ninja/x-twitter-advanced-search - For keyword-based tweet scraping (ID: 0oVSlMlAX47R2EyoP) Community Actor: api-ninja/x-twitter-community-search-post-scraper - For community-based tweet scraping (ID: upbwCMnBATzmzcaNu) Credential needed**: Apify account (API token) 4\. OpenRouter (LLM Provider) Sign up at OpenRouter.ai Used for AI-powered tweet analysis and reply generation Model used**: x-ai/grok-3 (configurable) Credential needed**: OpenRouter account (API key) 5\. Twitter/X API Set up developer account at developer.x.com Note**: Free tier limited to ~17 posts per day Credential needed**: X account (OAuth2 credentials) Workflow Components Trigger Nodes 1\. Schedule Trigger Purpose**: Runs automatically every 20 minutes Smart timing**: Only active between 7 AM - 11:59 PM (configurable timezone) Randomization**: Built-in probability control (~28% execution chance) to mimic natural posting patterns 2\. Manual Trigger Purpose**: Manual execution for testing 3\. Telegram Trigger Purpose**: Manual execution via /reply command in Telegram Usage**: Send /reply to your bot to trigger the workflow manually Data Processing Flow 1\. MongoDB Query (Find documents) Purpose**: Retrieves previously replied tweet IDs to avoid duplicates Collection**: collection\_name (configure to match your setup) Projection**: Only fetches tweet\_id field for efficiency 2\. Data Aggregation (Aggregate1) Purpose**: Consolidates tweet IDs into a single array for filtering 3\. Keyword/Community Selection (Keyword/Community List) Purpose**: Defines search terms and communities Configuration**: Edit the JSON to include your keywords and Twitter community IDs Format:{   "keyword\_community\_list": \[     "SaaS",     "Entrepreneur",      "1488663855127535616"  // Community ID (19-digit number)   \],   "failure": 0 } 4\. Random Selection (Randomized community, keyword) Purpose**: Randomly selects one item from the list to ensure variety 5\. Routing Logic (If4) Purpose**: Determines whether to use Community search or Keyword search Logic**: Uses regex to detect 19-digit community IDs vs keywords Tweet Scraping (Apify Actors) Community Search Actor Actor**: api-ninja/x-twitter-community-search-post-scraper Purpose**: Scrapes tweets from specific Twitter communities Configuration:{   "communityIds": \["COMMUNITY\_ID"\],   "numberOfTweets": 40 } Search Actor Actor**: api-ninja/x-twitter-advanced-search Purpose**: Scrapes tweets based on keywords Configuration:{   "contentLanguage": "en",   "engagementMinLikes": 10,   "engagementMinReplies": 5,   "numberOfTweets": 20,   "query": "KEYWORD",   "timeWithinTime": "2d",   "tweetTypes": \["original"\],   "usersBlueVerifiedOnly": true } Filtering System (Community filter) The workflow applies multiple filters to ensure high-quality replies: Text length**: >60 characters (substantial content) Follower count**: >100 followers (audience reach) Engagement**: >10 likes, >3 replies (proven engagement) Language**: English only Views**: >100 views (visibility) Duplicate check**: Not previously replied to Recency**: Within 2 days (configurable in actor settings) AI-Powered Reply Generation LLM Chain (Basic LLM Chain) Purpose**: Analyzes filtered tweets and generates contextually appropriate replies Model**: Grok-3 via OpenRouter (configurable) Features**: Engagement potential scoring User authority analysis Timing optimization Multiple reply styles (witty, informative, supportive, etc.) <100 character limit for optimal engagement Output Parser (Structured Output Parser) Purpose**: Ensures consistent JSON output format Schema:{   "selected\_tweet\_id": "tweet\_id\_here",   "screen\_name": "author\_screen\_name",    "reply": "generated\_reply\_here" } Posting & Notification System Twitter Posting (Create Tweet) Purpose**: Posts the generated reply as a Twitter response Error handling**: Catches API limitations and rate limits Status Notifications Success**: Notifies via Telegram with tweet link and reply text Failure**: Notifies about API limitations or errors Format**: HTML-formatted messages with clickable links Database Storage (Insert documents) Purpose**: Saves successful replies to prevent future duplicates Fields stored**: tweet\_id, screen\_name, reply, tweet\_url, timestamp Retry Mechanism The workflow includes intelligent retry logic: Failure Counter (If5, Increment Failure Counter1) Logic**: If no suitable tweets found, increment failure counter Retry limit**: Maximum 3 retries with different random keywords Wait time**: 3-second delay between retries Final Failure Notification Trigger**: After 4 failed attempts Action**: Sends Telegram notification about unsuccessful search Recovery**: Manual retry available via /reply command Configuration Guide Essential Settings to Modify MongoDB Collection Name: Update collection\_name in MongoDB nodes Telegram Chat ID: Replace 11111111111 with your actual chat ID Keywords/Communities: Edit the list in Keyword/Community List node Timezone: Update timezone in Code node (currently set to Europe/Kyiv) Actor Selection: Enable only one actor (Community OR Search) based on your needs Filter Customization Adjust filters in Community filter node based on your requirements: Minimum engagement thresholds Text length requirements Time windows Language preferences LLM Customization Modify the AI prompt in Basic LLM Chain to: Change reply style and tone Adjust engagement criteria Modify scoring algorithms Set different character limits Usage Tips Start small: Begin with a few high-quality keywords/communities Monitor performance: Use Telegram notifications to track success rates Adjust filters: Fine-tune based on the quality of generated replies Respect limits: Twitter's free tier allows ~17 posts/day Test manually: Use /reply command for testing before scheduling Troubleshooting Common Issues No tweets found: Adjust filter criteria or check keywords API rate limits: Reduce posting frequency or upgrade Twitter API plan MongoDB connection: Verify connection string and collection name Apify quota: Monitor Apify usage limits LLM failures: Check OpenRouter credits and model availability Best Practices Monitor your bot's replies for quality and appropriateness Regularly update keywords to stay relevant Keep an eye on engagement metrics Adjust timing based on your audience's activity patterns Maintain a balanced posting frequency to avoid appearing spammy Documentation Links Full Documentation**: Google Doc Guide Latest Version**: dziura.online/automation MongoDB Setup Tutorial**: YouTube Guide This workflow provides a comprehensive solution for automated, intelligent Twitter engagement while maintaining quality and avoiding spam-like behavior.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 📦 Multi-Platform Price Finder: Scraping Prices with Bright Data & Telegram An intelligent n8n automation that fetches real-time product prices from marketplaces like Amazon, Wayfair, Lowe's, and more using Bright Data's dataset, and sends promotional messages via Telegram using AI—perfect for price tracking, deal alerts, and affiliate monetization. 📋 Overview This automation tracks product prices across top e-commerce platforms using Bright Data and sends out alerts via Telegram based on the best available deals. The workflow is designed for affiliate marketers, resellers, and deal-hunting platforms who want real-time competitive pricing. ✨ Key Features 🔎 Multi-Platform Scraping: Supports Amazon, Wayfair, Lowe's, and more ⚡ Bright Data Integration: Access to structured product snapshots 📢 AI-Powered Alerts: Generates Telegram-ready promo messages using AI 🧠 Lowest Price Logic: Filters and compares products across sources 📈 Data Merge & Processing: Combines multiple sources into a single stream 🔄 Keyword-Driven Search: Searches using dynamic keywords from form input 📦 Scalable Design: Built for multiple platform processing simultaneously 🧼 Clean Output: Strips unnecessary formatting before publishing 🎯 What This Workflow Does Input Search Keywords**: User-defined keyword(s) from a form trigger Platform Sources**: Wayfair, Lowe's, Amazon, etc. Bright Data API Key**: Needed for authenticated scraping Processing Steps User Input via n8n form trigger (keyword-based) Bright Data API Trigger for each marketplace Status Polling: Wait until scraping snapshot is ready Data Retrieval: Fetches JSON results from Bright Data snapshot Data Cleaning & Normalization: Price, title, and URL are extracted Merging Products from all platforms Find Lowest Price Product using custom JS logic AI Prompt Generation via Claude/Anthropic Telegram Formatting and alert message creation Output 🛍️ Product Title 💰 Final Price 🔗 Product URL ✉️ Promotional Message (for Telegram/notifications) 🚀 Setup Instructions Step 1: Import Workflow Open n8n > Workflows > + Add Workflow Import the provided JSON file Step 2: Configure Bright Data Add credentials under Credentials → Bright Data API Set the appropriate dataset_id for each platform Ensure dataset includes title, price, and url fields Step 3: Enable Keyword Trigger Use the built-in Form Trigger node Input: Single keyword field (SearchHere) Step 4: Telegram or AI Integration Modify prompt node for your language or tone Add Telegram webhook or integration where needed 📖 Usage Guide Adding Keywords Trigger the form with a product keyword like iPhone 15 Wait for workflow to fetch best deals and generate Telegram message Understanding AI-Powered Output AI creates a short, engaging message like: > "🔥 Deal Alert: Get the iPhone 15 for just ₹74,999! Limited stock—Check it out: [link]" Debugging Output Output node shows cleaned JSON with title, price, url, and message If no valid results, debug message is returned with sample structure info 🔧 Customization Options Add More Marketplaces Clone any HTTP Request node (e.g., for Wayfair) Update dataset_id and required output fields Modify Price Logic Update the Code1 node to change comparison (e.g., highest price instead of lowest) Change Message Format Edit the AI Agent prompt to customize tone/language Add emoji, CTAs, or markdown formatting as needed 🧪 Test & Activation Add a few sample keywords via form trigger Run manually or set as a webhook for external app input Check final AI-generated message in output node 🚨 Troubleshooting | Issue | Solution | |-------|----------| | No Data Returned | Ensure keyword matches real products | | Status Not 'Ready' | Bright Data delay; add Wait nodes | | Invalid API Key | Check Bright Data credentials | | AI Errors | Adjust prompt or validate input fields | 📊 Use Cases 💰 Affiliate Campaigns: Show best deals across platforms 🛒 Deal Pages: Post live offers with product links 🧠 Competitor Analysis: Track cross-platform pricing 🔔 Alert Bots: Send real-time alerts to Telegram or Slack ✅ Quick Setup Checklist [x] Bright Data API credentials configured [x] n8n form trigger enabled [x] Claude or AI model connected [x] All HTTP requests working [x] AI message formatting verified 🌐 Example Output { "title": "Apple iPhone 15 Pro Max", "price": 1199, "url": "https://amazon.com/iphone-15", "message": "🔥 Grab the Apple iPhone 15 Pro Max for just $1199! Limited deal—Check it out: https://amazon.com/iphone-15" } 📬For any questions or support, please contact: 📧 <info@incrementors.com> or fill out this form: https://www.incrementors.com/contact-us/

🛡️ Automated AWS Key Compromise Remediation Description This n8n workflow provides a secure, enterprise-grade response system for AWS IAM access key compromises with built-in form submission and human approval mechanisms. When an AWS access key is suspected to be compromised, this workflow enables rapid containment through a secure web form interface with basic authentication, human approval via Slack, and automated damage prevention through immediate key deactivation, credential invalidation, and comprehensive security reporting. How This Workflow is Useful Secure Form-Based Response Authenticated Form Submission**: Secure web form with basic authentication for capturing compromise details Human Approval Workflow**: Slack-based approval system for sensitive security operations Rapid Key Deactivation**: Instantly disables compromised access keys after approval Credential Invalidation**: Creates and applies security policies to invalidate existing temporary credentials Policy Analysis**: Automatically scans and analyzes both inline and attached IAM policies for the affected user AI-Powered Reporting**: Generates detailed security reports with intelligent analysis and team notifications Business Value Reduces Mean Time to Response (MTTR)**: Automates manual security procedures that typically take hours Minimizes Security Exposure**: Immediate containment prevents potential data breaches and unauthorized resource access Ensures Compliance**: Provides audit trails and documentation required for security compliance frameworks Cost Prevention**: Prevents potential financial damage from compromised credentials being used maliciously Rapid Response Capability**: Streamlines security response procedures when incidents are detected Technical Benefits AWS Best Practices**: Implements official AWS security recommendations for key compromise response Scalable Architecture**: Handles multiple access keys and complex IAM policy structures Error Handling**: Robust error handling ensures workflow continues even if individual steps fail Audit Trail**: Complete logging of all actions taken during the incident response Integration Ready**: Easily integrates with existing security tools and notification systems Use Cases 1. Incident Response Automation Automated response to security alerts from AWS CloudTrail Integration with SIEM systems for immediate key compromise response 24/7 security monitoring and automated containment 2. Compliance and Audit Meeting regulatory requirements for incident response documentation Providing audit trails for security compliance frameworks (SOC 2, ISO 27001, PCI DSS) Demonstrating due diligence in security incident handling 3. Multi-Account Management Centralized security response across multiple AWS accounts Consistent incident response procedures across different environments Standardized security automation for enterprise AWS deployments 4. Security Training and Testing Security team training on AWS incident response procedures Tabletop exercises and security drills Testing and validation of security response capabilities Key Features Core Functionality ✅ Secure Form Interface: Web form with basic authentication for secure data submission ✅ Human Approval Gate: Slack-based approval workflow for sensitive operations ✅ Authenticated Data Processing: Secure handling of form submissions with validation ✅ Immediate Key Deactivation: Instant disabling of compromised credentials after approval ✅ Security Policy Generation: Automatic creation and attachment of credential invalidation policies ✅ Policy Analysis: Deep analysis of user permissions and attached policies ✅ AI Security Analysis: Intelligent security report generation with risk assessment ✅ Team Notifications: Real-time Slack notifications to security teams ✅ Comprehensive Logging: Complete audit trail of all response actions Technical Specifications Secure Form Interface**: Web form with basic authentication for secure data capture Human Approval System**: Slack-based approval workflow for sensitive operations AWS API Integration**: Direct integration with AWS IAM APIs Authentication Layer**: Basic auth protection for form submissions Error Handling**: Robust error handling with continuation on non-critical failures Scalable Processing**: Handles multiple policies and complex IAM structures Security Best Practices**: No hardcoded credentials, uses AWS credential management Modular Design**: Easy to customize and extend for specific organizational needs Prerequisites Required Credentials AWS Credentials** with IAM permissions for: ListAccessKeys, UpdateAccessKey ListUserPolicies, ListAttachedUserPolicies CreatePolicy, AttachUserPolicy GetPolicy, GetPolicyVersion, GetUserPolicy Required Integrations Slack Workspace** for approval workflow and team notifications Basic Authentication Setup** for secure form access Optional Integrations AI Language Model** (Claude/OpenAI) for intelligent security analysis and report generation Installation and Setup Import the workflow into your n8n instance Configure AWS credentials in n8n credential manager Set up basic authentication for the secure form interface Configure Slack integration for approval notifications and team alerts Set up AI model (optional) for enhanced security analysis and reporting Configure approval workflow in Slack for human oversight Test in development environment before production use Workflow Inputs Secure Form Submission This workflow uses a secure web form with basic authentication to capture compromise details: Username**: The AWS IAM username of the compromised account Access Key ID**: The specific access key ID that has been compromised Authentication & Approval Process Form Authentication: Basic authentication protects the submission form Data Processing: Secure handling and validation of submitted credentials Human Approval: Slack notification sent to security team for approval Automated Execution: Upon approval, the workflow executes the security response This multi-layered approach ensures that sensitive security operations require both authentication and human oversight before execution. 🚀 Automate with Slack Integration Want to fully automate and simplify this workflow? Connect it with Slack for seamless team collaboration and instant response capabilities! Interactive Slack Automation Combine this AWS Key Compromise Response workflow with our Interactive Slack Approval & Data Submission System to create a fully automated incident response pipeline: Instant Slack Alerts**: Receive immediate notifications when key compromises are detected One-Click Response**: Trigger the AWS response workflow directly from Slack with interactive buttons Team Collaboration**: Enable security teams to respond collectively through Slack channels Approval Workflows**: Add human approval gates before executing critical security actions Real-time Updates**: Get live status updates and completion notifications in Slack How the Complete Solution Works Detection: External security monitoring tools (CloudTrail, SIEM, etc.) detect potential key compromise Secure Form Access: Security team accesses the authenticated web form to submit compromise details Form Submission: Credentials are securely submitted through the basic auth-protected form Human Approval: Slack notification sent to security team for review and approval Approved Execution: Upon approval, the AWS security response executes automatically Real-time Updates: Progress and completion notifications sent back to Slack Security Analysis: AI-powered analysis and comprehensive reporting delivered to the team Get Started with Full Automation To enable automatic notifications and complete the automation pipeline, use the Interactive Slack Approval & Data Submission System with Webhooks workflow: https://n8n.io/workflows/5049-interactive-slack-approval-and-data-submission-system-with-webhooks/ This integration transforms manual security responses into streamlined, team-collaborative automation that reduces response time from hours to minutes. Security Considerations Form Authentication**: Basic authentication protects the submission interface Human Approval Gate**: Slack-based approval prevents unauthorized execution AWS Credential Management**: Uses AWS credential management best practices No Sensitive Data Storage**: No sensitive data stored in workflow configuration Least-Privilege Access**: Implements least-privilege access principles Complete Audit Trails**: Provides complete audit trails for compliance Secure Data Processing**: Encrypted handling of form submissions and approvals Immediate Damage Prevention**: Designed for rapid containment after approval ⚠️ Important Disclaimer Use with Caution: Disabling access keys without proper understanding can significantly impact your personal or business operations. This workflow immediately deactivates AWS access keys, which may disrupt running applications, automated processes, or services that depend on these credentials. AWS Best Practices Recommendation: Use IAM Roles instead of Access Keys** whenever possible for enhanced security IAM roles provide temporary credentials and eliminate the need for long-term access keys Follow the principle of least privilege when assigning permissions Regularly rotate and audit your AWS credentials Implement proper monitoring and alerting for credential usage Before Using This Workflow: Ensure you understand which services and applications use the target access key Have a rollback plan in case of accidental disruption Test in a non-production environment first Coordinate with your team before executing in production For comprehensive AWS security best practices, refer to the AWS Security Best Practices Guide. For more workflows and automation solutions, visit: https://n8n.io/creators/niranjan/

Source Discovery - Automatically Search More Up-to-Date Information Sources 🎬 Overview Version : 1.0 This workflow utilizes various nodes to discover and analyze potential sources of information from platforms like Google, Reddit, GitHub, Bluesky, and others. It is designed to streamline the process of finding relevant sources based on specified search themes. ✨ Features Automated source discovery from multiple platforms. Filtering of existing and undesired sources. Error handling for API requests. User-friendly configuration options. 👤 Who is this for? This workflow is ideal for researchers, content marketers, journalists, and anyone looking to efficiently gather and analyze information from various online sources. 💡 What problem does this solve? This workflow addresses the challenge of manually searching for relevant information sources, saving time and effort while ensuring that users have access to the most pertinent content. Ideal use-cases include: Resource Compilation for Academic and Educational Purposes Journalism and Research Content Marketing Competitor Analysis 🔍 What this workflow does The workflow gathers data from selected platforms through search terms. It filters out known and undesired sources, analyzes the content, and provides insights into potential sources relevant to the user's needs. 🔄 Workflow Steps 1. Search Queries Fetch sources using SerpAPI search, DuckDuckGo, and Bluesky. Utilizes GitHub repositories to find relevant links. Leverages RSS feeds from subreddits to identify potential sources. 2. Filtering Step Removes existing and undesired sources from the results. 3. Source Selection Analyzes the content of the identified sources for relevance. 📌 Expected Input / Configuration The workflow is primarily configured via the Configure Workflow Args (Manual) node or the Global Variables custom node. Search themes: Keywords or phrases relevant to the desired content. Lists of known sources and undesired sources for filtering. 📦 Expected Output A curated list of potential sources relevant to the specified search themes, along with insights into their content. 📌 Example ⚙️ n8n Setup Used n8n version:** 1.105.3 n8n-nodes-serpapi:** 0.1.6 n8n-nodes-globals:** 1.1.0 n8n-nodes-bluesky-enhanced**: 1.6.0 n8n-nodes-duckduckgo-search**: 30.0.4 LLM Model:** mistral-small-latest (API) Platform:** Podman 4.3.1 on Linux Date:** 2025-08-06 ⚡ Requirements to Use / Setup Self-hosted or cloud n8n instance. Install the following custom nodes: SerpAPI, Bluesky, and DuckDuckGo Search. n8n-nodes-serpapi n8n-nodes-duckduckgo-search n8n-nodes-bluesky-enhanced Install the Global Variables Node for enhanced configuration: n8n-nodes-globals (or use Edit Field (Set) node instead) Provide valid credentials to nodes for your preferred LLM model, SerpAPI, and Bluesky. Credentials for GitHub recommended. ⚠️ Notes, Assumptions \& Warnings Ensure compliance with the terms of service of any platforms accessed or discovered in this workflow, particularly concerning data usage and attribution. Monitor API usage to avoid hitting rate limits. The workflow may encounter errors such as 403 responses; in such cases, it will continue by ignoring the affected substep. Duplicate removal is applied, but occasional overlaps might still appear depending on the sources. This workflow assumes familiarity with n8n, APIs, and search engines. Using AI agents (Mistral or substitute LLMs) requires access to their API services and keys. This is not a Curator of News. It is designed to find websites that are relevant and useful to your searches. If you are looking for a relevant news selector, please check this workflow. ℹ️ About Us This workflow was developed by the Hybroht team. Our goal is to create tools that harness the possibilities of technology and more. We aim to continuously improve and expand functionalities based on community feedback and evolving use cases. For questions, reach out via contact@hybroht.com. ⚖️ Warranty & Legal Notice This free workflow is provided "as-is" without any warranties of any kind, either express or implied, including but not limited to the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. By using this workflow, you acknowledge that you do so at your own risk. We shall not be held responsible for any damages, losses, or liabilities arising from the use or inability to use this workflow, including but not limited to any direct, indirect, incidental, or consequential damages. It is your responsibility to ensure that your use of this workflow complies with all applicable laws and regulations.

Automatically fetches daily sales, shifts, and receipts from Loyverse. Calculates gross profit, net operating profit, other key metrics, saves them to a Google Sheet and sends out a daily report via email. Who’s it for This template is for any business owner, manager, or analyst using Loyverse POS who needs more advanced financial reporting. If you're a restaurant, bar, or retail owner who wants to automatically track daily net profit, compare sales to historical averages, and build a custom financial dashboard in Google Sheets, this workflow is for you. How it works / What it does This workflow runs automatically on a daily schedule. It fetches all sales data and receipts from your Loyverse account for the previous business day, defined by your custom shift times (even past midnight). A powerful Code node then processes all the data to calculate the metrics that Loyverse either doesn't provide at all, or only spreads out across several separate reports instead of in one consolidated place. Already set up are metrics like... -Total Revenue, Gross Profit, and Net Operating Profit Cash handling differences (over/under) Average spend per receipt (ATV) 30-day rolling Net Operating Profit (NOP) Performance vs. your historical weekday average Finally, it appends the single, calculated row of daily metrics to a Google Sheet and sends an easily customizable summary report to your email. How to set up This workflow includes detailed Sticky Notes to guide you through the setup process. Because every business has a unique POS configuration (different POS devices, categories, and payment types), you'll need to set up a few things manually before executing the workflow. I've tried to make this as easy as possible to follow, and the entire setup should only take about 15 minutes. Preparations & Credential setup Subscribe to "Integrations" Add-on in Loyverse ($9 / month) to gain API access. Create an Access token in Loyverse Create Credentials: In your n8n instance, create credentials for Loyverse (use "Generic" > "Bearer Auth"), Google Sheets (OAuth2), and your Email (SMTP or other). Make a copy of a prep-configured Google Spreadsheet (Link in the second sticky note inside the workflow). Fill MASTER CONFIG: Open the MASTER CONFIG node. Follow the comments inside to add your Google Sheet ID, Sheet Names, business hours, timezone, and Loyverse IDs (for POS devices, payment types, and categories). Configure Google Sheet Nodes Configure Read Historical Data: Open this node. Follow the instructions in the nearby Sticky Note to paste the expressions for your Document ID and Sheet Name. Configure Save Product List: Open this node. Paste in the expressions for Document ID and Sheet Name. The column mapper will load; map your sheet columns (e.g., item_name) to the data on the left (e.g., {{ $json.item_name }}). Configure Save Latest Sales Data: Open this node. Paste in the expressions for Document ID and Sheet Name. Save and run the workflow. After that, the column mapper will load. This is the most important step: map your sheet's column names (e.g., "Total Revenue") to the calculated metrics from the Calculate All Metrics node (e.g., {{ $json.totalGrossRevenue }}). Activate the workflow. 🫡 Requirements Loyverse Integrations Subscription Loyverse Access Token Credentials for Loyverse (Bearer Auth) Credentials for Google Sheets (OAuth2) Credentials for Email/SMTP sender How to customize the workflow This template is designed to be highly flexible. Central Configuration: Almost all customization (POS devices, categories, payment types, sheet names) is done in the MASTER CONFIG node. You don't need to dig through other nodes. Add/Remove Metrics: The Calculate All Metrics node has additional metrics already set up, just add the relevant collumns to the SalesData sheet or even add your own calculations to the node. Any new metric you add (e.g., metrics.myNewMetric = 123) will be available to map in the Save Latest Sales Data node. Email Body: You can easily edit the Send email node to change the text or add new metrics from the Calculate All Metrics node.

Zoho CRM → AI Sentiment Analysis for customer interactions & Automatic Alerts Workflow This workflow analyzes newly created Notes (in Any module) in Zoho CRM, detects customer sentiment using an AI model, updates the related CRM record with custom fields - sentiment label and score, and sends an instant alert whenever negative sentiment is detected. It runs on a scheduled interval and gives teams real-time visibility into customer emotions and potential risks. Quick Implementation Steps Connect Zoho CRM OAuth2 credentials Add custom fields in Zoho CRM: Sentiment_Label and Sentiment_Score Add AI provider credentials Set Gmail alert recipient Activate workflow and test by adding a Note What It Does This workflow automatically monitors Zoho CRM Notes. When a new Note is detected, the text is extracted and analyzed through an AI-powered sentiment model. The AI classifies the text as Positive, Neutral or Negative and produces a numeric sentiment score. The workflow updates the related CRM module with these values. If the sentiment is negative, a Gmail alert is triggered so your team can follow up quickly. This automation helps organizations maintain high customer satisfaction and detect potential issues early. Who’s It For Support teams Sales teams CRM administrators Customer success managers Businesses needing automated customer sentiment tracking Requirements n8n instance Zoho CRM OAuth2 credentials Gmail OAuth2 credentials AI provider key Custom fields in Zoho CRM: Sentiment_Label & Sentiment_Score (if you are using different field name then do changes in workflow accoredingly) How It Works & Setup Step 1: Schedule Trigger Runs periodically to check for new or updated Notes. Step 2: Fetch Latest Note Retrieves the most recently modified Note. Step 3: Extract Details Extracts Note text, note_id, parent_id and module name. Step 4: AI Sentiment Analysis Sends text to the AI (via LangChain chain) for sentiment classification. Step 5: Conditional Branching If Negative: Send Gmail alert and update CRM Otherwise: Just update CRM Step 6: Update CRM Writes sentiment data back into the related parent record. How to Customize Nodes Adjust sentiment output by modifying the AI prompt. Change field mappings in Zoho update nodes. Customize the Gmail alert message. Adjust Schedule Trigger frequency. Add additional metadata (e.g., emotion tags). Add‑Ons Slack/Teams alerts for negative sentiment. Historical sentiment logging. Weekly sentiment reports. Auto-task creation for negative interactions. Priority-based escalation logic. Use Case Examples Detect unhappy customers in support interactions. Monitor sentiment across sales conversations. Escalate negative feedback automatically. Quality assurance tracking for customer interactions. Early detection of churn indicators. Troubleshooting Guide | Issue | Possible Cause | Solution | |------|----------------|----------| | Sentiment not updating | Missing Zoho fields | Add custom fields in CRM | | Note not detected | Fetching only latest note | Increase frequency or widen fetch scope | | AI output invalid | Prompt mismatch | Update prompt and parser | | Alerts not sending | Gmail OAuth expired | Reconnect Gmail | | Incorrect sentiment | Weak prompt instructions | Refine prompt wording | Need Help? WeblineIndia can help you configure, customize and extend workflows like this. We specialize in: n8n automation CRM integrations AI/LLM-powered workflows Zoho CRM customization Reach out if you'd like assistance building or enhancing similar n8n automation solutions.

📊 Description Ensure your GitHub repositories stay configuration-accurate and documentation-compliant with this intelligent AI-powered validation workflow. 🤖 This automation monitors repository updates, compares configuration files against documentation references, detects inconsistencies, and alerts your team instantly—streamlining DevOps and compliance reviews. ⚡ What This Template Does Step 1: Triggers automatically on GitHub push or pull_request events. 🔄 Step 2: Fetches both configuration files (config/app-config.json and faq-config.json) from the repository. 📂 Step 3: Uses GPT-4o-mini to compare configurations and detect mismatches, missing keys, or deprecated fields. 🧠 Step 4: Categorizes issues by severity—critical, high, medium, or low—and generates actionable recommendations. 🚨 Step 5: Logs all discrepancies to Google Sheets for tracking and audit purposes. 📑 Step 6: Sends Slack alerts summarizing key issues and linking to the full report. 💬 Key Benefits ✅ Prevents production incidents due to config drift ✅ Ensures documentation stays in sync with code changes ✅ Reduces manual review effort with AI-driven validation ✅ Improves team response with Slack-based alerts ✅ Maintains audit logs for compliance and traceability Features Real-time GitHub webhook integration AI-powered config comparison using GPT-4o-mini Severity-based issue classification Automated Google Sheets logging Slack alerts with detailed issue context Error handling for malformed JSON or parsing issues Requirements GitHub OAuth2 credentials with repo and webhook permissions OpenAI API key (GPT-4o-mini or compatible model) Google Sheets OAuth2 credentials Slack API token with chat:write permissions Target Audience DevOps teams ensuring consistent configuration across environments Engineering leads maintaining documentation accuracy QA and Compliance teams tracking configuration changes and risks Setup Instructions Create GitHub OAuth2 credentials and enable webhook access. Connect your OpenAI API key under credentials. Add your Google Sheets and Slack integrations. Update file paths (config/app-config.json and faq-config.json) if your repo uses different names. Activate the workflow — it will start validating on every push or PR. 🚀