Copyright infringement detector with ScrapeGraphAI and automated legal response
Copyright Infringement Detector with ScrapeGraphAI Analysis and Legal Action Automation 🎯 Target Audience Intellectual property lawyers and legal teams Brand protection specialists Content creators and publishers Marketing and brand managers Digital rights management teams Copyright enforcement agencies Media companies and publishers E-commerce businesses with proprietary content Software and technology companies Creative agencies protecting client work 🚀 Problem Statement Manual monitoring for copyright infringement is time-consuming, often reactive rather than proactive, and can miss critical violations that damage brand reputation and revenue. This template solves the challenge of automatically detecting copyright violations, analyzing infringement patterns, and providing immediate legal action recommendations using AI-powered web scraping and automated legal workflows. 🔧 How it Works This workflow automatically scans the web for potential copyright violations using ScrapeGraphAI, analyzes content similarity, determines legal action requirements, and provides automated alerts for immediate response to protect intellectual property rights. Key Components Schedule Trigger - Runs automatically every 24 hours to monitor for new infringements ScrapeGraphAI Web Search - Uses AI to search for potential copyright violations across the web Content Comparer - Analyzes potential infringements and calculates similarity scores Infringement Detector - Determines legal action required and creates case reports Legal Action Trigger - Routes cases based on severity and urgency Brand Protection Alert - Sends urgent alerts for high-priority violations Monitoring Alert - Tracks medium-risk cases for ongoing monitoring 📊 Detection and Analysis Specifications The template monitors and analyzes the following infringement types: | Infringement Type | Detection Method | Risk Level | Action Required | |-------------------|------------------|------------|-----------------| | Exact Text Match | High similarity score (>80%) | High | Immediate cease & desist | | Paraphrased Content | Moderate similarity (50-80%) | Medium | Monitoring & evidence collection | | Unauthorized Brand Usage | Brand name detection in content | High | Legal consultation | | Competitor Usage | Known competitor domain detection | High | DMCA takedown | | Image/Video Theft | Visual content analysis | High | Immediate action | | Domain Infringement | Suspicious domain patterns | Medium | Investigation | 🛠️ Setup Instructions Estimated setup time: 30-35 minutes Prerequisites n8n instance with community nodes enabled ScrapeGraphAI API account and credentials Telegram or other notification service credentials Legal team contact information Copyrighted content database Step-by-Step Configuration Install Community Nodes bash Install required community nodes npm install n8n-nodes-scrapegraphai Configure ScrapeGraphAI Credentials Navigate to Credentials in your n8n instance Add new ScrapeGraphAI API credentials Enter your API key from ScrapeGraphAI dashboard Test the connection to ensure it's working Set up Schedule Trigger Configure the monitoring frequency (default: every 24 hours) Adjust timing to match your business hours Set appropriate timezone for your legal team Configure Copyrighted Content Database Update the Content Comparer node with your protected content Add brand names, slogans, and unique phrases Include competitor and suspicious domain lists Set similarity thresholds for different content types Customize Legal Action Rules Update the Infringement Detector node with your legal thresholds Configure action plans for different infringement types Set up case priority levels and response timelines Define evidence collection requirements Set up Alert System Configure Telegram bot or other notification service Set up different alert types for different severity levels Configure legal team contact information Test alert delivery and formatting Test and Validate Run the workflow manually with test search terms Verify all detection steps complete successfully Test alert system with sample infringement data Validate legal action recommendations 🔄 Workflow Customization Options Modify Detection Parameters Adjust similarity thresholds for different content types Add more sophisticated text analysis algorithms Include image and video content detection Customize brand name detection patterns Extend Legal Action Framework Add more detailed legal action plans Implement automated cease and desist generation Include DMCA takedown automation Add court filing preparation workflows Customize Alert System Add integration with legal case management systems Implement tiered alert systems (urgent, high, medium, low) Add automated evidence collection and documentation Include reporting and analytics dashboards Output Customization Add integration with legal databases Implement automated case tracking Create compliance reporting systems Add trend analysis and pattern recognition 📈 Use Cases Brand Protection: Monitor unauthorized use of brand names and logos Content Protection: Detect plagiarism and content theft Legal Enforcement: Automate initial legal action processes Competitive Intelligence: Monitor competitor content usage Compliance Monitoring: Ensure proper attribution and licensing Evidence Collection: Automatically document violations for legal proceedings 🚨 Important Notes Respect website terms of service and robots.txt files Implement appropriate delays between requests to avoid rate limiting Regularly review and update copyrighted content database Monitor API usage to manage costs effectively Keep your credentials secure and rotate them regularly Ensure compliance with local copyright laws and regulations Consult with legal professionals before taking automated legal action Maintain proper documentation for all detected violations 🔧 Troubleshooting Common Issues: ScrapeGraphAI connection errors: Verify API key and account status False positive detections: Adjust similarity thresholds and detection parameters Alert delivery failures: Check notification service credentials Legal action errors: Verify legal team contact information Schedule trigger failures: Check timezone and interval settings Content analysis errors: Review the Code node's JavaScript logic Support Resources: ScrapeGraphAI documentation and API reference n8n community forums for workflow assistance Copyright law resources and best practices Legal automation and compliance guidelines Brand protection and intellectual property resources
By vinci-king-01Reliable Reddit subreddit search with OAuth2 API authentication
Since the Get Many Subreddit node often blocks requests because Reddit requires proper authentication headers, this workflow provides a reliable alternative. It uses the Reddit OAuth2 API through the HTTP Request node, processes the results, and outputs cleaned subreddit data. If you are using Get Many subreddit node and you are getting this error: n8n You've been blocked by network security.To continue, log in to your Reddit account or use your developer token Usecase: This is especially useful if you want to search multiple subreddits programmatically and apply filtering for members, descriptions, and categories. How It Works Trigger Input The workflow is designed to be called by another workflow using the Execute Workflow Trigger node. Input is passed in JSON format with parameters: json { "Query": "RealEstateTechnology", "min_members": 0, "max_members": 20000, "limit": 50 } Fetch Subreddits The HTTP Request (Reddit OAuth2) node queries the Reddit API (/subreddits/search) with the given keyword and limit. Because it uses OAuth2 credentials, the request is properly authenticated and accepted by Reddit. Process Results Split Out: Iterates over each subreddit entry (data.children). Edit Fields: Extracts the following fields for clarity: Subreddit URL Description 18+ flag Member count Aggregate: Recombines the processed data into a structured output array. Output Returns a cleaned dataset with only the relevant subreddit details.(Saves token if Attached to an AI Agent) How to Use Import this workflow into n8n. In your main workflow, replace the Get Many Subreddit node with an Execute Workflow node and select this workflow. Pass in the required query parameters (Query, minmembers, maxmembers, limit). Run your main workflow — results will now come through authenticated API requests without being blocked. --- Requirements Reddit OAuth2 API Credentials (must be set up in n8n under Credentials*). Basic understanding of JSON parameters in n8n. An existing workflow that calls this one using Execute Workflow. --- Customizing This Workflow You can adapt this workflow to your specific needs by: Filtering by member range: Add logic to exclude subreddits outside minmembers or maxmembers. Expanding extracted fields: Include additional subreddit properties such as createdutc, lang, or activeuser_count. Changing authentication: Switch to different Reddit OAuth2 credentials if managing multiple Reddit accounts. Integrating downstream apps: Send the processed subreddit list to Google Sheets, Airtable, or a database for storage.
By Christian MoisesAutomated patient vitals monitoring & alerts with Philips IntelliVue & Google Sheets
This workflow utilizes Philips IntelliVue Device details to automatically track patient vitals, such as heart rate and oxygen levels. It quickly spots critical health issues and sends alerts to healthcare staff for fast action. The system saves data for records and helps improve patient care with real-time updates. It’s simple to set up and adjust for different needs. Essential Information Processes data from Philips IntelliVue Devices to monitor vitals instantly. Filters and categorizes conditions as critical or non-critical based on thresholds. Sends clinical alerts for critical conditions and logs data for review. Runs every 30 seconds to ensure timely updates. System Architecture Data Collection Pipeline: Poll Device Data Every 30s: Continuously retrieves vitals from Philips IntelliVue Devices. Fetch from IntelliVue Gateway: Retrieves data via HTTP GET requests. Processing Pipeline: Process Device Data: Analyzes and validates the data stream. Alert Generation Flow: Validate & Enrich Data: Ensures accuracy and adds patient context. Save to Patient Database: Stores data for records. Check Alert Status: Applies rules to trigger alerts. Send Clinical Alert: Notifies staff for critical conditions. Implementation Guide Import workflow JSON into n8n. Configure the Philips IntelliVue Devices gateway URL and test with sample data. Set up alert credentials (e.g., email). Test and adjust rule thresholds. Technical Dependencies Philips IntelliVue Devices for vitals data. n8n for automation. Email or messaging API for alerts. Database for data storage. Customization Possibilities Adjust Switch node rules for critical thresholds. Customize alert messages. Modify database schema. Add logging for analysis.
By Oneclick AI Squad