This workflow can automatically convert Splunk alerts into unique Jira tickets, preventing duplicate ticket creation. It intelligently assesses existing tickets and updates relevant information in real-time, ensuring data integrity and consistency. Additionally, it automatically standardizes hostname formats, enhancing the accuracy of ticket fields. This process significantly improves the response speed and management efficiency of security operations and IT operations teams, reduces manual intervention, lowers the risk of errors, and optimizes the alert handling process.

This workflow automatically backs up workflow configurations to Nextcloud cloud storage to ensure data security. Users can choose to schedule tasks or manually trigger the backup process. The system retrieves workflow details by calling an API, merges and converts them into binary format, and then uploads them to the cloud for centralized management and convenient recovery. This solution is suitable for teams or individuals who need to regularly back up and protect workflow data, significantly improving operational efficiency and reducing the complexity of manual operations.

This workflow can automatically retrieve server information from multiple regions of the Scaleway cloud service platform and perform data integration and standardization. Users can quickly locate target servers using flexible filtering criteria (such as tags, names, public IPs, and regions). Ultimately, the filtered results are returned through a Webhook interface, enhancing the automation level of cloud resource management. It is suitable for DevOps engineers, operations automation developers, and IT infrastructure teams, enabling efficient server information querying and management.

This workflow is capable of regularly fetching content from the Hacker News homepage, automatically filtering out popular projects that contain the keyword "Show HN:", and sending them to users via email. It addresses the cumbersome process of users manually searching for information, achieving automated data collection and integration. This helps tech enthusiasts, entrepreneurs, and investors quickly access the latest ideas and project showcases, enhancing the efficiency and accuracy of information retrieval.

This workflow monitors changes in a specified Dropbox folder in real-time through a Webhook, automatically detecting newly added or modified files. It filters out known files using a database to ensure that only new files trigger subsequent automated processing. It supports monitoring multiple folders and offers a flexible file filtering mechanism, enhancing the efficiency of file change management. This is suitable for scenarios such as content creation, team collaboration, and IT automation, significantly reducing manual intervention and improving work efficiency.

This workflow implements automated management of bookmarks through the Raindrop API, including functionalities for creating, updating, and querying bookmarks. Users can easily create bookmark collections, dynamically update bookmark titles, and retrieve detailed information, thereby improving the efficiency and accuracy of bookmark management. It is suitable for positions in content management, information collection, and especially beneficial when frequently handling large amounts of online resources, as it effectively reduces errors caused by manual operations, saves time, and enhances management standardization.

This workflow automatically monitors IP addresses and their ports within the enterprise's internal systems on a weekly basis. It utilizes the Shodan API to scan for open ports and services, promptly identifying any unexpected abnormal ports. The information is organized into a Markdown format report, which is then pushed to TheHive platform for quick response. Its core advantages lie in enhancing monitoring efficiency, reducing human oversight, ensuring network security, and helping the security team stay informed about potential risks, thereby building an efficient security protection system.

This workflow automatically monitors the leaked data on the HaveIBeenPwned website at scheduled intervals to detect new data breach incidents. When new leaked information is found, the system promptly triggers alerts to ensure that users can quickly respond to security risks. This process runs automatically every 15 minutes and employs an intelligent caching mechanism to avoid duplicate alerts. It supports flexible integration with various messaging platforms, enhancing the efficiency and responsiveness of information security monitoring, making it suitable for the security management needs of both individuals and businesses.

This workflow is designed to automatically back up workflow configurations to a specified GitHub repository, ensuring data security and version management. It supports both scheduled and manual triggers, intelligently assesses the backup status to avoid duplicate writes, thereby optimizing storage efficiency. By utilizing a sub-workflow design, it reduces memory usage and enhances execution stability, helping users effectively mitigate the risk of data loss. It meets the needs of team collaboration and compliance auditing, making it an important tool for automated management.

This workflow automates the generation and storage of sensor data. Every minute, it generates data that includes the sensor ID, a random humidity value, and a timestamp, and writes this information into a PostgreSQL database. It effectively addresses the need for real-time data collection and storage, eliminates the need for manual intervention, and enhances the automation and accuracy of data processing. This workflow is widely applicable in monitoring systems and smart home applications within the Internet of Things (IoT) environment.

This workflow is designed to automatically back up users' workflow configurations, regularly saving the backup data as JSON files and uploading them to a specific directory in Google Drive. Through scheduled triggers and data transformation, it ensures the secure storage and convenient recovery of workflows, effectively preventing data loss due to accidental operations or system failures. It is suitable for enterprises and individuals that require regular backups and centralized storage of workflow configurations, enhancing management efficiency and data security.

This workflow utilizes AI technology to automate the processing of resumes and matching them with job applications. It supports the upload of resumes in PDF format, automatically extracts key information, and pre-fills application forms based on job requirements, significantly reducing the workload for both applicants and HR. Airtable is integrated as the backend database, facilitating centralized storage and management of resumes and application information, thereby enhancing recruitment efficiency and optimizing the candidate experience. This system is suitable for corporate recruitment websites and various job postings, promoting the intelligent automation of the recruitment process.

The API architecture crawling and extraction workflow is an intelligent automation tool that efficiently searches, crawls, and extracts API documentation for specified services. By integrating search engines, web crawlers, and large language models, this workflow not only accurately identifies API operations but also structures the information for storage in Google Sheets. Additionally, it generates customized API architecture JSON files for centralized management and sharing, significantly enhancing development and integration efficiency, and helping users quickly obtain and organize API information.

This workflow automates the process of web data scraping, extracting and formatting content, generating high-quality text vector embeddings, and storing them in a vector database, forming a complete data processing loop. By combining efficient data crawling, intelligent content extraction, and vector retrieval technologies, users can quickly build vector datasets suitable for training large language models, enhancing data quality and processing efficiency, and making it applicable to various scenarios such as machine learning, intelligent search, and knowledge management.

This workflow can be manually triggered to quickly batch retrieve all product information from a Shopify store, enabling automated data extraction. The operation is simple; just click to execute without the need for coding. It is suitable for e-commerce operators, data analysts, and marketing teams, enhancing the efficiency and accuracy of obtaining product information, and supporting subsequent business decisions and data-driven operations.

The main function of this workflow is to provide e-commerce customers with secure and intelligent order inquiry and logistics tracking services. By integrating WooCommerce with DHL, customers can quickly access their order information and package status while ensuring data privacy. With the use of AI-powered customer service, customers can engage in natural language interactions, enhancing service efficiency and reducing the workload of customer service representatives, ultimately improving customer satisfaction. Additionally, the system ensures that customers can only query their personal orders, thereby reducing the risk of data leakage.

This workflow transforms a Telegram bot into an intelligent document assistant. Users can upload PDF documents via Telegram, and the system automatically parses them to generate semantic vectors, which are stored in a Supabase database for easy intelligent retrieval and Q&A. The bot utilizes a powerful language model to answer complex questions in real-time, supporting rich HTML format output and automatically splitting long replies to ensure clear information presentation. Additionally, it integrates a weather query feature to enhance user experience, making it suitable for personal knowledge management, corporate assistance, educational tutoring, and customer support scenarios.

This workflow is specifically designed to receive and process payment notifications from the Ko-fi platform. It can automatically verify the security of requests and intelligently categorize them into three types: donations, subscription payments, and store orders. By extracting key payment data, the workflow simplifies the data processing process, supports first-time subscription identification, and aids in precise marketing and user management. It is suitable for content creators, freelancers, and online stores, enhancing operational efficiency and enabling automated integration with other systems.

This workflow builds a comprehensive multi-format AI chatbot that allows users to interact with it via text or voice. The chatbot utilizes advanced natural language processing technology and possesses contextual memory capabilities, enabling multi-turn conversations and ensuring coherent responses. It can automatically transcribe voice messages and intelligently handle different types of information to enhance the user experience. Additionally, by formatting and correcting errors, it ensures the accuracy and professionalism of the replies, making it widely applicable in customer service, intelligent assistance, and voice processing scenarios.

This workflow enables the automatic synchronization and publication of video content across multiple major social media platforms, supporting nine platforms including Instagram, YouTube, and TikTok. By integrating Blotato's API, users can upload videos with a single click, significantly reducing manual operations and improving publishing efficiency. This workflow aims to address the cumbersome and inefficient processes faced by content creators and social media operators during multi-platform publishing, ensuring that videos are released simultaneously at the optimal time, thereby enhancing dissemination effectiveness and management convenience.

This workflow automates the synchronization of potential customer information collected from Typeform forms to the Pipedrive customer management system, significantly enhancing the efficiency of lead management. It addresses the manual operation issues in traditional data import through automatic formatting, field mapping, and multi-entity creation, ensuring data accuracy. Additionally, it intelligently maps company size to custom attributes in Pipedrive, helping the sales team obtain high-quality lead information in a timely manner, facilitating precise follow-up and conversion.

This workflow aims to automate the management of Spotify users' music data by regularly fetching user playlists and favorite songs on a monthly basis. It combines audio feature analysis and artificial intelligence for multidimensional classification. New songs will be recorded in Google Sheets to avoid duplicate archiving and will be intelligently updated in personalized playlists. Through this process, users can efficiently organize and archive their music, enhancing the personalization and professionalism of their playlists, and enjoy a higher quality music experience.

This workflow provides an intelligent movie recommendation service by integrating OpenAI's Chat model with a MongoDB database. Users can input natural language, and the system can automatically generate queries to accurately retrieve high-quality movies rated 5 stars. Additionally, users can save their favorite movies to the database, enhancing the personalized recommendation experience. This workflow simplifies the complexity of traditional recommendation systems, allowing users to easily obtain and manage movie recommendations without needing to understand query syntax, thereby improving the flexibility and accuracy of interactions.

This workflow utilizes AI technology to automatically screen and score candidates' resumes, intelligently matching and analyzing resumes against job descriptions to generate compatibility scores and interview recommendations. At the same time, it automatically sends confirmation emails to candidates and records the information and scores in Google Sheets for easy HR management. This system effectively reduces the time and misjudgments associated with manual initial screening, improving recruitment efficiency and accuracy, particularly suitable for handling a large volume of resumes for technical positions.