This workflow enables the automatic import of workflows from local files or remote instances. It supports reading and parsing JSON format files, simplifying the migration process across instances or from local files. Users can select the target workflow and manage credential mapping to ensure the validity and security of the imported credentials. The workflow provides instant feedback, enhancing the user experience, and is particularly suitable for team collaboration, workflow sharing, and batch import scenarios, effectively reducing the risks associated with manual operations.

This workflow automatically receives messages via Webhook and sends them to a designated Telegram chat window, streamlining the process of manually sending messages. It offers an efficient automation solution that can respond to external requests in real time and generate feedback confirmation messages, enhancing the convenience and immediacy of message notifications. It is suitable for IT operations, developers, and teams or individuals who need to quickly push notifications, significantly improving work efficiency.

This workflow utilizes the advanced Google Gemini AI model to automatically process and analyze the content of YouTube videos or playlists. Users simply need to input a link to receive an intelligent summary and in-depth analysis of the video transcription text, saving them time from watching. It supports multi-video processing, intelligent Q&A, and context preservation, enhancing the user experience. Additionally, it incorporates a vector database for rapid retrieval, making video content more structured and easier to query, suitable for various scenarios such as education, content creation, and enterprise knowledge management.

This workflow utilizes automation to monitor customer activities on LinkedIn in real-time, such as job changes and new posts, thereby enhancing the efficiency of the sales team's customer relationship management. It integrates data from HubSpot and LinkedIn, automatically updating customer information to Google Sheets, and notifies the sales manager of key developments via email. This ensures the timeliness and accuracy of customer management, reduces the complexities of manual maintenance, and optimizes the quality of customer service.

This workflow automatically monitors the real-time weather in specified cities, regularly retrieving temperature data to determine if it falls below 25°C. Once the condition is met, the system instantly pushes a low-temperature alert via SIGNL4, including detailed temperature and geographical location information. This process effectively enhances the response speed of low-temperature warnings, helping businesses, organizations, and individuals take timely measures against cold weather, ensuring the safety of equipment and personal arrangements.

This workflow provides a fully automated subscription push service, allowing users to select topics of interest and push frequency through an online form. The system uses AI to automatically generate relevant content and illustrations, which are then sent to subscribers via email at scheduled times. Additionally, a simple unsubscribe process is provided to ensure a smooth user experience. This service is suitable for educational platforms, content marketing, and community operations, aiming to enhance user engagement and personalized experiences.

This workflow is manually triggered to automatically access the Hacker Noon website and scrape the titles and links of all secondary headings on the homepage. Users can quickly obtain the latest article information without manually browsing the webpage, enhancing the efficiency of information collection. It is suitable for scenarios such as media monitoring, content aggregation, and data collection, facilitating content analysis and public opinion tracking. This workflow holds significant application value, especially for content editors, market researchers, and developers.

This workflow combines intelligent AI agents with the OpenAI GPT-4 model to achieve automatic web content scraping and processing. After the user inputs a chat message, the system automatically generates HTTP request parameters, retrieves web content from a specified URL, performs deep cleaning of the HTML, and finally outputs it in Markdown format. It supports both complete and simplified scraping modes, intelligently handles request errors, and provides feedback and suggestions. This workflow is suitable for content monitoring, information collection, and AI question-answering systems, enhancing information retrieval efficiency and reducing manual intervention.

This workflow enables automated personalized AI video generation and status monitoring. Users can easily configure AI avatars, voices, and text content, and the system will automatically send generation requests and poll the status in real-time until the video is completed and a usable link is provided. This process simplifies cumbersome API calls and enhances the efficiency of video content production, making it suitable for businesses, educational institutions, and content creators to quickly generate personalized videos while lowering the technical barrier.

This workflow provides an efficient tool that automatically converts uploaded XML files or data into JSON format, supporting the processing of various request types. With a precise error capture mechanism, alerts are promptly sent to the Slack channel in the event of a conversion failure, ensuring that the operations team can respond quickly. Additionally, it simplifies the data format conversion process, enhancing the productivity of developers and data analysts, making it suitable for scenarios that require real-time monitoring and data processing.

This workflow is mainly used for generating and splitting simulated user data, facilitating subsequent processing. By using custom function nodes, it creates an array containing multiple user information entries and splits them into independent JSON data items. This process addresses the flexibility issues in batch data processing, making it suitable for scenarios such as test data generation, individual operations, and quickly building demonstration data, thereby enhancing the efficiency and controllability of workflow design.

This workflow monitors the creation events of customers in HelpScout in real-time. Once a new customer joins, it immediately triggers notifications and subsequent automated processes. This ensures that the team can promptly receive information about new customers, improving customer management efficiency and avoiding response delays caused by information lag. It is suitable for customer service, sales, and business operations personnel, helping them achieve quick follow-up and management of customer data, thereby enhancing the timeliness and accuracy of services.

This workflow is primarily used for clustering analysis in agricultural crop image datasets. It automates the setting of representative center points (medoids) for clustering and their threshold scores to support subsequent anomaly detection. By combining traditional distance matrix methods with multimodal text-image embedding techniques, it accurately locates clustering centers and calculates reasonable thresholds, enhancing the effectiveness of anomaly detection. It is suitable for applications in the agricultural field, such as pest and disease identification and anomaly warning, ensuring efficient and accurate data processing.

This workflow uses an SSE (Server-Sent Events) trigger to receive event pushes from a specified URL in real-time. It is designed to continuously listen for server events and respond automatically, making it suitable for scenarios that require real-time data updates. The process is straightforward, consisting of only one SSE trigger node, making it ideal for developers, operations personnel, and business teams looking to automate responses to external events. Overall, this workflow helps build real-time monitoring and event-driven automation processes, enhancing response speed and operational efficiency, and can be further expanded to achieve complex automation task chains.

This workflow aims to enhance meeting efficiency by automatically retrieving Zoom meeting data and transcribing recordings. It utilizes AI to generate meeting minutes, extract tasks and to-dos, and intelligently create tasks in ClickUp while scheduling follow-up meetings. The entire process automates the flow from capturing meeting content to task assignment and scheduling, addressing issues such as the cumbersome nature of manually organizing meeting minutes, untimely task distribution, and time-consuming information transfer. It is suitable for organizations with frequent meetings and cross-departmental collaboration.

This workflow automatically analyzes and constructs a dependency graph between workflows, helping users identify the callers of sub-workflows and automatically tagging them. Through visual charts, users can intuitively understand the call frequency and structure between workflows, reducing maintenance costs and preventing operational errors. At the same time, this workflow is suitable for teams and enterprises managing complex automation processes, enhancing workflow management efficiency and ensuring the stability and healthy development of processes.

This workflow automatically backs up all workflow configurations to a specified GitHub repository, ensuring data security and version control. Triggered either on a schedule or manually, the workflow processes configuration files one by one, checking for differences with the files on GitHub and performing the corresponding create or update operations. This process effectively manages workflows, prevents data loss, and saves storage resources, making it suitable for teams and individuals that require regular backups and version management.

This workflow helps businesses quickly obtain and enrich decision-maker information for target companies through automated processing. It is triggered from Google Sheets, utilizing the Apollo API to search for company and contact data, and combines it with OpenAI models to intelligently summarize business information. High-quality contact information is then integrated back into the spreadsheet. Additionally, manual review is conducted via Slack to ensure data accuracy, and potential client reports are generated regularly to enhance the efficiency and data quality of marketing and sales teams.

This workflow effectively extracts and processes contact information by automatically calling the FileMaker Data API. It can parse complex nested data structures and standardize contact data, facilitating subsequent analysis, synchronization, and automation. It is suitable for scenarios such as enterprise customer relationship management and marketing campaign preparation, significantly enhancing data processing efficiency, reducing manual intervention, and helping users easily manage and utilize contact information, thereby strengthening digital operational capabilities.

This workflow provides a convenient method for users to automatically generate RSS feeds in various formats by simply entering the username, ID, or video link of a YouTube channel. There is no need to apply for a Google API or have administrative privileges. It supports multiple formats including ATOM, JSON, and MRSS, covering video content and community dynamics. This makes it suitable for a variety of applications such as content creators, operations personnel, and media monitoring, lowering the barriers to use and enhancing the efficiency of information aggregation and monitoring.

This workflow automatically scrapes the latest content from specified news websites, extracting the publication time, title, and body of the news articles. It then uses AI technology to generate summaries and key technical keywords for each news item, ultimately storing the organized data in a database. This process enables efficient monitoring and analysis of news sources without RSS feeds, making it suitable for various scenarios such as media monitoring, market research, and content management, significantly enhancing the efficiency and accuracy of information retrieval.

This workflow can automatically scrape the latest news articles from specified news websites without relying on RSS subscriptions. It regularly extracts article links, publication dates, titles, and body content, and uses the GPT-4 model to generate brief summaries and extract key technical keywords. The organized structured data will be stored in a NocoDB database, facilitating subsequent retrieval and analysis, significantly improving the efficiency of news monitoring and content management, making it suitable for use by businesses, media, and data analysts.

This workflow implements the storage and management of user conversation history by building an intelligent chatbot based on the Line platform, ensuring continuity and contextual relevance in conversations. Utilizing Google Sheets as a lightweight database, the chatbot can automatically archive chat records and generate polite and friendly responses through advanced AI models, suitable for customer support and intelligent Q&A in the Thai language environment. This system effectively addresses the shortcomings of traditional chatbots in memory and data management, enhancing the user interaction experience.

This workflow implements real-time monitoring and intelligent analysis of emails in corporate mailboxes, automatically identifying potential phishing email risks. By deeply analyzing the email content and header information, it assesses the security of the emails and automatically creates tickets in the Jira system, including email screenshots and body text, thereby enhancing the response efficiency and processing speed of the security team. This solution effectively alleviates the pressure of manual screening, ensuring quick tracking and management of email security incidents, and is suitable for various organizations that require email security risk identification.