This workflow automatically retrieves legislative procedure data from the European Parliament's official website for the past 18 days, using advanced AI technology to intelligently filter topics related to environmental sustainability. The filtered results will be stored in Google Sheets, and Google task reminders will be generated for each relevant topic to help users efficiently track and manage legislative developments. This process significantly enhances information processing efficiency, ensuring that users can stay updated on key sustainable development policies in a timely manner.

This workflow automatically generates prompts that meet AI model requirements by receiving user queries, and it calls relevant APIs for in-depth content retrieval, extracting and outputting concise, structured answers. It can provide authoritative materials with citations, ensuring the professionalism and credibility of the results. This helps users quickly access the latest research materials in a specific field, enhancing information retrieval efficiency and content quality. It is applicable in various scenarios such as academic research, content creation, and industry analysis.

This workflow focuses on the verification of email address validity by integrating a professional email verification tool to detect the availability of email addresses in real-time. It ensures the success rate of email marketing and user registration. It effectively reduces email sending failures and information loss, making it suitable for email list cleaning, verification during user registration, and email validation in CRM systems. It is designed for marketers and operations personnel to enhance email delivery quality and ensure the accuracy of business data.

This workflow can regularly extract upcoming schedule events from the user's Outlook calendar and automatically sync them to a Notion database. It supports adding and updating events, ensuring that the information in Notion remains consistent with Outlook, thus avoiding errors and omissions caused by manual synchronization. Through this automated process, users can efficiently manage personal or team schedules, enhancing work efficiency and data consistency, and addressing the issue of information silos.

This workflow combines advanced AI language models with the Notion knowledge base to provide intelligent Q&A services. Users can input questions, and the system will automatically retrieve relevant content and generate accurate answers, along with links to Notion pages, ensuring the reliability and traceability of the information. This assistant enhances the efficiency of knowledge queries and is suitable for various scenarios such as internal knowledge management in enterprises, customer support, and personal information retrieval, helping users quickly access the information they need.

This workflow automatically captures error events in the automation process and sends detailed error report emails to designated recipients via Gmail in real-time. The email content includes the workflow name, error information, the last executed node, and the error stack, helping to quickly locate the issue. This mechanism significantly enhances operational efficiency, ensuring that relevant personnel are promptly informed of any anomalies. It is suitable for monitoring and alerting various automation tasks, supporting the stable operation of internal processes within the enterprise.

This workflow implements automatic replies and proactive push notifications through the LINE Messaging API. It can receive user messages and respond in real-time, while also supporting manual notifications to specific users. By utilizing Webhooks and conditional logic, it effectively filters message types, processing only valid message events, which enhances service response speed and user experience. It is suitable for scenarios such as customer service automatic replies, event notifications, and testing and development, helping businesses and developers efficiently build messaging interaction systems.

This workflow provides an intelligent personal shopping assistant feature for e-commerce platforms by integrating language models and retrieval-augmented generation technology. It can automatically identify users' shopping needs, accurately extract product search information, and match relevant products in the WooCommerce database. Additionally, for non-shopping inquiries, the system offers intelligent responses based on a knowledge base, enhancing the user experience. Through context management, it ensures the continuity of conversations, significantly improving customer satisfaction and service efficiency.

This workflow receives customer feedback through a Webhook, utilizes AI to intelligently analyze the feedback content, and automatically generates a summary report and social media promotional copy. The summary report is then sent to the team via email, while the promotional copy is sent to a designated chat group on Telegram. This automation and intelligence in feedback processing effectively enhance the analysis and dissemination of customer feedback, helping the company respond to customer needs more quickly and optimize its services.

This workflow is primarily used to automatically import concert data from local CSV files into a MySQL database. With a simple manual trigger, the system reads the CSV file and converts it into spreadsheet format, followed by batch writing to the database, achieving seamless data migration. This process not only improves data processing efficiency but also reduces errors associated with traditional manual imports, making it suitable for various scenarios such as music event management and data analysis.

This workflow utilizes automated browser technology and AI models to achieve intelligent web data scraping and analysis. It supports data collection in both logged-in and non-logged-in states, automatically searching for and filtering valid web links, extracting key information, and performing image analysis. Additionally, it has a built-in multi-layer error handling mechanism to ensure the stability of the scraping process. It is suitable for various fields such as data analysis, market research, and automated operations, significantly enhancing the efficiency and accuracy of data acquisition.

This workflow combines the Odoo sales module with AI conversational technology to achieve automatic acquisition of sales opportunity data and intelligent interaction. Through the aggregation and analysis of sales data by the AI model, the sales team can quickly grasp key information, enhancing decision-making efficiency and customer communication experience. It supports scheduled data retrieval, generates intelligent summaries, and enables real-time chat interactions, helping sales personnel efficiently manage sales opportunities and improve customer service quality. It is suitable for various enterprises to enhance digital sales efficiency.

This workflow implements automatic synchronization between Zendesk tickets and Asana tasks, ensuring that when customer service receives a new ticket, it can automatically check whether the corresponding task has been created in Asana. If the task already exists, a comment is added to the task; if it does not exist, a new task is automatically created, and the task ID is written back to the ticket. This process significantly enhances collaboration efficiency between customer service and project management, eliminates information silos, reduces the workload of manual operations, ensures real-time information updates, and facilitates smooth internal communication within the organization.

This workflow receives users' dietary records via Telegram, including text and voice messages. It utilizes AI technology to intelligently analyze the nutritional components of the ingredients and automatically stores the structured data in Google Sheets. It addresses the cumbersome issues of traditional dietary recording, supporting health management, exercise nutrition tracking, and medical rehabilitation, providing users who are concerned about dietary health with a convenient and efficient tool for recording and analysis.

This workflow is manually triggered to quickly read the cached value of a specified key ("hello") from the Redis database, simplifying the data access process. The operation is straightforward and suitable for business scenarios that require real-time retrieval of cached information, such as testing, debugging, and monitoring. Users can easily verify stored data, enhancing development and operational efficiency, making it suitable for developers and operations engineers.

This workflow automatically scrapes the latest articles from the Paul Graham website, extracts and processes the text content, and converts it into vectors stored in the Milvus database. By integrating OpenAI's embedding model, it enables intelligent Q&A and information retrieval based on the knowledge base. It supports manual triggers and chat message triggers for AI responses, making it suitable for researchers, businesses, and content creators, enhancing information management and retrieval efficiency, and streamlining the knowledge base construction process.

This workflow integrates DeepSeek's latest V3 chat model and R1 inference model, supporting real-time conversations triggered by messages and possessing multi-turn contextual understanding capabilities. Users can flexibly call cloud APIs or local models to quickly build intelligent Q&A and inference services, suitable for scenarios such as customer service, knowledge management, and educational tutoring. By enhancing interaction coherence and accuracy through memory window management, it reduces the complexity of AI integration, making it easier for developers and enterprises to build and test intelligent assistants.

This workflow is designed to automate the backup of workflow configurations. Users can trigger it either on a schedule or manually to automatically retrieve all workflow information from the local instance and consolidate it into a JSON file, which is then uploaded to a designated Google Drive folder. This process not only simplifies the backup operation and avoids manual omissions but also ensures data security and traceability, facilitating quick recovery and version management for users, thereby enhancing workflow management efficiency.

This workflow can automatically process YouTube video links provided by users, verify their validity, and extract video subtitles. Through powerful API services and AI models, the extracted text undergoes grammar correction and formatting, ultimately returning clear and readable transcribed content. This process eliminates the need for manual video viewing, allowing learners, content creators, and corporate employees to quickly access the core information of the videos, thereby effectively enhancing learning and work efficiency.

This workflow automatically retrieves the release information of the latest stable version from a specified GitHub repository daily. It converts the release notes from Markdown format to HTML and ultimately sends them via Gmail to designated recipients. This process requires no manual intervention, ensuring that the development team and project stakeholders receive timely updates on version changes, thereby enhancing the efficiency of information dissemination. It is suitable for various scenarios such as software development, product management, and open-source project maintenance.

This workflow automatically monitors WooCommerce order updates in real-time, identifying orders with refund amounts greater than or equal to 100 and pushing the relevant information to a designated Slack channel. This automation significantly enhances the team's response speed to important refund events, reduces the burden of manual monitoring, ensures timely follow-up on high-value refunds, and minimizes the potential for financial risk and delays in customer service. It is suitable for e-commerce operations, customer service, and finance teams that need quick access to refund information.

This workflow builds an intelligent question-and-answer system based on company documents stored in Google Drive, utilizing a vector database and large language models to achieve rapid information retrieval and natural language interaction. By automatically synchronizing document updates, employees can obtain concise and accurate answers related to policies and processes in real time, thereby enhancing knowledge management efficiency, optimizing the self-service experience, and addressing the issues of traditional document fragmentation and retrieval difficulties. It is applicable to various scenarios, including internal knowledge bases, HR policy inquiries, and intelligent retrieval of legal compliance documents.

This workflow is designed to automatically screen and process conference submission applications, filtering high-scoring proposals based on evaluation criteria and generating visual presentation materials. By synchronizing candidate information with project management tools, it helps teams efficiently manage and review content, enhancing review efficiency and collaboration transparency. It is particularly suitable for conference organizers and event management teams, effectively reducing the manual screening workload and achieving an aesthetically pleasing and structured management of application materials.

This workflow automatically reads keywords in bulk from Google Sheets, using an AI intelligent agent to analyze whether each keyword is related to known IT software, services, or tools. The final classification results are then updated back to the spreadsheet. It effectively addresses the inefficiencies and errors of manual analysis while preventing API call frequency limitations, ensuring a stable and efficient process. This workflow is suitable for scenarios such as SEO research, market research, and keyword database management.