This workflow automatically determines the emotional tendency of user feedback by collecting it and conducting sentiment analysis. Positive feedback is synchronized to the Notion database for easy management and tracking, while negative feedback creates a Trello task for subsequent handling. Additionally, relevant team members are notified via Slack to ensure timely communication of information. This efficient feedback management approach significantly enhances the team's response speed and collaboration efficiency, making it suitable for organizations that require multi-channel feedback management.

This workflow automates the quick duplication of transaction item details on the HubSpot platform. When a deal is marked as "closed" and a related deal is created, the system automatically copies the item details to the new deal, reducing manual entry errors. Additionally, the team is instantly notified via Slack of the successful duplication, enhancing work efficiency and data consistency, making it suitable for sales teams and CRM administrators.

This workflow is manually triggered and automatically executes the creation of database tables, data setup, and query operations, simplifying the database management process. Users only need to click "Execute" to quickly complete table structure definition, data assignment, and data retrieval, enhancing efficiency and reducing human errors. It is suitable for scenarios such as database development and testing, as well as data initialization validation, helping technical teams efficiently build and query database tables while minimizing operational risks.

This workflow automatically processes user-uploaded logo images using AI technology, intelligently extracting tool names, attributes, and similar tool information, and synchronizing the structured data to an Airtable database. It supports the automatic creation and updating of records, ensuring data uniqueness and integrity, significantly improving data organization efficiency. It is suitable for market research, product management, and data collection and management within the AI ecosystem. Users only need to upload images to achieve automated data processing and management.

This workflow is triggered either by a timer or a webhook to automatically clean up package label data in the database that is older than one month and has a status of "TRANSPORTE-RECEBIDO." It sends a notification to Telegram upon completion of the cleanup. This effectively addresses the issue of data accumulation for logistics package labels, prevents database redundancy, and ensures a tidy data environment. It is suitable for industries such as logistics and warehousing, enhancing operational efficiency, reducing manual operations, and achieving automation in data management with real-time notifications.

This workflow is manually triggered to automatically call the well-known Hunter API to verify a specified email address, quickly assessing its validity and availability. It simplifies the email verification process, helping users avoid email delivery failures and resource waste due to invalid email addresses in scenarios such as marketing, customer relationship management, and recruitment, thereby enhancing the communication efficiency and marketing effectiveness of the business.

This workflow implements automatic notifications via a DingTalk group bot when a Pull Request is created in Azure DevOps, ensuring that relevant reviewers are promptly informed of code changes. It maintains user mapping relationships through a MySQL database, supports Markdown format for notification content, and offers a high degree of customization, enhancing team collaboration efficiency. This helps avoid delays or omissions in information transmission, ensuring the timeliness and transparency of code reviews. It is suitable for development teams that need to respond quickly to code merge requests.

This workflow automates the creation and updating of data in the FileMaker database. Users only need to manually trigger it once to complete the addition, deletion, modification, and querying of records, significantly improving the efficiency of database management. It addresses the cumbersome issues of manual data entry and modification in traditional data management, making it suitable for business scenarios that require frequent updates of customer or product information. This reduces operational errors and time consumption, helping businesses achieve a more intelligent office workflow.

This workflow can automatically monitor a specified folder for new documents, extract content in real-time, and generate intelligent summaries. By using various preset templates and leveraging AI for multi-turn Q&A, it automates the creation of learning and reporting notes, ultimately exporting and storing the generated documents. This process effectively enhances document processing efficiency and addresses the challenges of information organization and knowledge extraction, making it suitable for multiple scenarios such as education, corporate knowledge management, sales support, and research analysis.

This workflow is designed to automate the screening and enrichment of real estate leads. By calling a bulk data API, the system can retrieve property information based on custom criteria and use skip tracing technology to complete the owner's contact information. The generated client data will be exported as an Excel file and synchronized with the CRM system, while a report email will be sent to notify relevant personnel. This process supports both manual and scheduled automatic execution, significantly enhancing the efficiency and accuracy of lead generation, thereby assisting real estate investment and marketing teams in achieving more effective customer management.

This workflow is designed to efficiently collect and manage user product feedback. After collecting feedback data through Typeform, it automatically organizes and stores the information in an Airtable database. For feedback with a score higher than 7, it automatically creates Trello tasks, facilitating timely follow-up by the team, thereby improving the efficiency of feedback processing and ensuring a quick response to customer voices. This process is suitable for product teams, customer service, and project managers, helping them systematically manage user feedback and enhance product iteration and customer satisfaction.

This workflow builds an intelligent AI chat agent that allows users to converse with it in natural language to query and analyze website data from Google Search Console in real time. Leveraging OpenAI's intelligent conversational understanding and the historical memory storage of a Postgres database, users can easily obtain accurate data reports without needing to understand API details. Additionally, the agent can proactively guide users, optimizing the data querying process and enhancing user experience, while supporting multi-turn conversations to simplify data analysis and decision-making processes.

This workflow automatically generates new SEO keywords by calling the Google Ads API and retrieves data such as monthly search volume, bid price range, and competition level. It efficiently processes keyword data and ultimately updates the results to Google Sheets for easier analysis and management. This process is suitable for digital marketing teams, advertisers, and content creators, helping them quickly identify potential keywords, enhance promotional effectiveness, and address the issue of low efficiency in manual keyword discovery.

This workflow automatically collects and summarizes detailed statistical data from all workflows, generating a structured JSON format, which is then rendered into an interactive HTML dashboard using an XML template. Users can intuitively view the total number of workflows, their activation status, trigger counts, and the usage of various nodes, tags, and Webhooks, thereby enhancing management efficiency and avoiding resource waste. It also supports custom data presentation in BI tools, facilitating team collaboration and optimizing the design of automated processes.

This workflow integrates web scraping, intelligent search, and language processing technologies to achieve automated web data search, extraction, and summarization functions. Users can quickly obtain key information and utilize Webhook for result push notifications, significantly enhancing information retrieval efficiency. It is suitable for market research, content monitoring, and data-driven decision-making, providing analysts, product managers, and developers with an efficient solution that facilitates the convenience and quality of information processing.

This workflow automatically creates Zoom meetings through a manual trigger, streamlining the meeting scheduling process. Users can generate meeting links quickly with just one click, without the need to log into the Zoom client, thereby enhancing work efficiency. This feature is particularly suitable for remote working teams, sales personnel, and educational institutions, helping them save time and reduce operational costs when organizing online meetings, achieving automation in meeting creation.

This workflow utilizes advanced multimodal AI technology to achieve precise recognition and localization of target objects within images. Users can quickly detect specific objects and automatically draw bounding boxes through natural language descriptions, simplifying the cumbersome processes of traditional object detection. It is suitable for various scenarios such as intelligent image labeling, rapid identification, and anomaly monitoring, providing developers and business analysts with a flexible and efficient image processing solution.

This workflow is designed to automatically retrieve complete information about specified tasks from Monday.com, including all data related to main tasks, sub-tasks, and associated tasks. Through multi-level data scraping and integration, it ultimately outputs a well-structured JSON format data, facilitating subsequent processing and analysis. It effectively addresses the cumbersome and error-prone issues of manual data collection, enhancing the efficiency and accuracy of data retrieval, and is suitable for scenarios such as project management, report generation, and data integration.

This workflow automatically uploads specified video files to Google Drive by calling the Google Apps Script interface, and renames them uniformly after the upload. It addresses the cumbersome nature of the manual upload process and the inconsistency in naming, thereby improving efficiency. It is suitable for content creators and business users, achieving automation in video file management and reducing repetitive tasks and human errors.

This workflow is designed to monitor and manage new contact information on the Keap platform in real-time, automatically triggering events to capture newly added customer data. Through automation, users can quickly respond to changes in customer information, enhancing sales and customer service efficiency while reducing the risks of information delays and omissions. It is suitable for sales teams, customer service departments, and technical teams that need to stay updated on customer dynamics, facilitating efficient synchronization and intelligent management of customer data.

This workflow automatically reads email data from Airtable and validates its effectiveness using the Mailcheck service to determine whether the MX records of the emails exist. The validation results are updated in real-time back to Airtable, enabling dynamic verification and synchronization of data. This effectively enhances the quality management of email data, reduces email sending failures caused by incorrect information, and subsequently improves the marketing efficiency and communication effectiveness of the enterprise. It is particularly suitable for teams and companies that require email data maintenance.

This workflow focuses on the automated management of Todoist tasks, primarily achieving the automatic "snoozing" and "waking" of tasks. By intelligently recognizing task deadlines, the system can automatically migrate tasks between the "Inbox" and "Snooze" projects, ensuring that users are not distracted by tasks that are prematurely interrupted while still receiving timely reminders for pending matters. This process enhances the efficiency and accuracy of task management, making it suitable for individuals and teams that need to handle task timing flexibly.

This workflow implements automated digital public relations news trend mining and analysis. It can regularly monitor trending topics on Reddit, filter high-quality posts, and capture comments. By utilizing AI language models for sentiment and content analysis, it ultimately generates structured analytical reports, which are stored in Google Drive and communicated to the team via Mattermost, enhancing information delivery efficiency. This system helps the PR team quickly identify hot topics, gain deeper insights into public opinion dynamics, and optimize PR strategies and decision-making.

This workflow is an intelligent stock analysis agent. Users send stock codes and chart style requests via Telegram, and the AI automatically generates technical charts and conducts in-depth analysis, covering indicators such as candlestick patterns, MACD, and RSI. The analysis results are ultimately presented in an easy-to-understand manner. It supports voice-to-text conversion and stock code storage for convenient batch analysis later on. The entire process is highly automated and efficient, allowing users to quickly obtain professional stock technical analysis reports.