The workflow is called Email Domain Extraction Assistant, designed to automatically extract and output the domain part of email addresses. Using simple string processing techniques, this tool can quickly separate the domain after the "@" symbol, significantly enhancing the efficiency of data organization and analysis. It is particularly suitable for scenarios such as customer information management, marketing automation, and data cleansing. Data analysts, marketers, and automation engineers can all benefit from it, saving time and reducing error rates.

This workflow integrates multiple systems through automation to generate and publish social media content. It retrieves topics to be published from Google Sheets, utilizes AI models to generate original content and visual materials, ensuring they align with the characteristics of the target platforms. After publication, the system automatically updates the status to avoid content duplication, significantly enhancing creative efficiency and the convenience of content management, making it highly suitable for social media marketing teams and brand promotion companies.

This workflow provides an intelligent, multi-turn, contextually relevant conversational experience by integrating advanced AI language models and real-time search tools. It can respond to user inquiries in real time, maintain the context of the conversation, and effectively address the issues of information timeliness and comprehension that traditional chatbots face. It is suitable for scenarios such as intelligent customer service, knowledge Q&A, and online consultations, significantly enhancing user interaction experience and the level of service intelligence.

This workflow achieves fully automated processing from automatically capturing images from the web to text content recognition and result storage. Utilizing a powerful image text detection service, it accurately extracts text from images, and after formatting, automatically saves the recognition results to Google Sheets for easy management and analysis. This process significantly enhances the efficiency and accuracy of image text processing, making it suitable for businesses and individuals that need to handle large volumes of image text information. It is widely used in fields such as market research and customer service operations.

This workflow significantly enhances order fulfillment efficiency by automating the querying and processing of pending orders on the Squarespace platform. It can automatically filter eligible orders and generate fulfillment records while notifying customers, addressing the cumbersome and inefficient issues of traditional manual processing. This solution is particularly suitable for merchants selling digital products, helping them achieve efficient and rapid order management, thereby improving customer satisfaction.

This workflow aims to simplify the process of reading user data from Google Sheets and inviting new users through no-code automation. It automatically compares existing user information, filters out unregistered users, and sends invitation emails via API. It supports both manual and scheduled triggers, significantly enhancing user management efficiency while reducing repetitive tasks and errors. Additionally, it ensures accurate data synchronization, making it suitable for teams or enterprises and optimizing the user invitation process.

This workflow automatically converts text content submitted by users into high-quality audio files via a Webhook interface, utilizing OpenAI's text-to-speech functionality for real-time responses. The entire process requires no manual intervention, supports customizable voice parameters, and is easy to operate. It is suitable for scenarios such as content creation, corporate customer service, and the education industry, significantly improving audio production efficiency, lowering technical barriers, and meeting diverse automation needs.

This workflow allows users to upload images containing multiple logos through a form. It utilizes AI technology to automatically recognize and extract information about tools, software, or products, such as names, attributes, and competitor relationships. The extracted data is then structured and automatically synchronized to an Airtable database, reducing the time and errors associated with manual data entry and improving the accuracy and efficiency of data management. It is suitable for teams such as product managers and market analysts who need to quickly organize and maintain tool information, significantly enhancing the convenience and automation of information processing.

This workflow is designed to receive and respond to security incident updates on TheHive platform in real time, addressing the inefficiencies of traditional manual monitoring. By subscribing to all events and automatically capturing notifications, it ensures that critical security dynamics are not overlooked. It is suitable for cybersecurity operations and incident response teams, significantly enhancing the speed and accuracy of incident handling and improving the overall efficiency of security operations.

This workflow is primarily used for the automated management and adjustment of the "Close Date" field. It intelligently assesses the validity of the date format and dynamically sets the close date. If the format is correct, the original date remains unchanged; if the format is incorrect, it automatically postpones the date by three weeks, thereby ensuring data accuracy and timeliness. It is suitable for scenarios such as sales management and project progress tracking, effectively reducing manual intervention, improving time management efficiency, and preventing work delays caused by date issues.

This workflow is designed to automate the collection and analysis of website traffic data. It retrieves key traffic metrics by calling the Umami tool and uses artificial intelligence to generate easily readable SEO optimization suggestions. The final analysis results are saved to the Baserow database. This process supports scheduled triggers and manual testing, helping website administrators, SEO experts, and data analysts efficiently gain data insights, reduce manual workload, and enhance decision-making efficiency. It is suitable for users looking to achieve intelligent data processing.

This workflow is an efficient tool for detecting anomalies in agricultural crops, capable of automatically identifying whether crop images are abnormal or unknown. Users only need to provide the URL of the crop image, and the system converts the image into a vector using multimodal embedding technology, comparing it with predefined crop category centers to determine the image category. This tool is suitable for scenarios such as agricultural monitoring, research data cleaning, and quality control, significantly improving the efficiency and accuracy of crop monitoring.

This workflow automates the conversion of JPG or PNG image formats to the more efficient WEBP format, enhancing image processing efficiency. By integrating the APYHub API, the workflow batch retrieves image URLs from Google Sheets, completes the format conversion, and uploads the newly formatted images to Google Drive. This simplifies the management process, ensures uniformity in image formats, reduces file sizes, and helps improve webpage loading speed and user experience, making it ideal for content managers, designers, and marketing teams.

This workflow is designed to automatically capture and record system errors while controlling the frequency of error notifications through database statistics to avoid excessive email alerts. It saves error information to a Postgres database and supports flexible integration into existing processes. Additionally, the workflow provides an automatic cleanup feature for error logs, ensuring a tidy development environment. It is suitable for automated systems that require centralized management of errors and monitoring notifications, enhancing the efficiency and responsiveness of error handling.

This workflow listens for comment events on GitLab merge requests through a Webhook, automatically retrieves code changes, and analyzes the differences. It uses an intelligent language model to review and score each change, generating professional review suggestions, which are then posted back to GitLab as comments, creating a fully automated code review process. This process significantly enhances the efficiency and quality of code reviews, reduces the risk of human oversight, and is suitable for CI/CD processes in software development teams and the maintenance of open-source projects.

This workflow receives user chat messages and utilizes an AI intelligent agent combined with a web search API to achieve real-time information retrieval and intelligent Q&A. Leveraging the GPT-4o-mini model, it supports contextual memory, enhancing the coherence and accuracy of continuous conversations. It addresses the issue of traditional AI models being unable to access real-time data, making it suitable for customer service robots, intelligent assistants, and scenarios that require quick access to external information, significantly enhancing the user interaction experience.

This workflow is manually triggered and automatically connects to the customer service system to quickly retrieve and synchronize all email data from a specified mailbox. It helps the customer service team and operations personnel easily manage emails, avoiding manual operations and improving the efficiency and accuracy of data access. It is suitable for unified management and analysis of customer service emails, email data synchronization, and automated workflows, enhancing work efficiency and customer response speed.

This workflow integrates the appointment event trigger mechanism of Acuity Scheduling to capture user appointment actions in real-time, enabling automated responses and subsequent processing. It addresses the issue of insufficient real-time interaction between traditional appointment systems and other business systems, ensuring that every appointment information is instantly acquired and drives subsequent processes. This is suitable for businesses and service providers that require automated handling of appointment information. This workflow provides an efficient foundation for intelligent appointment management.

This workflow integrates the WhatsApp message Webhook with an AI question-and-answer agent, utilizing retrieval-augmented generation technology to build an intelligent customer service chatbot. It can receive customer inquiries in real-time, leveraging the company's internal knowledge base and advanced AI models to provide accurate product consultations and technical support. This system not only reduces the pressure on human customer service representatives but also ensures the professionalism and accuracy of the responses, enhancing the customer experience and making it suitable for the automated customer service needs of various enterprises.

This workflow aims to automate the tracking of the latest artificial intelligence funding opportunities by regularly scraping and filtering relevant information. It utilizes AI technology to assess eligibility and eliminate duplicate data. By saving key information to an Airtable database and generating well-designed email notifications that are promptly sent to subscribers, it significantly enhances the team's response speed to funding opportunities, saves time on manual filtering, ensures the timeliness and uniqueness of the information, and supports research institutions and startup teams in securing funding.

This workflow helps users create customized AI assistants for specialized Q&A on specific topics by retrieving files from Google Drive and uploading them to the OpenAI platform. Users can engage in real-time chat with the assistant to receive accurate answers based on the uploaded documents, enhancing information relevance and user experience. It is suitable for scenarios such as event consulting, corporate knowledge bases, and customer support, and supports multi-channel expansion to meet diverse needs. The overall process is efficient and straightforward, significantly improving service quality.

This workflow automates the processing of sales call recordings, utilizing AI technology to extract key information and store it in a structured manner within a database, achieving intelligent management of sales call data. It supports batch processing and has a fault tolerance mechanism to ensure that incomplete tasks are retried during API rate limiting. Additionally, it provides real-time updates on processing progress and completion notifications in team communication tools, enhancing collaboration efficiency. This workflow is suitable for sales teams to efficiently manage and analyze call data, promoting improved sales performance and customer relationship optimization.

This workflow can automatically read and convert data from local JSON files, and then append it to a specified Google Sheets spreadsheet. Through secure OAuth2 authentication, it ensures the safety of data operations, greatly simplifying the data import process, avoiding cumbersome manual tasks, and enhancing the efficiency and accuracy of data processing. It is suitable for businesses and individuals who need to regularly organize and analyze data, helping to achieve efficient data management and decision-making.

This workflow implements intelligent image object recognition and management by automatically downloading source images and using AI models to identify objects within them. After identifying objects with a confidence level higher than 0.9, the system crops the target images and uploads them to cloud storage, while indexing the relevant metadata into an Elasticsearch database. This process enhances the retrieval accuracy of image resources and is suitable for scenarios such as e-commerce, media management, and intelligent monitoring, helping users efficiently search and categorize large volumes of images.