This workflow automatically extracts and processes sales call records through integration with Salesforce and Gong, filtering for the latest call data and converting it into a standardized JSON format. It regularly retrieves call information from the past four hours, filtering for valid calls to ensure efficient data utilization. Ultimately, the organized data will be passed to the AI processing module for intelligent analysis of sales data, helping the sales team improve performance and customer satisfaction.

This workflow automatically scrapes the latest job information from LinkedIn through the Bright Data platform and synchronizes the cleaned data to Google Sheets. Users only need to submit job search parameters, and the system can retrieve and organize job data in real-time, addressing the cumbersome nature of manual information collection and the complexity of data formats. It is suitable for job seekers, sales and marketing personnel, and HR teams, helping them quickly obtain accurate recruitment updates and improve work efficiency and decision-making quality.

This workflow automatically retrieves order data from the Shopify store every week, quickly calculates the total number of orders and total sales, and records the results in Google Sheets. At the same time, it sends sales report notifications via Slack to help the team stay updated on business dynamics in real-time. This process eliminates the cumbersome traditional manual statistics, ensuring data accuracy and timeliness, making it suitable for e-commerce operations teams, sales analysts, and finance personnel, thereby enhancing work efficiency and team collaboration.

This workflow automatically captures users' running, swimming, and cycling activities by real-time monitoring of Strava's sports data, and conducts in-depth analysis using advanced AI models. It provides users with personalized training feedback and improvement suggestions, helping athletes accurately identify their strengths and weaknesses and develop scientific training plans. Ultimately, the analysis results are sent in a structured HTML format via email or WhatsApp, ensuring that users receive efficient exercise guidance in a timely manner, enhancing their training effectiveness and motivation.

This workflow automatically processes uploaded PDF files by listening to events from the Baserow table. It utilizes an AI language model to extract key information from the PDFs and populates the corresponding fields in the table, supporting dynamically defined extraction rules for intelligent data entry. This process significantly improves data processing efficiency, reduces manual operations and errors, and is suitable for document management scenarios such as contracts and invoices, aiding in the digital transformation of enterprises.

This workflow automates the retrieval of detailed data for main project items and their sub-items from Monday.com, recursively obtaining associated contact information and structuring the data. It supports converting the results into JSON format for easy subsequent upload or export. With a flexible process design, users can efficiently handle multi-level task data, avoiding manual queries and enhancing project management transparency and collaboration efficiency. It is suitable for teams and analysts who need to export or integrate data in bulk.

This workflow is triggered at regular intervals and automatically retrieves real-time location data of the International Space Station every minute, including latitude, longitude, and timestamps. It features an intelligent deduplication function to ensure that the output trajectory points are the most recent and unique, preventing duplicate records and thereby enhancing the accuracy and timeliness of the data. It is suitable for aerospace research institutions, educational projects, and aerospace enthusiasts, enabling efficient monitoring and analysis of the dynamics of the International Space Station.

This workflow is designed to automatically monitor competitors' pricing information. It begins by retrieving pricing page links from Google Sheets and uses intelligent extraction tools to analyze prices and features. By comparing with historical data, it identifies price changes in real time and feeds the updated information back into Google Sheets. Additionally, it notifies the team via Slack to ensure timely awareness of market dynamics. This process effectively reduces manual checking time, improves data flow efficiency, and helps businesses quickly adjust strategies to enhance market competitiveness.

The main function of this workflow is to automate the comparison of two datasets, allowing for the identification of common items, differences, and unique items. It supports multiple output options, facilitating subsequent data processing and in-depth analysis. With a streamlined design, users can quickly generate datasets and perform comparisons, enhancing the efficiency and accuracy of data verification. It is suitable for scenarios such as data analysis, quality checks, and cross-department collaboration. This is an efficient tool that helps users easily master data comparison techniques.

This workflow enables the batch reading, deduplication, filtering, and date sorting of multiple CSV files, and automatically imports the processed data into Google Sheets. It supports the identification and integration of the latest subscriber data, significantly improving data processing efficiency and addressing the time-consuming and error-prone issues of traditional manual processing. It is suitable for fields such as marketing, data analysis, and content operations, helping teams stay updated on user subscription status in real-time, and supporting informed decision-making and strategy formulation.

This workflow regularly retrieves website keyword ranking data from the SERPBear platform, automatically parses it, and generates a summary of keyword performance. The data is then sent to an AI model for in-depth analysis, and the results are finally saved to a Baserow database. The purpose is to help website operators and SEO practitioners efficiently monitor changes in keyword rankings, identify well-performing and under-optimized keywords, thereby enhancing the scientific accuracy of SEO decision-making and reducing the workload of manual analysis.

This workflow automates the processing of transaction receipt images received by a LINE chatbot. By uploading the images to Google Drive and using OCR technology to recognize the information within them, the system can accurately extract transaction details and automatically record the data in Google Sheets. This process significantly enhances the efficiency and accuracy of manual data entry, addressing the challenge of structuring image information for storage. It is suitable for scenarios where efficient management of transaction receipts is needed, such as in finance departments, individuals, and small businesses.

This workflow automatically converts webpage content from HTML format to structured Markdown and extracts all links from the webpage. Users can batch process multiple URLs, and the system will automatically manage API request rate limits to ensure efficient and stable data scraping. The workflow is flexible, supporting the reading of URLs from a user database and outputting the processing results to a specified data storage system, making it suitable for scenarios such as content analysis, market research, and website link management.

This workflow utilizes advanced AI language models and web data scraping technologies to automate the research and structuring of corporate information. Users can process lists of companies in bulk, accurately obtaining various key information such as company domain names, LinkedIn links, and market types. The results are automatically updated to Google Sheets for easier management and analysis. This system significantly enhances data collection efficiency, addressing issues of incomplete information and outdated updates commonly found in traditional manual research. It is suitable for scenarios such as market research, sales lead generation, and investment due diligence.

This workflow automatically scrapes and analyzes LinkedIn profiles to extract key information and calculate ICP scores, enabling precise evaluation of sales leads and candidates. Users only need to manually initiate the workflow, and the system can automatically access LinkedIn, analyze the data, and update it to Google Sheets, achieving a closed-loop data management process. This significantly improves work efficiency, reduces manual operations, and ensures the timeliness and accuracy of information, making it suitable for various scenarios such as sales, recruitment, and market analysis.

This workflow automates the retrieval of website traffic data from Google Analytics and conducts a two-week comparative analysis using AI, generating SEO reports and optimization suggestions. After intelligent data processing, the results are automatically saved to a Baserow database, facilitating team sharing and long-term tracking. It is suitable for website operators and digital marketing teams, enhancing work efficiency, reducing manual operations, and providing data-driven SEO optimization solutions to boost website traffic and user engagement.

This workflow demonstrates how to flexibly handle date and time data, including operations such as addition and subtraction of time, formatted display, and conversion from ISO strings. Users can quickly calculate and format time through simple node configurations, addressing common date and time processing needs in automated workflows, thereby enhancing work efficiency and data accuracy. It is suitable for developers, business personnel, and trainers who require precise management of time data, helping them achieve complex time calculations and format conversions.

This workflow automates the retrieval and updating of the latest market prices for cryptocurrency portfolios, calculates the total value, and saves the data to Airtable. It runs automatically every hour, ensuring that users stay updated on asset dynamics in real time, while reducing the errors and burden associated with manual updates. By calling the CoinGecko API, the workflow effectively addresses the challenges posed by cryptocurrency price volatility, making it suitable for investors, financial analysts, and any teams or individuals managing crypto assets, thereby enhancing the efficiency and accuracy of data maintenance.

This workflow quickly and batch retrieves customer data from Zoho CRM through a simple manual trigger. Users only need to click the "Execute" button to automatically call the API and pull customer information in real-time, eliminating the cumbersome manual export steps and significantly improving data retrieval efficiency. It is suitable for various roles such as sales, marketing, and customer service, ensuring the timeliness and completeness of data, and supporting the digital transformation of enterprises.

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 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 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 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 automatically extracts information from the customer data repository, formats it, and synchronizes it to Google Sheets for efficient data management. Field adjustments are made through the "Set" node to ensure the data meets requirements, avoiding errors that may occur during manual operations. This process addresses the issues of scattered customer data and inconsistent formatting, making it suitable for marketing and customer service teams. It helps them update and maintain customer information in real-time, enhancing data accuracy and operational efficiency.