Google Page Entity Extraction Template

This workflow can automatically extract text from newly uploaded PDF files and images in a specified Google Drive folder, using Google Vertex AI and Openrouter AI for intelligent recognition and analysis. The extracted transaction data will be converted into a CSV file with classification information and automatically uploaded back to Google Drive, thereby streamlining the manual data entry and classification process, improving the efficiency and accuracy of data processing, and making it suitable for various scenarios such as financial management and data analysis.

This workflow can automatically receive and process multiple vectors, ensuring the consistency of input data dimensions. It calculates the centroid of these vectors, which is the average value across all dimensions, and returns the results in a user-friendly format. It effectively addresses common issues in multidimensional data processing and is applicable in fields such as data analysis, machine learning, and geographic information systems, enhancing the automation and accuracy of data processing.

This workflow builds an intelligent dialogue assistant that combines natural language processing with database management, allowing users to query and analyze data using natural language without needing to master SQL skills. It can dynamically generate SQL queries, retrieve database table structures, process JSON data, and provide clear and understandable feedback on query results. This tool significantly lowers the barrier to database operations and is suitable for scenarios such as internal data analysis, customer service, product support, and education and training, enhancing the convenience and efficiency of data querying.

This workflow automates the scraping and analysis of employee review data from Glassdoor, utilizing AI technology to deeply analyze company ratings and the differences in workplace experiences among various demographic groups. It calculates statistical indicators and generates visual charts. It helps HR and management quantify workplace discrimination, supports fair improvement measures, promotes organizational culture enhancement and inclusivity assessments, and enables the effective implementation of data-driven diversity, equity, and inclusion initiatives.

This workflow automates the retrieval of JSON files from the latest emails in Gmail and converts them into CSV format spreadsheets. It efficiently extracts binary JSON data from emails, automates the handling of email attachments, and eliminates the need for manual downloading and organizing, significantly enhancing data processing efficiency and reducing human errors. It is suitable for businesses and data analysts to quickly archive and analyze email data in their daily work, supporting data-driven decision-making.

This workflow automates the synchronization of video links from a YouTube channel to Google Sheets, providing an efficient and convenient management solution for content creators and data analysts. Users can input the channel ID into a designated spreadsheet, and the system will call the YouTube API to retrieve the latest video data. The data is then formatted and written into another spreadsheet, supporting both addition and update operations, ensuring the timeliness and accuracy of the data. This greatly simplifies the tedious process of manually collecting and organizing video links.

This workflow implements the automated synchronization and export of Shopify customer data, effectively addressing the API pagination limitation issue. It extracts and merges all customer information from Shopify, which can be triggered either on a schedule or manually, and updates it in real-time to Google Sheets for easier management and backup. Additionally, it automatically generates CSV files that meet Squarespace import requirements, significantly reducing the time spent on manual processing and improving the efficiency of multi-platform data management.

This workflow automatically checks the specified Google Sheets every 45 minutes to detect newly added data in real-time. Once new entries are found, the system sends an instant notification via Mattermost, including the ID, name, and email of the new data. This process significantly enhances the efficiency of data monitoring and addresses the cumbersome issue of data personnel manually checking the spreadsheet. It is suitable for teams that require quick responses to customer information updates, such as sales and customer service.