Real Estate Market Scanning

This workflow automates the processing of YouTube video links in Airtable. It retrieves video transcription text through a third-party API and utilizes a large language model to generate content summaries and key points. Finally, the structured information is written back to Airtable, enabling efficient organization and management of video content. This process significantly enhances the work efficiency of content creators, knowledge management teams, and market researchers when handling video materials, addressing the issues of manual organization and information fragmentation.

This workflow can automatically crawl user reviews of specified companies from the Trustpilot website, extract key information from the reviews, and perform sentiment analysis. Using the DeepSeek model, it accurately retrieves multidimensional information such as the reviewer's name, rating, date, and more. It then utilizes OpenAI to classify the sentiment of the reviews, achieving automatic collection and intelligent analysis of review data. Finally, the data is synchronized and updated to Google Sheets, providing strong support for brand management, market research, and customer service.

This workflow automatically scrapes Bing Copilot's search results through the Bright Data API and utilizes the Google Gemini AI model for structured data extraction and content summarization. It addresses the issue of disorganized traditional search result data, enhancing information utilization efficiency. Users can quickly obtain search information related to keywords, aiding in market research, competitive intelligence analysis, and content creation. Ultimately, the processed results are pushed via Webhook, facilitating subsequent integration and automation.

This workflow utilizes advanced web scraping and artificial intelligence technologies to automatically capture, extract text, generate summaries, and perform sentiment analysis on the content of specified brand webpages. By overcoming web scraping restrictions, it enables real-time access to high-quality content, systematically analyzes consumer attitudes towards the brand, and provides clear text summaries and sentiment classifications. It is suitable for brand monitoring, market research, and user feedback processing, helping relevant personnel quickly gain deep insights and optimize decisions and strategies.

This workflow automatically monitors a Google Drive folder for new CSV files, and once a new file is detected, it initiates the process. It utilizes OpenAI to intelligently identify personally identifiable information (PII) columns and automatically removes this sensitive data, generating a de-identified file and re-uploading it to the designated folder. The entire process is efficient, intelligent, and requires no manual intervention, effectively reducing the risk of data breaches, making it suitable for businesses and teams that need to process privacy data in bulk.

This workflow utilizes the Google Natural Language API to automatically extract named entities such as people, organizations, and locations from any webpage, enabling structured analysis of information. Users submit the webpage URL via a webhook, and the system automatically fetches the content and performs entity recognition, returning detailed entity information along with its importance score. This tool is particularly suitable for scenarios such as media monitoring, market research, and data integration, significantly enhancing the efficiency and accuracy of information processing and helping users quickly obtain key data.

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.