CoinMarketCap AI Data Analyst Agent

This workflow automatically processes CSV files exported from Screaming Frog to generate an `llms.txt` file that meets AI training standards. It supports multilingual environments and features intelligent URL filtering and optional AI text classification, ensuring that the extracted content is of high quality and highly relevant. Users simply need to upload the file to obtain structured data, facilitating AI model training and website content optimization, significantly enhancing work efficiency and the accuracy of data processing. The final file can be easily downloaded or directly saved to cloud storage.

This workflow builds an intelligent movie recommendation chatbot that utilizes Retrieval-Augmented Generation (RAG) technology, combining the Qdrant vector database and OpenAI language model to provide personalized movie recommendations for users. By importing rich IMDb data, it generates text vectors and conducts efficient similarity searches, allowing for a deep understanding of users' movie preferences, optimizing recommendation results, and enhancing user interaction experience. It is particularly suitable for online film platforms and movie review communities.

This workflow utilizes an automated intelligent agent to help users efficiently conduct competitor research. Users only need to input the target company's official website link, and the system can automatically identify similar companies, collect and analyze their basic information, products and services, and customer reviews. Ultimately, all data will be consolidated into a detailed report, stored in Notion, significantly enhancing research efficiency and addressing the issues of scattered information and cumbersome organization found in traditional research methods, thereby supporting market analysis and strategic decision-making.

This workflow automates the extraction of article and page content from WordPress websites to create an intelligent question-and-answer system based on retrieval-augmented generative artificial intelligence. It filters, transforms, and vectorizes the content, storing the data in a Supabase database to support efficient semantic retrieval and dynamic questioning. By integrating OpenAI's GPT-4 model, users can enjoy a more precise query experience while achieving persistent management of chat memory, enhancing the contextual continuity of interactions and increasing the intelligent utilization value of the website's content.

This workflow builds an intelligent chatbot integrated into the Slack platform, utilizing RAG technology to connect in real-time with the company's internal knowledge base. It helps employees quickly query company documents, policies, and processes. The chatbot supports natural language interaction, accurately extracting relevant information and responding in a friendly format to ensure the information is accurate and reliable. This system not only enhances the efficiency of information retrieval but also automates responses to IT support and human resources-related inquiries, significantly improving employees' work experience and communication efficiency.

This workflow can automatically extract transcribed text from specified YouTube videos, generate concise summaries, and intelligently provide question-and-answer examples related to the video content. By integrating advanced text processing and natural language generation technologies, it significantly enhances the efficiency of information retrieval, making it suitable for professionals such as content creators, educators, and market analysts, helping them quickly grasp the main points of the videos and manage knowledge for content reuse.

This workflow automatically retrieves legislative procedure data from the European Parliament's official website for the past 18 days, using advanced AI technology to intelligently filter topics related to environmental sustainability. The filtered results will be stored in Google Sheets, and Google task reminders will be generated for each relevant topic to help users efficiently track and manage legislative developments. This process significantly enhances information processing efficiency, ensuring that users can stay updated on key sustainable development policies in a timely manner.

This workflow automatically generates prompts that meet AI model requirements by receiving user queries, and it calls relevant APIs for in-depth content retrieval, extracting and outputting concise, structured answers. It can provide authoritative materials with citations, ensuring the professionalism and credibility of the results. This helps users quickly access the latest research materials in a specific field, enhancing information retrieval efficiency and content quality. It is applicable in various scenarios such as academic research, content creation, and industry analysis.