Competitor Research Intelligent Agent

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.

This workflow combines advanced AI language models with the Notion knowledge base to provide intelligent Q&A services. Users can input questions, and the system will automatically retrieve relevant content and generate accurate answers, along with links to Notion pages, ensuring the reliability and traceability of the information. This assistant enhances the efficiency of knowledge queries and is suitable for various scenarios such as internal knowledge management in enterprises, customer support, and personal information retrieval, helping users quickly access the information they need.

This workflow provides an intelligent personal shopping assistant feature for e-commerce platforms by integrating language models and retrieval-augmented generation technology. It can automatically identify users' shopping needs, accurately extract product search information, and match relevant products in the WooCommerce database. Additionally, for non-shopping inquiries, the system offers intelligent responses based on a knowledge base, enhancing the user experience. Through context management, it ensures the continuity of conversations, significantly improving customer satisfaction and service efficiency.

This workflow automatically scrapes the latest articles from the Paul Graham website, extracts and processes the text content, and converts it into vectors stored in the Milvus database. By integrating OpenAI's embedding model, it enables intelligent Q&A and information retrieval based on the knowledge base. It supports manual triggers and chat message triggers for AI responses, making it suitable for researchers, businesses, and content creators, enhancing information management and retrieval efficiency, and streamlining the knowledge base construction process.