Core Viewpoint - The article discusses the emergence of Sheet0 as a Level 4 Data Agent, emphasizing its ability to provide real-time data collection and delivery capabilities, which is crucial for the effective functioning of AI agents in various applications [1][2][4]. Group 1: Company Overview - Sheet0 aims to create a high-efficiency aggregation layer for real-time data, targeting super individuals, knowledge workers, and agent networks, with the goal of becoming a key hub in the agent internet [4][12]. - The founder, Wang Wenfeng, has nearly a decade of experience in AI, foundational software, and large-scale distributed data processing, which informs the company's technical and market strategies [2][6]. Group 2: Product Features - Sheet0's product is defined as an L4 level Data Agent, which autonomously collects and delivers structured data based on user-defined goals, significantly reducing the time and cost compared to other agent products [13][14]. - The system utilizes a dynamic workflow that translates user data needs into executable code, allowing for self-repair in case of execution errors, thus ensuring high accuracy and reliability [2][20]. Group 3: Market Positioning - The company differentiates itself by focusing on delivering "100% accurate, 0 hallucination" results, emphasizing the importance of transparency and verifiability in data collection and processing [14][19]. - Sheet0 is positioned to become a new backend for agents by providing real-time data supply capabilities, which is essential for the next generation of AI applications [16][18]. Group 4: Data Importance - Data is categorized into three levels of value for agents: model training, operational context, and tool invocation, highlighting the necessity of high-quality, structured data for effective AI performance [9][11]. - The article stresses that the future competition will hinge on the speed and precision of real-time data provision rather than the sheer volume of data available [18]. Group 5: User Scenarios and Business Model - Initial user scenarios focus on public internet data collection, with successful case studies demonstrating the tool's efficiency in gathering and structuring data for analysis [21][24]. - The business model includes a credit-based payment system for short-term operations, with plans to explore a user-driven pricing model for data that is not readily available [25].