Agent TARS leverages a combination of advanced computer vision and natural language processing techniques to understand and manipulate graphical user interfaces. By capturing visual representations of web pages, TARS can identify buttons, forms, tables, and other page elements. Users interact with TARS through natural language prompts, instructing it to click, scroll, extract text, or fill forms across multiple pages. It supports customizable workflows that chain tasks—such as logging into accounts, scraping data, and exporting results to CSV or JSON. With support for headless and headful browser modes, TARS enables both interactive exploration and unattended automation, making it ideal for testing, data acquisition, and routine browser-based operations.

CausaLens is an AI-powered platform that specializes in causal inference, allowing organizations to analyze the relationships between different variables in their data. It helps businesses derive actionable insights by identifying cause-and-effect relationships, ultimately improving decision-making processes. The platform caters to both technical and non-technical users, making it accessible for diverse teams seeking to enhance their data-driven strategies.