AI Web Scraper automates the process of collecting and structuring data from websites by combining a headless browser for rendering JavaScript with powerful AI-driven parsing. Users supply a URL and optional custom prompts, and the tool fetches the page, renders dynamic content, and feeds the result into a large language model to extract tables, lists, metadata, summaries, or any user-defined information. Output is provided in clean JSON, ready for downstream processing or integration into data pipelines.

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.