Webtap

Webtap is a web scraping tool that enables users to extract structured data from any website by simply describing what they need in natural language. Unlike traditional scraping methods that require writing custom code, managing proxies, or manually parsing HTML, Webtap uses automated crawlers powered by natural language processing to understand user requests and execute them end-to-end. The workflow consists of three main steps: query, retrieve, and export. In the query phase, users specify their data requirements using plain English, such as “get all job listings from LinkedIn with title, company, and location.” Webtap’s system supports dozens of websites out of the box, covering e-commerce platforms, social media, news sites, and more, and can also adapt to arbitrary websites through its AI agents. During the retrieve phase, Webtap automatically solves CAPTCHAs, identifies relevant data fields, transforms the extracted information into a clean format, and continuously monitors websites for layout or DOM changes, adjusting its scraping logic accordingly without user intervention. This dynamic adaptation ensures long-term reliability and reduces maintenance overhead significantly. In the export phase, users can download the results as CSV files, which are immediately usable in spreadsheets, databases, or analytics tools. An API is also under development, which will allow direct programmatic access to scraped data for integration into custom applications, dashboards, or machine learning pipelines. A notable feature is the generative AI agent that interprets complex or ambiguous queries. For example, a user can ask “compare prices of all iPhone models on two different online stores and give me a table with the cheapest options,” and the agent will break down the request,