Compare Gaffa vs. WebScraping.AI

Gaffa is a REST API built for web scraping and browser automation, allowing developers to run real, full browsers at scale with a single API call. It removes the difficulty of managing headless browser frameworks, rotating proxies, CAPTCHA solving, and scaling infrastructure, all of which are handled automatically. JavaScript-heavy and dynamic websites render exactly as they would for a human visitor by default. Beyond standard scraping, Gaffa supports AI-driven structured data extraction (extract data into a defined schema without writing CSS selectors), screenshot and PDF capture, infinite-scroll and form-filling automation, and clean Markdown conversion for feeding webpages directly into LLM and RAG pipelines. A rotating residential proxy network keeps access reliable across regions, and a credit-based pricing model means teams pay only for the browser time and bandwidth they actually use. Gaffa is designed for AI engineers, data teams, and developers who want production-grade web data extraction without having to build and maintain their own infrastructure.

WebScraping.AI is an advanced web scraping API that leverages artificial intelligence to streamline the process of data extraction by managing tasks such as browser interactions, proxy usage, CAPTCHA solving, and HTML parsing automatically for the user. When users input a URL, they can obtain the HTML, text, or other data from the specified webpage effortlessly. The service incorporates JavaScript rendering capabilities within a genuine browser, guaranteeing that the content displayed mirrors what a user would see on their own device. Furthermore, it features a system of automatically rotating proxies, which enables users to scrape any website without restrictions, and includes geotargeting options for more precise data collection. HTML parsing occurs on WebScraping.AI's servers, minimizing the risks associated with high CPU usage and potential vulnerabilities in HTML parsing tools. In addition, the platform provides advanced functionalities powered by large language models, which help in extracting unstructured data from pages, answering user inquiries, generating concise summaries, and facilitating content rewrites. Users can also extract the visible text from web pages after JavaScript rendering, allowing them to use this information as prompts for their own language models, enhancing their data processing capabilities. This comprehensive approach makes WebScraping.AI an invaluable tool for anyone needing efficient data extraction from the web.