AgentQL

AgentQL is a revolutionary tool designed to simplify web scraping and automation. It uses natural language selectors to find data on any webpage, including authenticated content. This means you can extract structured data from websites without the hassle of constantly updating broken selectors.

Imagine being able to write a single query that works across multiple sites with similar data structures. AgentQL makes this possible, adapting to UI changes and ensuring that your data extraction tasks remain reliable.

How It Works

AgentQL uses AI to build a semantic understanding of the context surrounding web elements on a page. This allows elements to be found based on their meaning and context, not just their position in the DOM. As a result, queries are more stable, reusable, and intuitive for both developers and non-technical users.

Key Features

- Natural Language Queries: Describe what you're looking for in plain English, making queries more readable and maintainable.

- Controlled Output: Define the structure of your output data, eliminating post-processing steps.

- Deterministic Results: Get consistent and reliable results, ensuring the same output for the same input every time.

Primary Use Cases

- Data Scraping: Extract structured data from websites, such as pricing details from multiple storefronts, social media metrics, and news articles.

- Web Automation: Streamline repetitive tasks and complex workflows, like automating form submissions and interacting with web applications programmatically.

- End-to-End Testing: Build robust and maintainable test suites that are resistant to UI changes, reducing test flakiness and maintenance overhead.

Getting Started

Visit the AgentQL playground to experience the future of web automation today. With AgentQL, you can write natural language queries to access web data as easily as having a conversation, extract structured data in real time, and automatically adapt to website changes.