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AgentQL is a suite of AI-powered tools designed to connect large language models (LLMs) and AI agents to the entire web, enabling efficient and precise data extraction from any webpage. Developed to solve the challenges of fragile web scraping methods like XPath and CSS selectors, AgentQL uses AI to analyze page structures and deliver robust, self-healing queries that adapt to dynamic content changes. It offers a versatile SDK compatible with Python, JavaScript, and Playwright, along with a browser-based debugger for real-time query optimization. The tool supports public and private sites, including those behind authentication, and can parse complex data formats such as tables in PDFs. AgentQL is ideal for developers, data engineers, and teams automating web data workflows, providing reusable code and scalable API access to streamline web automation and data extraction tasks.
4.7/5
Accurate, reliable, and adaptable
Developer-focused with intuitive debugging tools
To enable AI agents and developers to extract structured data from any web page efficiently and reliably.
Supports Python, JavaScript, Playwright SDKs, REST API, and integrates with various web automation workflows.
Freemium with tiered paid plans based on API usage and remote browser hours
Features with the highest value for users are highlighted here.
AI-powered web data extraction
Versatile Python and JavaScript SDKs
Browser-based debugging extension
Self-healing query capabilities
Support for authenticated and dynamic pages
Reusable query configurations
Browserless REST API access
PDF content parsing
Web Developers
Data Engineers
AI Researchers
Automation Specialists
Startups
Enterprise Teams
Product Managers
Content Aggregators
AI Developers
Technical Consultants
Starter
Professional
Weekly intelligence on AI strategy, operations, and market shifts. No noise. No narrative. Direct to your inbox.
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