AgentQL

AgentQL connects LLMs and AI agents to the entire web. It provides a framework for building AI-powered web agents that can access data from public or private pages and automate tasks across sites. The tool supports developers and data workflows by offering a language to describe what to retrieve and how to interact with pages. It emphasizes web interaction and data extraction at scale.

The product uses a query language and a parser to interact with web page elements and extract data quickly and precisely. It is designed to help users define what data to pull, how to navigate pages, and how to structure results for reuse in automated tasks or analyses.

AgentQL provides SDKs and a REST API to access web data and automate actions. It supports interaction through Playwright, Python, and JavaScript, and includes features to handle dynamic content and varying page structures. The goal is to reduce fragility in parsing while offering repeatable results across similar pages.

The platform offers tools for debugging, self-healing data extraction, and reusable queries. It aims to be compatible with various data workflows and automation setups, allowing integration with different frameworks and environments.

Use cases

• Automate web interactions and extract data from web pages to feed data workflows
• Parse information from PDFs and structured documents