What is AgentQL?
Forget fragile XPath or DOM selectors. AI-powered AgentQL finds elements reliably, even as websites change. Just specify what data you are scraping from the web with natural language-like queries, and AgentQL will handle the rest.
Problem
Users face challenges in reliably extracting data from websites due to the limitations of fragile XPath or DOM selectors.
Drawbacks: Fragile selectors can result in data extraction failures as websites evolve, leading to inefficiencies and inaccuracies in web scraping.
Solution
AgentQL provides an AI-powered solution for data extraction and web automation by enabling users to specify scraping requirements in natural language queries.
Core features: AI technology accurately locates elements on websites, ensuring reliable data extraction even with website changes.
Customers
Data analysts, researchers, and businesses requiring efficient web scraping and data extraction capabilities.
Occupation: Data analysts, researchers, business intelligence professionals.
Unique Features
AgentQL utilizes AI-powered technology to enhance the accuracy and reliability of web scraping, ensuring consistent results.
Offers natural language query input for users, simplifying the process of specifying data extraction requirements.
User Comments
Accurate and reliable data extraction tool.
Saves time and effort in web scraping tasks.
Intuitive natural language query interface.
Great for handling dynamic website structures.
AI technology provides precise data extraction results.
Traction
AgentQL has gained significant traction with over $500k MRR and a user base exceeding 10,000 customers.
Continuous updates and enhancements to the product have contributed to its growth and popularity.
Market Size
The global web scraping market size is valued at approximately $2.4 billion as of 2021, with a projected CAGR of 22.6% from 2022 to 2028.
Increasing demand for automated data extraction solutions and competitive intelligence is driving market growth.
