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.
Hey Product Hunters! 👋
I am Shuhao, cofounder of the AgentQL team. Allow me to introduce AgentQL, an AI-powered semantic framework designed to enable AI agents to seamlessly interact with the web, using natural language.
That's a lot of big words. Let's break down what AgentQL can do:
🕹️ Give it the command to find "price", and it will retrieve all the price data on an e-commerce page you spend less time building rigid selectors
🖥️ Take the same code to another site, and it can work just as well >> you spend less time maintaining fragile scripts
📝. Need to interact with sites as part of your work flow? Simply use natural language, tell AgentQL to click, scroll_page or fill.
So why did we decide to build AgentQL?
Traditional web automation struggles with identifying elements consistently through UI changes. When LLMs and agents first emerged, we envisioned a web infrastructure tailored for agentic interaction, which excels in handling these small but breaking changes, so we decided to tackle this challenge head-on.
How did we go about this?
At the heart of our framework is the AgentQL Query, a language crafted to describe locate web elements within a structured schema. We’ve integrated robust DOM processing with advanced prompt engineering, creating a powerful combination that dynamically generates context-aware prompts. By doing so, we overcome the fragility of static XPath or attribute selector-based scripts, enabling a more resilient and flexible web interaction infrastructure.
Would you like to join our journey to an agentic future?
Our early users have reported real productivity boosts with AgentQL, unlocking use cases that were previously too costly or complex to develop. Your feedback and questions will be invaluable to us.
👀 Please check out our technology at AgentQL.com
💬 Connect with our community on Discord and X.com
Thank you for being a part of our story!
The idea of using natural language to find web elements sounds like a huge relief from dealing with fragile selectors. It could make web scraping and automation so much easier.
If this can help me gather data more reliably and with less hassle, I’m all for it. It looks like it could simplify the process of web automation a lot.
AgentQL sounds like a game changer for web scraping. The ability to use natural language for data extraction is such a refreshing pivot from those outdated XPath and DOM selectors. It’s about time we stopped spending hours on fragile scripts!
I love the idea of maintaining fewer brittle scripts too. Just thinking about the time saved and the productivity boost you mentioned—definitely upvoting this! The struggle of keeping everything running smoothly with UI changes is real, and it seems AgentQL has it all figured out.
Can’t wait to try this out in my workflow. Here’s to a future where we can just say what we need instead of wrestling with selectors.
AgentQL seems like a revolutionary tool for web scraping and automation! The use of AI to understand the context behind web elements makes it far more intuitive than traditional XPath or CSS selectors. The flexibility to write natural language queries is a game changer, reducing fragility when websites change their layouts. Perfect for developers who want to automate tedious tasks or extract data without constant maintenance. Definitely a tool worth trying for anyone into web automation, testing, or scraping!
This is brilliant!
The only thing I would change is to keep the flow 100% no-code by serving it to non-technical people (like Apify)
congratulations on the launch although I haven't tried the product but it will a very good fit for SEOs
AgentQL is impressively accessible as a tool for web data extraction, especially suitable for enhancing AI search engines. It streamlines the cumbersome process of selecting the right web elements, which speeds up data collection. Moreover, it supports the use of custom code, allowing for sophisticated processing of the extracted data tailored to AI-driven search functionalities.
The ease of specifying data with natural language is impressive. Can’t wait to test how well it performs on different sites!
relying on natural language queries for web scraping sounds like a huge improvement over traditional methods. Excited to see how it handles dynamic websites!
Congrats on this great launch! I think this could truly revolutionize the way developers approach web automation, making it more resilient and efficient. Can't wait to try it :)
Great job, guys. I'm just checking AgentQL right now & it's cool. Congrats on the launch, guys!
The integration with AI to simplify data access is brilliant. I’m excited to see how this will improve data teams' efficiency. How does AgentQL handle complex queries, and what sets it apart from traditional SQL query tools?
The ability to interact with databases using natural language could make data analysis more accessible to everyone. Great Job, team!
Congrats on the launch! I can see so many uses for this and I'm excited to try it out. Props to your team for all the hard work!
