• Browser Use secures $17M in funding to improve AI-driven web automation.
  • The tool allows AI agents to navigate websites and execute tasks efficiently.
  • Investors back Browser Use’s vision of a more interactive and autonomous web experience.

Browser Use has secured $17 million in fresh funding to develop its tool that enables AI agents to navigate and interact with websites more effectively. With AI-powered web automation advancing rapidly, this funding will bring Browser Use to the forefront of this transformation.

The seed funding is led by Felicis' Astasia Myers with participation from Paul Graham, A Capital and Nexus Venture Partners.

As the Chinese start-up Butterfly Effect employed Brower Use in its viral Manus tool, it drove awareness to new heights.

Browser Use’s solution addresses a key challenge in AI development—enabling artificial intelligence to interact with and extract information from websites with greater accuracy and efficiency.

Magnus Müller and Gregor Zunic founded Browser Use last year through ETH Zurich’s Student Project House accelerator, combining Müller’s expertise in web scraping with their shared background in data science.

In just five weeks, they built a demo that quickly gained traction, leading them to open-source the project.

Browser Use simplifies a website’s buttons and elements into a more readable, “text-like” format, enabling agents to interpret options and make decisions independently.

“A lot of agents rely on vision-based systems and try and navigate websites through screenshots, and in [the] process, things break,” Müller said.
“We convert [websites] into something agents can understand. This approach means we can run the same tasks again and again at a cheaper cost.”

Browser Use anticipates to be the key technology that can make an AI company's agent interact with websites more gracefully by becoming a "fundamental layer".

“There are companies coming to us and saying, ‘What can we do to make it easier for agents to navigate our website?’” Müller said.
“There are sites — for example, LinkedIn — that change the way the website works all the time, so agents often fail on sites like those.”

According to Myers, web AI agents represent the next frontier in advancing end-to-end automation of human tasks.

These agents serve as a dynamic bridge between static, pre-trained models – primarily text-focused – and the constantly evolving digital landscape.

Edited by Harshajit Sarmah