Type: GitHub Repository Original Link: https://github.com/browser-use/browser-use Publication Date: 2025-09-18
Summary #
WHAT - Browser-Use is a Python library for automating online tasks by making websites accessible to AI agents. It allows performing automated actions on browsers using AI agents.
WHY - It is relevant for AI business because it enables the automation of complex and repetitive tasks on browsers, improving operational efficiency and reducing the time required to perform manual activities. It solves the problem of the need for human interaction for repetitive online tasks.
WHO - The main actors are developers and companies that use Python for browser automation. The library is developed and maintained by Gregor Zunic.
WHERE - It positions itself in the browser automation and AI tools market, integrating with the Python ecosystem and browser-based automation technologies.
WHEN - It is an established project with an active user base and comprehensive documentation. The library is continuously evolving with daily improvements for speed, accuracy, and UX.
BUSINESS IMPACT:
- Opportunities: Integration with our existing stack to automate support and administrative tasks, reducing operational costs and improving productivity.
- Risks: Competition with other browser automation solutions, such as Puppeteer and Selenium. Need to monitor the project’s evolution to maintain competitiveness.
- Integration: Possible integration with existing automation tools and business process management (BPM) platforms.
TECHNICAL SUMMARY:
- Core technology stack: Python, Playwright, LLM (Large Language Models).
- Scalability: High scalability thanks to the use of cloud for browser automation, support for parallel and distributed executions.
- Limitations: Dependency on Chromium-based browsers, potential compatibility issues with complex websites.
- Technical differentiators: Use of AI agents for automation, integration with LLM for self-healing workflows, support for stealth executions.
Use Cases #
- Private AI Stack: Integration in proprietary pipelines
- Client Solutions: Implementation for client projects
- Development Acceleration: Reduction of project time-to-market
- Strategic Intelligence: Input for technological roadmap
- Competitive Analysis: Monitoring AI ecosystem
Third-Party Feedback #
Community feedback: Users appreciate the use of non-LLM code for main paths and the integration of LLM for workflow repair. Main concerns involve managing loading times and support for various input types, such as checkboxes and radio buttons. Some users have proposed similar solutions for self-healing in their automation experiences.
Resources #
Original Links #
- Enable AI to control your browser 🤖 - Original link
Article suggested and selected by the Human Technology eXcellence team, processed through artificial intelligence (in this case with LLM HTX-EU-Mistral3.1Small) on 2025-09-18 15:11 Original source: https://github.com/browser-use/browser-use
Related Articles #
- Cua is Docker for Computer-Use AI Agents - Open Source, AI Agent, AI
- Cua: Open-source infrastructure for Computer-Use Agents - Python, AI, Open Source
- Data Formulator: Create Rich Visualizations with AI - Open Source, AI