Browser Use - The way AI uses the internet

What

Browser Use is a web automation platform for teams building AI agents that need to interact with websites at scale. Based on the page, it combines web agents, stealth browsing infrastructure, purpose-built models, proxies, and skill APIs so AI systems can extract data, automate browser tasks, run QA testing, and monitor websites using natural-language instructions.

The product appears positioned for developers and technical teams that want a managed way to turn browser actions into reliable workflows or API-like endpoints. Its core workflow is: run agent-driven browser tasks on live websites, use anti-detect and proxy tooling to improve access reliability, and package repeatable website interactions as reusable skills that can be called programmatically.

Features

• Web Agents for browser tasks — Supports extraction, automation, QA testing, and monitoring through natural-language tasking, which can reduce the need to script every browser interaction manually.
• Stealth Browsers — Provides anti-detect browser infrastructure with CAPTCHA solving and fingerprint controls, which is useful for websites that block or restrict standard automation tools.
• Global residential proxies — Includes proxy coverage across 195+ countries, helping teams run location-sensitive browsing and distribute requests through residential IPs.
• Custom models for browser automation — Offers purpose-built LLM options for browser tasks, suggesting optimization for web interaction workflows rather than general-purpose prompting alone.
• Skill APIs — Lets users create reusable website-specific actions and expose them as API calls, which can make recurring browser workflows easier to operationalize in applications or backend systems.
• Cloud and open-source access paths — Provides cloud documentation and an open-source library install path, giving teams a choice between managed platform usage and code-driven implementation.

Helpful Tips

• Validate reliability on target sites early — For browser automation products, actual performance depends heavily on the sites involved, especially those with anti-bot protections, login complexity, or dynamic content.
• Treat “any website becomes an API” as a workflow design pattern, not a guarantee — Reusable skills can be powerful, but edge cases such as layout changes, captchas, and session handling still need operational planning.
• Use purpose-built browser models selectively — They may improve task success for navigation and extraction, but teams should compare them against existing model stacks for cost, latency, and observability.
• Plan governance around proxies and stealth tooling — Residential routing and anti-detect features can help reliability, but organizations should define acceptable use and review legal or platform-policy constraints for their specific use cases.
• Assess cloud versus open-source fit — Teams needing fast deployment may prefer the managed platform, while engineering-heavy teams may value the open-source library for tighter control and customization.