
Browser Use, known as BU, is a comprehensive infrastructure platform that deploys fully autonomous AI browser agents at scale. As a leading AI browser agent solution, it enables users to control browsers programmatically with a single prompt, giving agents a browser, terminal, and persistent memory. This platform is designed for developers, data engineers, and operations teams who need to automate complex web interactions, extract data, and perform QA testing without manual intervention. The core value lies in its ability to make AI agents navigate the web exactly as a human would, but with greater speed, stealth, and reliability.
Traditional web automation approaches break frequently due to site changes, require extensive scripting, and can be detected and blocked by anti-bot measures. BU solves these pain points by providing undetectable browsers with advanced fingerprint spoofing and CAPTCHA solving capabilities. For teams that rely on web data extraction, monitoring, or testing, the constant maintenance and detection risks create significant operational overhead. BU eliminates these challenges by offering zero-config stealth browsers that mimic human interactions, complete with residential proxy support across 195+ countries, ensuring that agents operate unseen and without interruption.
BU's Stealth Browsers are anti-detect browsers that automatically spoof canvas fingerprint, WebGL renderer, and other browser signals to appear as a normal human user. They come with built-in CAPTCHA solving, proxy location selection from 195+ countries, and require zero configuration to start using. This feature is critical because many sites actively block automated access; Stealth Browsers ensure that AI agents can access any website without being flagged. Additionally, they offer sub-second cold starts and cost only $0.02 per hour, making them three times cheaper than alternatives while providing enterprise-grade undetectability.
The Fully Hosted Web Agents service provides AI browser automation at scale, handling extraction, automation, QA testing, and monitoring tasks. Users simply describe what they need—for example, 'Find hiring managers on LinkedIn'—and the agent executes the task using a real browser session. This eliminates the need for writing and maintaining custom scraping scripts or Selenium code. The agents are hosted on BU's cloud infrastructure, which maintains persistent memory and session state, allowing long-running workflows. They also integrate with popular tools like Slack, Gmail, and Linear through 100+ service connectors, enabling automated data flows into existing systems.
admin
BU offers custom LLMs purpose-built for browser automation, optimized for tasks per dollar. For instance, BU's own model can perform 37 tasks per $1, compared to 2 for Claude Sonnet 4.5 and 13 for Gemini Flash. These models are fine-tuned for web navigation accuracy, achieving 97% benchmarked performance. Additionally, the Browser Harness is an open-source, thin Python library that gives agents superpowers to complete any web task. It includes self-healing selectors, helpers for clicking coordinates, waiting for page loads, and file uploads. This harness can be used independently or combined with BU's cloud services.
BU's approach is built around a simple workflow: define a task in natural language, and the AI agent automatically spins up a browser session, navigates sites, solves any challenges, and completes the goal. The system handles authentication flows, session management, and memory through a persistent context that learns from past actions. All browser interactions are executed on BU's cloud infrastructure, with optional residential proxy rotation to maintain anonymity. The platform exposes REST APIs for programmatic control, and open-source libraries for local development. The entire pipeline is designed to be failure-resistant, with automatic retry and healing mechanisms that adapt to page changes.
Teams use BU to extract competitor pricing data from e-commerce sites without being blocked, automatically scrape job listings from multiple boards, and monitor regulatory changes on government portals. In QA testing, agents can run end-to-end test suites on complex web apps, clicking through workflows and verifying UI states. Marketing teams automate the collection of ad performance metrics from platforms like Google Ads and LinkedIn. The outcome is consistent: teams reduce data collection time by over 90%, eliminate maintenance overhead from site changes, and achieve extraction accuracy upwards of 97%, as measured by BU's benchmarks.
BU is trusted by engineering teams at companies like Airbnb, Amazon, Anthropic, Google, and OpenAI. Its primary users are DevOps engineers, data scientists, QA engineers, and automation specialists who need reliable browser automation at scale. The platform offers cloud-hosted agents with per-second billing, self-hosted options via the open-source library, and a managed 'Bux' box for 24/7 Claude agent operation from Telegram or SSH. Pricing starts at $0.02 per hour for stealth browsers, making it accessible for startups and enterprises alike. In summary, BU provides the most complete infrastructure for deploying AI browser agents with unmatched stealth, speed, and reliability.
DevOps engineers, data scientists, QA engineers, automation specialists, and data engineers who need reliable, undetectable browser automation at scale. Also used by marketing teams for competitive intelligence and by startups and enterprises requiring persistent memory AI agents. Trusted by engineering teams at top companies like Amazon, Google, OpenAI, and Airbnb.
Updated 2026-03-02