Browser Use

TL;DR. Browser Use is an open-source Python framework and cloud platform that lets LLM-powered AI agents autonomously navigate, interact with, and extract data from websites. Founded in 2024 by Magnus Müller and Gregor Žunič, it targets Python developers and engineering teams building agentic web automation, from individual contributors to enterprises.

Overview

Browser Use is an open-source framework and cloud platform that lets AI agents autonomously navigate and interact with websites by converting page elements into structured text that large language models can process deterministically. Rather than relying on vision-based screenshot approaches, Browser Use breaks down buttons, forms, and interactive elements into a text-like format, enabling agents to understand available actions and make decisions with higher reliability and lower cost.

Founded in 2024 by Magnus Müller and Gregor Žunič, Browser Use originated through ETH Zurich's Student Project House accelerator. The two met while pursuing master's degrees in data science and built a prototype in a matter of days, launching it publicly on Hacker News. The project gained rapid traction in the developer community, reaching 50,000 GitHub stars within three months of launch and surpassing 103,000 stars by mid-2025, making it one of the fastest-growing open-source projects in the AI tooling space. Browser Use is part of Y Combinator's Winter 2025 batch.

In March 2025, the company raised a $17 million seed round led by Felicis (partner Astasia Myers), with participation from Paul Graham, A Capital, Nexus Venture Partners, Y Combinator, Liquid2, SV Angel, and Pioneer Fund. The company is headquartered in San Francisco and has approximately 7 to 13 employees.

Browser Use offers both an open-source Python library (installable via pip) and a hosted cloud platform. The open-source library supports multiple LLM providers including OpenAI, Anthropic, Google, and Browser Use's own optimized models. The cloud platform adds stealth browsers with anti-detection capabilities, CAPTCHA solving, residential proxies across 195+ countries, and fully hosted web agents. The company reports 97% accuracy on its benchmark of 100 real-world browser tasks and claims Fortune 500 customers. Browser Use gained significant visibility when Chinese startup Butterfly Effect used it as a core component of its viral Manus AI agent.

Key links: Website | GitHub | Documentation | Cloud Platform | Blog

Products & Features

Browser Use offers an open-source Python library for AI-driven browser automation alongside a cloud platform with fully-hosted web agents, stealth browsers, and custom LLMs. The core library (MIT-licensed, 103K+ GitHub stars) lets developers connect any LLM to automate web tasks locally or self-hosted, while Browser Use Cloud provides managed infrastructure for scaling agent workloads.

The product suite includes six components: Browser Harness (an open-source, self-healing agent harness for direct browser control), Stealth Browsers (anti-detect infrastructure with CAPTCHA solving and 195+ country proxy rotation), Custom Models (purpose-built LLMs for browser automation, branded "BU 2.0"), Fully Hosted Web Agents (cloud-managed agents for complex multi-step tasks), Browser Use Box (a 24/7 dedicated agent environment combining Claude Code with Browser Harness, drivable via Telegram, web, or SSH), and Proxies (residential IPs across 195+ countries). The cloud agent supports data extraction, form filling, multi-step workflows, research, monitoring, testing, and scheduled task execution, with 1,000+ integrations including Gmail, Slack, and Notion.

Pricing follows a freemium credit model with four tiers: Free ($0, 3 concurrent sessions, 10 agent tasks/month), Dev ($29/mo, 25 concurrent sessions), Business ($299/mo, 200 sessions), and Scaleup ($999/mo, 500 sessions). Enterprise plans offer annual credit pools, SLAs, and dedicated support. Usage rates include browser sessions at $0.02/hour, proxy bandwidth at $5/GB, and V2 agent step costs from $0.006/step. The custom BU 2.0 model charges $0.60/1M input tokens and $3.50/1M output tokens. A Bring Your Own Key option lets users connect Anthropic, OpenAI, or Google API keys with a 0.2x orchestration fee.

Developer access spans a REST API (v3), a Python SDK, CLI 3.0 for coding agents, and MCP server compatibility. The CLI integrates with Claude Code, Codex, and similar agent frameworks. An open-source desktop app shipped with the v2.1 release. The library requires Python 3.11+ and installs via pip install browser-use or uv add browser-use.

Security & Compliance

Browser Use holds SOC 2 Type II certification and offers a self-hosted open-source option for data-sensitive environments, but its cloud platform trains AI models on user inputs by default with no documented opt-out. The company achieved SOC 2 Type II compliance with a reporting period of July 17 to October 17, 2025, audited by Accorp Partners. SOC 2 is not legally required but Browser Use frames it as a long-term security investment, with regular audits conducted by third-party firms.

The platform's agent sandbox architecture is a notable security strength. In production, each agent runs in an isolated Unikraft micro-VM that receives only three environment variables (session token, control plane URL, and session ID) and has no access to AWS keys, database credentials, or API tokens. A stateless control plane holds all real credentials and acts as a proxy for every external request, including LLM calls and file storage via presigned S3 URLs. Sandboxes undergo hardening steps before agent code executes: Python source is compiled to bytecode and deleted, the process drops from root to an unprivileged user, and environment variables are stripped after read. The backend runs on ECS Fargate in private subnets behind an ALB.

Data handling practices carry important caveats. The privacy policy discloses that Browser Use collects user inputs and generated outputs, and uses inputs to train its AI models. Third-party reviews confirm the standard cloud plan trains on user inputs with no opt-out, making self-hosting the recommended path for sensitive workflows. Payment processing is handled by Stripe. Browser Use does not filter user-submitted content and places responsibility on users to ensure inputs comply with applicable laws. Enterprise-tier customers can negotiate custom data retention terms. The open-source library (MIT license, available on GitHub) allows full self-hosting where organizations control their own compute, LLM API keys, and data pipeline entirely.

No publicly known security breaches or incidents were identified as of this research. The company has not publicly documented certifications beyond SOC 2 Type II (no ISO 27001, HIPAA, or GDPR-specific certifications were found). Specific enterprise features like SSO, RBAC, and audit logs are not detailed in publicly available documentation.

User Feedback & Adoption

Browser Use has achieved explosive developer adoption since its October 2024 open-source launch, reaching roughly 93,000+ GitHub stars by mid-2026, making it one of the fastest-growing open-source AI projects on the platform. The repository was created on October 31, 2024, and crossed 50,000 stars within roughly five months, as reported by the company in its March 2025 seed funding announcement. By early 2026, the leaderboard tracked approximately 78,500 stars (with cached data from February 2026), and independent coverage from June 2026 cites 93K+ stars. The project also reports 15,000+ active developers and over 9,200 forks as of early 2026.

The company raised $17 million in seed funding in March 2025, led by Felicis Ventures with participation from A Capital, Nexus Ventures, Y Combinator, Paul Graham, SV Angel, and Pioneer Fund. Browser Use was part of Y Combinator's Winter 2025 batch, and TechCrunch reported that more than 20 companies in that same YC cohort used Browser Use for their own products. Viral adoption was further accelerated when Chinese startup Butterfly Effect incorporated Browser Use into its widely discussed Manus agent tool.

User sentiment is mixed. Developer reviews praise the natural language control paradigm, broad LLM support, and the open-source MIT licensing that lowers barriers to entry. Independent review site GoLogin highlights strengths in data extraction, RPA-style workflows, and cross-platform testing. A community of 23,400+ Discord members and 27,000+ Twitter followers represents the largest community among browser agent tools, according to one aggregator. However, Reddit users in r/AI_Agents and r/automation report recurring pain points: slow execution times, high per-task API costs ($5+ for a single task in some cases), failures on tasks requiring authentication or complex multi-step workflows, and difficulties with anti-bot detection on platforms like LinkedIn and Reddit. One Reddit thread titled "PSA: Browser-Use is a Scam" reflects the most negative cloud-tier experiences, though these complaints primarily target the hosted cloud product rather than the open-source library. Common barriers to adoption include cost unpredictability at scale, reliability on dynamic or login-protected sites, and the need for retries and human review in production workflows.

Monetization & Business Model

Browser Use operates a hybrid monetization model: an open-source Python library (free, MIT-style) that serves as a top-of-funnel, paired with a credit-based cloud platform where the company earns revenue. The open-source library has surpassed 78,000 GitHub stars, making it one of the fastest-growing open-source AI projects of 2025.

Pricing tiers (official, from browser-use.com/pricing):

• Free: $0, 3 concurrent sessions, 10 agent tasks/month, with pay-as-you-go credit top-ups available.

• Dev: $29/month, includes $29 in monthly credits, 25 concurrent sessions, advanced stealth, bring-your-own-key support.

• Business: $299/month, $299 in monthly credits, 200 concurrent sessions.

• Scaleup: $999/month, $999 in monthly credits, 500 concurrent sessions.

• Enterprise: Custom, with annual credit pools, SLAs, data retention terms, and dedicated support.

Usage-based rates apply across all paid plans: browser sessions at $0.02/hour, proxy bandwidth at $5/GB (or $0.20/GB egress when bringing your own proxy), and LLM tokens at 1.2x provider rates. Users can also bring their own API keys (Anthropic, OpenAI, Google) and pay only a 0.2x orchestration fee on top of direct provider costs. The company offers its own "BU 2.0" model at $0.60/M input tokens and $3.50/M output tokens.

Funding and stage: Browser Use raised a $17 million seed round in March 2025, led by Felicis Ventures (Astasia Myers) with participation from Paul Graham, A Capital, Nexus Venture Partners, Y Combinator (Winter 2025 batch), SV Angel, and Pioneer Fund. The valuation was not disclosed. Third-party data from GetLatka estimates revenue at approximately $1.4M as of mid-2025, though this figure is unverified by the company. No ARR or growth rate has been officially disclosed. The company was founded in 2024 by Magnus Müller and Gregor Žunič through ETH Zurich's Student Project House accelerator.

Leadership & Team

Browser Use was founded in 2024 by Magnus Müller (CEO) and Gregor Žunič, two ETH Zurich data science master's students who met through the university's Student Project House accelerator. The company is part of Y Combinator's Winter 2025 batch and has raised a $17 million seed round led by Felicis Ventures (partner Astasia Myers), with participation from Paul Graham, A Capital, Nexus Venture Partners, Y Combinator, Liquid2, SV Angel, and Pioneer Fund.

Müller transitioned from hands-on coding to a CEO role as the company scaled, reporting in early 2026 that he now does "less coding" and focuses more on organizational leadership. The team grew from two founders to approximately seven to eight people by early 2025, operating out of San Francisco while retaining European roots. Müller has emphasized a hacker-house culture, telling press he wants "an awesome community" where engineers can "hack together, have fun building together and just work really hard." The company is actively hiring engineers, particularly those with LLM and browser automation expertise.

The open-source-first ethos is central to the founders' philosophy: they chose to open-source Browser Use from day one rather than build in stealth, a decision Müller credits with driving rapid community adoption (50,000 GitHub stars in three months) and attracting investor attention. Felicis partner Astasia Myers cited the founding team and open-source approach as decisive factors in the investment.

Target Audience & Use Cases

Browser Use targets developers and engineering teams building AI agents that need to interact with websites, spanning individual open-source contributors, startups, and Fortune 500 enterprises. The platform is built primarily for Python developers (Python 3.11+) who want to give LLM-powered agents the ability to navigate, interact with, and extract data from the web without writing brittle scraping scripts.

Primary personas include AI/ML engineers, automation engineers, and full-stack developers integrating web capabilities into agent workflows. The tool also serves AI researchers exploring agentic web interaction, and increasingly, non-developer end users who use the hosted cloud version as a B2C chat tool for tasks like job applications and online shopping.

Top use cases:

1. Web research and data extraction: AI agents autonomously navigate complex sites to scrape product information, compile job listings, or gather competitive intelligence in real time.
2. Workflow automation: Agents complete multi-step processes such as filling out online forms, booking travel, managing account registrations, and placing grocery orders, mimicking human browsing behavior.
3. Browser infrastructure at scale: Production teams use the hosted cloud for stealth browsers with CAPTCHA solving, residential proxies across 195+ countries, and the ability to run thousands of isolated agent sessions in parallel.
4. Real-time web monitoring: Users describe what to watch on a webpage and the agent detects changes, eliminating the need for custom scrapers or diffing logic.
5. Coding agent integration: The CLI and agent skill integrate with tools like Claude Code, Codex, and Cursor, giving coding agents a browser they can control reliably.

Market segments and company size: The open-source library (MIT-licensed, 103K+ GitHub stars) serves individual developers and small teams who self-host, while the fully hosted cloud platform targets scaling startups and enterprises needing production-grade reliability. Browser Use claims adoption by Fortune 500 companies and has been used by engineering teams at major technology enterprises including Airbnb, Amazon, and Anthropic. The company is a Y Combinator Winter 2025 batch participant, founded in 2024 by Magnus Müller and Gregor Zunic.

Industry verticals: E-commerce, recruitment, market research, and any domain requiring interaction with websites that lack APIs. The structured output capabilities (JSON, CSV, webhooks) make it suitable for data pipelines and business intelligence workflows.

Geographic focus: No explicit regional limitation. Proxies span 195+ countries, and the infrastructure is distributed across multiple cloud metros, supporting a globally distributed user base.

Tags & Categories

Primary Category: AI Other Categories: AI Other, AI Infrastructure, AI DevOps Tags: browser automation, ai agent, web automation, llm agent, open-source, python, playwright, anti-detect browser, captcha solving, proxy rotation, rpa, developer tools

Browser Use is an open-source framework and cloud platform that enables LLM-powered AI agents to control web browsers autonomously. It provides a thin, self-healing harness that lets AI agents navigate websites, fill forms, extract data, and complete multi-step web tasks. The project is built in Python and runs on top of Playwright as its underlying browser automation layer. The framework supports multiple LLM providers including OpenAI (GPT models), Anthropic (Claude), and Google (Gemini), and also offers its own purpose-built models (the bu-* series) optimized specifically for browser automation tasks.

The product spans several sub-categories: the open-source Browser Harness library, a fully-hosted cloud agent platform, stealth browser infrastructure with anti-detect capabilities, CAPTCHA solving, residential proxy rotation across 195+ countries, and custom LLMs fine-tuned for browser control. The cloud platform also offers "Browser Use Box," a persistent 24/7 agent environment integrating Claude Code with Browser Harness, drivable from Telegram, web, or SSH.

Browser Use is classified here under AI Other as its primary category because browser automation agents do not fit neatly into more specialized AI software categories like coding, marketing, or customer service. It serves as horizontal infrastructure that other AI workflows build upon. Secondary categories include AI Infrastructure (for its managed cloud browser and proxy offerings) and AI DevOps (for its CLI tooling and agent harness aimed at developer workflows). Its target audience is primarily developers and engineering teams building agentic applications. The repository has accumulated over 103K GitHub stars, making it one of the most adopted open-source projects in the AI browser agent space.

Impact & Recommendations

Browser Use has established itself as the leading open-source framework for AI-driven browser automation, amassing 103,000+ GitHub stars and a $17M seed round that signals strong market validation. The project, founded in 2024 by Magnus Müller and Gregor Zunic, went from a weekend prototype to one of the fastest-growing open-source tools in the AI ecosystem within months.

Market Position and Competitive Landscape. Browser Use occupies the open-source agent framework layer of the AI browser automation market, which is projected to grow from $4.5B in 2024 to $76.8B by 2034 (32.8% CAGR). Its closest open-source competitors include Skyvern (20,000+ stars, stronger on no-code form-filling workflows, 85.85% WebVoyager score) and Stagehand (23,000+ stars, TypeScript-focused). Browser Use leads on benchmark performance with an 89.1% success rate on the WebVoyager benchmark and a 97% accuracy figure advertised on its site. It also competes with commercial offerings like OpenAI Operator and managed infrastructure platforms such as Browserbase and Steel.

Key Growth Signals. The tool gained 50,000 GitHub stars in just three months, reached 15,000+ active developers early on, and was notably used as a core component by Manus, the viral AI agent from Chinese startup Butterfly Effect, which significantly boosted awareness. Browser Use was accepted into Y Combinator's W25 batch and closed a $17M seed led by Felicis Ventures with participation from A Capital, Nexus Ventures, Paul Graham, SV Angel, and Pioneer Fund. The company has expanded from a single open-source library to a full commercial suite including stealth browsers, hosted web agents, custom LLMs, proxies, and a CLI.

Risk Factors. The AI browser automation space is highly competitive and evolving rapidly, with well-capitalized players like OpenAI and Anthropic building native agent capabilities. The company also faces scrutiny over GitHub star authenticity, as industry investigations have highlighted fake star economies affecting open-source metrics. Reliability remains probabilistic (30-89% task success rates across the category), and anti-bot detection by websites continues to be an arms race.

Competitive Advantages (Moat). Browser Use's core differentiator is its approach of converting websites into structured text for LLMs rather than relying on vision-based screenshot methods, enabling faster and cheaper task execution. Its MIT-licensed open-source model, model-agnostic architecture (supporting any LLM provider), and large developer community create strong network effects and switching costs.

ICP Fit. Browser Use is ideal for development teams building custom AI agents that need web interaction capabilities, startups requiring flexible and self-hostable browser automation, and enterprises wanting to avoid vendor lock-in to single-LLM commercial agent platforms. The cloud tier suits teams needing scalable, managed infrastructure with stealth and proxy capabilities.

Overall Recommendation. Browser Use is the strongest open-source choice for teams building AI browser agents, with the largest community, best benchmark results, and a well-funded commercial roadmap. Its trajectory suggests it will remain a foundational layer in the AI agent stack, though teams should evaluate reliability for production workloads and monitor the competitive dynamics with platform-native agent solutions.

Chiri Analysis

Chiri Score: 78/100

Verdict

Best for:

• Python developers and AI/ML engineers building custom LLM agents that need reliable web navigation and data extraction

• Startups wanting flexible, self-hostable, model-agnostic browser automation without single-LLM vendor lock-in

• Teams needing scalable managed cloud infrastructure with stealth browsers, CAPTCHA solving, and 195+ country residential proxies

• Coding-agent workflows integrating with Claude Code, Codex, and Cursor via the CLI and MCP server

Not for:

• Organizations with sensitive data unwilling to self-host, since the standard cloud plan trains on user inputs with no opt-out

• Non-technical users seeking a fully no-code, form-filling RPA tool (Skyvern fits better)

• TypeScript-first engineering teams (Stagehand is a more natural fit)

• Production workloads requiring deterministic reliability on authentication-heavy or aggressively anti-bot sites like LinkedIn

Head-to-head

Frequently Asked Questions

Is Browser Use SOC 2 compliant?

Yes. Browser Use holds SOC 2 Type II certification with a reporting period of July 17 to October 17, 2025, audited by Accorp Partners. No ISO 27001, HIPAA, or GDPR-specific certifications were found.

How much does Browser Use cost?

Browser Use uses a freemium credit model with four public tiers: Free ($0, 3 sessions, 10 tasks/month), Dev ($29/month), Business ($299/month, 200 sessions), and Scaleup ($999/month, 500 sessions). Usage rates add $0.02/browser-hour, $5/GB proxy bandwidth, and per-step agent charges.

Is Browser Use open source?

Yes. The core Browser Use Python library is MIT-licensed with 103,000+ GitHub stars and installs via pip. It runs on Playwright and supports OpenAI, Anthropic, Google, and Browser Use's own BU 2.0 models. A paid cloud platform layers on managed infrastructure.

Does Browser Use train on my data?

The standard cloud plan trains AI models on user inputs by default with no documented opt-out. For sensitive workflows, Browser Use recommends self-hosting the open-source library, where organizations fully control their compute, keys, and data. Enterprise customers can negotiate custom retention terms.

Who are Browser Use's competitors?

Browser Use's closest open-source competitors are Skyvern (no-code RPA focus) and Stagehand (TypeScript-focused). It also competes with commercial and managed offerings including OpenAI Operator, Browserbase, and Steel.

Is Browser Use good for enterprise?

Browser Use suits enterprises through SOC 2 Type II, isolated Unikraft micro-VM sandboxes, Fortune 500 adoption claims, and enterprise plans with SLAs. However, SSO, RBAC, and audit logs are not publicly documented, and login-protected site reliability requires evaluation.

Who founded Browser Use and is it funded?

Browser Use was founded in 2024 by Magnus Müller (CEO) and Gregor Žunič through ETH Zurich's Student Project House accelerator. It raised a $17 million seed round in March 2025 led by Felicis, with Paul Graham, Y Combinator, Nexus Venture Partners, SV Angel, and others participating. It is a Y Combinator Winter 2025 company.

How reliable is Browser Use for production?

Browser Use reports 97% accuracy on its internal benchmark and an 89.1% WebVoyager success rate, leading its category. However, users report slow execution, high per-task costs, and failures on authentication or anti-bot-heavy sites, so production workflows often need retries and human review.

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Reviewed by Chiri Atlas Research Desk (AI Tooling Analyst) on 2026-07-08.