BrowserQL provides a Browser-as-a-Service platform that delivers fingerprint‑free, stealth automation for Puppeteer and Playwright workloads.
Funding
Funding not disclosed
Founders
Product
Problem
Web automation and scraping scripts often fail against modern bot detection systems such as Cloudflare and DataDome, and managing a fleet of browsers at scale introduces memory leaks, version drift, and high proxy costs.
Solution
BrowserQL offers a Browser-as-a-Service platform that provides fingerprint‑free, stealth automation for Puppeteer and Playwright workloads. It runs a managed pool of browsers behind a WebSocket endpoint, automatically evading detection, auto‑solving CAPTCHAs, and simulating human mouse and keyboard behavior. Session persistence lets browsers be reused across requests, reducing repeated bot checks and cutting proxy usage by up to 90 %. The service handles scaling, load balancing, and custom machine configurations, while exposing PDF, screenshot, and download APIs for common output needs. Users can monitor health, metrics, and debug sessions through a built‑in dashboard, enabling reliable, enterprise‑grade automation without managing infrastructure.
Target Audience
Primary customers are development teams and enterprises that run large‑scale web scraping, data extraction, or browser‑based automation pipelines and need to bypass anti‑bot measures reliably.
Features
- Zero‑fingerprint browser runtime with hidden debugger protocol and built‑in stealth techniques
- Automatic CAPTCHA solving, including nested iframes and shadow DOM elements
- Humanized mouse movements, scrolling, and typing patterns to avoid behavior detection
- Session persistence and reconnect API to reuse browsers, cache, and cookies across runs
- Scalable pool of managed browsers with automatic load balancing and memory‑leak protection
- WebSocket endpoint compatible with existing Puppeteer or Playwright scripts
- PDF, screenshot, and file download APIs accessible via REST
- Enterprise options for custom GPU, OS, cloud provider, and private deployment