BrowserAct, released by EcoCreate Technology on June 25, 2026, is a next-generation open-source browser automation solution that enables AI agents to freely navigate complex and dynamic web ecosystems without human intervention. Just as a human researcher opens a web browser, searches for necessary papers, and collects information through mouse clicks and scrolling, BrowserAct provides AI agents with a highly abstracted digital interface, allowing them to reliably access real-time web data. This system is designed based on a command-line interface (CLI) and an AI-dedicated Agent Skill architecture, serving as an intelligent browsing layer that allows agents to freely create and control browser instances within a terminal environment. It is closely integrated with the Python ecosystem and features a Human-in-the-loop interface, enabling AI to monitor the browser's internal state as needed and autonomously find recovery paths in the event of unexpected script errors or security authentication requirements. Traditional web scraping and browser automation libraries like Selenium or Playwright are optimized for static scripts that operate according to predefined rules, which presents a critical limitation as they are easily blocked when encountering modern web security barriers. In particular, when AI agents autonomously conduct research, they often encounter sophisticated bot detection systems (Anti-bot security) such as Cloudflare, DataDome, and hCaptcha, leading to session invalidation or navigation interruption, which frequently paralyzes the entire research automation pipeline. BrowserAct not only incorporates defense-evasion techniques that intelligently bypass these blocking mechanisms but also provides differentiated functionality through multi-account and multi-session management, allowing for permanent session persistence without having to go through a new login authentication step each time. This is akin to providing an AI agent with an intelligent autonomous vessel that can navigate and avoid obstacles during its exploration of the vast ocean of information on the internet. Furthermore, by precisely controlling the session lifecycle and recording audit logs, it allows for transparent tracking of the path through which data is collected, making it perfectly suited for academic research environments where data reliability is paramount. From the perspective of researchers in biotechnology and drug development, BrowserAct is a powerful tool for autonomously collecting and refining vast amounts of biological data and the latest clinical information scattered across the web. Researchers can use prompt engineering to combine AI agents with the BrowserAct CLI and the latest language models, instructing them to continuously monitor the latest Phase 3 clinical data for specific target proteins on global clinical trial registries (ClinicalTrials.gov) or patent analysis websites. In this process, the agent bypasses complex login security and bot firewalls, parses tabular data rendered in dynamic JavaScript in real-time, and converts it into structured data in JSON or CSV format through structured data extraction, which is then immediately supplied as a training dataset for subsequent statistical analysis or machine learning models, thereby revolutionizing the speed of research and development. In practice, researchers can easily run the CLI in a local development environment, maintaining dozens of independent academic web portal sessions simultaneously, and perform large-scale parallel data engineering tasks, such as automatically extracting and downloading hidden PDF links within papers, with a single line of command.

BrowserAct, released by EcoCreate Technology on June 25, 2026, is a next-generation open-source browser automation solution that enables AI agents to freely navigate complex and dynamic web ecosystems without human intervention. Just as a human researcher opens a web browser, searches for the necessary papers, and collects information through mouse clicks and scrolling, BrowserAct provides AI agents with a highly abstracted digital interface, helping them reliably access real-time web data. This system features a command-line interface (C

🔬 Real-time Structuring of Dynamic Clinical Trial Data: By connecting BrowserAct CLI with GPT-4o, access the dynamic search engine of the ClinicalTrials.gov portal, search for the latest phase 3 clinical data related to the target protein 'KRAS G12C', bypass bot defenses, and precisely extract 50 active clinical data points into a JSON structure within 1.2 seconds for use in subsequent data mining.