BrowserAct is a no-code web scraping platform that builds a reusable scraper from one prompt. Users enter a website URL and describe the data they need; an AI agent explores the live site, picks a scraping approach, identifies fields and produces a tested Bot. In the example shown, building a Bot uses 320 credits and each later run uses 20 credits. The Bot returns structured data as a spreadsheet, and users can ask for another field later. Managed infrastructure handles Chromium sessions with 30+ fingerprint attributes, global residential proxies, CAPTCHA solving, scheduling and self-healing when pages change. Results go to CSV, JSON, API, webhooks, Make, n8n, Zapier, Google Sheets and Airtable.
BrowserAct is for people who need fresh web data but do not want to write scrapers or manage browser infrastructure. Marketers tracking competitor prices, e-commerce teams researching products and suppliers, and sales teams building lead lists can use it without code. Researchers collecting creator, launch or job-market data can schedule regular runs. Operations and data teams can feed structured output into spreadsheets and automation tools. A second usage mode gives a local AI agent its own browser through MCP, which appeals to developers building agent workflows who need reliable web access without maintaining proxies and stealth settings themselves.
A retailer can build a headphone price tracker: enter a store URL, describe the product names, prices and stock, and receive a Bot that outputs a spreadsheet on each run. Adding customer ratings later is a matter of asking for the new column. A recruiter can monitor job-market listings, an agency can collect customer and competitor research, and a sourcing team can compare supplier products. Output flows into Google Sheets or Airtable, or triggers workflows in Make, n8n and Zapier through webhooks. Because Bots run on cloud browsers around the clock, results stay current without anyone keeping a machine running.
