Browse AI is a no-code web scraping tool that trains robots to extract data and monitor any website, without writing a single line of code.
Browse AI makes web scraping accessible to anyone. You point its recorder at a page, click the data you want, and it creates a robot that extracts that data on demand or on a schedule. Robots handle pagination, scrolling and detail pages, and can monitor pages for changes and send alerts when something moves.
The platform integrates with Google Sheets, Zapier, Airtable and webhooks, so extracted data flows straight into workflows. Prebuilt robots for popular use cases — LinkedIn, real estate listings, product prices — get teams started in minutes, and the infrastructure handles proxies and anti-bot measures for you.
Robots are resilient by design: when a site’s layout changes, Browse AI’s adaptive extraction and self-healing selectors keep data flowing, and failed runs can be retried automatically. The monitoring mode compares page states over time and alerts you to price changes, new listings or content updates. For teams, shared workspaces, bulk exports and scheduling options make Browse AI suitable for recurring operational data needs rather than one-off grabs.
Browse AI offers a free plan with monthly credits; paid plans scale credits, concurrency, monitoring frequency and add team features.
Marketers, researchers and operations teams who need recurring web data without engineering resources.
Yes, a free plan provides monthly extraction credits for trying the platform and light use.
Yes — Browse AI provides a REST API and webhooks for triggering robots and receiving extracted data.
Its recorder-style setup is easier than selector-based scrapers, and monitoring is built in rather than bolted on.
Yes — Browse AI supports authenticated extraction from sites behind login screens, in addition to handling pagination and dynamic content.
Marketing teams track competitor pricing and content changes, sales teams build lead lists from directories, real estate professionals monitor new listings and researchers collect data at regular intervals. Robots run on schedule and push results into Google Sheets, Airtable or webhooks, so collected data lands directly in the workflows that consume it.
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