Run scheduled scraping jobs against target sites

Bright Data runs collection jobs that pull structured data, such as prices, listings, or reviews, from target websites. A Beam agent triggers a job on a schedule or when a request comes in, reads the returned data once the job completes, and applies an approved rule, such as updating a price sheet or flagging a change from the last run. Jobs that fail, return incomplete data, or hit a site that has changed its structure are routed to a person to check rather than retried blindly.

Route requests through managed proxy networks

Because scraping at scale needs requests spread across many IP addresses to avoid being blocked, Bright Data routes traffic through its proxy network. A Beam agent can configure or trigger a job using an approved proxy setup, then monitor whether the job completes successfully or gets blocked, reading the job's status and logs as it runs. Where a job repeatedly fails or a target site appears to have added new restrictions, the agent stops retrying and flags the case for a person to review the setup rather than continuing to send requests indefinitely.

Deliver structured results into downstream systems

Once a Bright Data job returns results, that data needs to land somewhere useful, such as a spreadsheet, database, or another connected tool. A Beam agent reads the completed job output and writes it to the approved destination, applying rules like deduplicating rows or only passing through fields that changed since the last run. Results that look malformed, empty, or far outside the expected range, which may signal the job scraped the wrong page, are held back for a person to check before they reach downstream systems.