Category
Technology
Built by
Beam.ai
Harvest data from target websites and file the results into your systems, automating research work like refreshing competitor price lists on a schedule.
Scheduled scrape runs
ScrapeNinja fetches page content from URLs you supply. A Beam agent starts a run on a set schedule, requests the target pages, and reads the returned HTML or structured payload. It applies your approved parsing rule, writes the cleaned fields into the destination system, and marks the job complete. When a page returns an unexpected layout, an empty body, or a status code the rule does not cover, the agent leaves the record untouched and routes the case to a person, who decides whether the selector needs updating or the source itself has quietly changed.
Proxy and block handling
Many sites reject automated requests. ScrapeNinja routes calls through proxies and retries when a request fails. A Beam agent watches the response codes on each run, and when a fetch is refused it applies your retry rule before trying again through a fresh route. Successful pages pass into the parsing step and results are stored against the source record. If a domain keeps refusing after the allowed retries, the agent stops, notes the failure count, and hands the site to a person, who checks whether the target now needs a different approach entirely.
Structured data output
ScrapeNinja can return page content as fields rather than raw markup. A Beam agent maps those fields to your schema, reads each value, and applies the approved validation rule before writing rows into your database or sheet. Records that pass land in the target table with a source timestamp. Rows with missing required values, or values outside the expected range, are held back and flagged for a person to inspect, so a broken selector never quietly fills your system with blank or malformed entries during an unattended overnight collection run.






