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Category
Technology
Built by
Beam.ai
Harvest structured data with ParseHub projects and write results downstream, automating scraping work like running scheduled jobs and validating exports.
Visual scrape configuration
ParseHub defines web scraping projects by pointing at page elements. A Beam agent runs the projects a customer has set up, reads the data each returns, and applies your rule for what a valid result looks like. Complete results move to the destination system and are tagged with their run, while incomplete ones are retried within limits. Runs that return an unexpected structure, hit a changed layout, or come back empty are routed to a person to check the project before further attempts. The agent keeps scheduled scrapes producing usable data without someone watching every run.
Scheduled run execution
ParseHub runs scraping projects on a schedule. A Beam agent launches or picks up these runs, reads their status and output, and applies your rule for handling complete, partial, and failed results. Good runs are passed downstream and marked done, while failures are retried per policy and noted. Repeated failures, access blocks, or output that shifts sharply from prior runs are escalated to a person to investigate. This keeps recurring runs finishing on their own, while a human hears about the runs that genuinely broke instead of discovering stale data later on.
Structured export handling
ParseHub outputs scraped data in structured formats for other systems. A Beam agent receives each export, reads the fields it contains, and applies your rule for completeness and format before anything moves on. Well-formed exports are written to the destination and recorded with their source and time, while malformed or short ones are held. Exports that look inconsistent with expected volume or shape are routed to a person to confirm before they enter downstream systems. The agent forwards dependable data automatically and raises only the batches that need a human eye first.







