AI-Guided Page Parsing

ScrapeGraphAI reads a web page and returns the fields you describe, using a model to find them even when the layout shifts. A Beam agent sends the pages and the field list your team approved, reads the parsed output, and writes the values into your records. It runs on your schedule and notes each parse. Pages where the model returns low confidence, blank fields, or output that fails your validation are not stored as-is; the agent flags the result and routes it to a person, who checks the page and corrects the extraction before it saves.

Prompt-Based Field Extraction

With ScrapeGraphAI you name the data you want in plain language and the API returns it structured. A Beam agent applies the approved prompt to each target, reads what comes back, and maps the fields onto your schema so records stay consistent. It updates the record and logs the source. Results that miss a required field, contradict a known value, or look off against your rules are not committed; the agent parks them and hands the case to a person, who reviews the output and confirms or corrects it before it lands.

Scheduled Data Refresh

ScrapeGraphAI can re-parse the same sources so stored data stays current. A Beam agent re-runs each source on the cadence your team set, reads the new values, and updates only the fields that changed under the rules you defined. It records every refresh and the differences it applied. A source that starts returning errors, a sudden swing in values, or a page that blocks the request is not overwritten quietly; the agent pauses that source and notifies an operator, who reviews it and decides whether to resume or adjust the job.