Use this table to document each field you extract:
| Field Name (output) | Source Path (selector / regex / cell) | Data Type | Validation Rule | Fallback Value | |---------------------|----------------------------------------|-----------|----------------|----------------| | InvoiceNumber | //div[@class='inv-num']/text() | String | Not empty | "MISSING" | | DueDate | table row 3, col 2 | Date | yyyy-MM-dd | +30 days from today | | TotalAmount | after "$" until space | Decimal | >0 | 0.0 | rpa extractor
A dropshipping retailer gets order confirmation emails from Amazon, eBay, and a custom Shopify store. Use this table to document each field you
The extractor is capable of processing data from multiple sources simultaneously: A dropshipping retailer gets order confirmation emails from
The RPA Extractor enables bots to move beyond simple screen scraping by utilizing advanced recognition technologies to extract structured and unstructured data. It bridges the gap between physical documents, legacy systems, and modern digital workflows by converting visual information into actionable data.