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I receive a steady stream of PDF invoices in a 365 mailbox. Every invoice follows the exact same layout, so the key fields—supplier, invoice number, date, net, VAT and gross—can be lifted from fixed coordinates without any OCR guess-work. Your task is to build an end-to-end routine that: I would really like it done in UiPath if possible • Monitors the 365 inbox, downloads each PDF invoice and captures the 2-factor code that arrives in the very same mailbox whenever I sign in to Tungsten Webinvoice. • Parses the predefined data fields from every PDF. • Signs in to Tungsten (Webinvoice) with those credentials, passes the email-based 2FA code automatically, and creates a draft invoice in the portal populated with the parsed data. Because the layout never changes, a rule-based extractor (e.g. PDFMiner, PyPDF2, Tesseract for backup) is fine—I do not need machine-learning. Reliability of the Tungsten login and correct field mapping are the two acceptance criteria: if the script can run unattended and every draft matches the source PDFs, the job is done. Deliver the commented source code, a short read-me on how to deploy, and a quick demo run or screencast showing a PDF sailing from the 365 inbox to a draft record in Tungsten. Read the attached setup suggestion, but everything goes. It just need to be able to run on a local machine and later on parsed to the Cloud if wanted Credeentials will be supplied for tungsten TestInvoice will also be supplied
Project ID: 40379368
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Remote project
Active 4 days ago
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