Rossum

Rossum is a specialized artificial intelligence platform designed to automate and streamline document processing for transactional workflows, particularly in finance, procurement, and accounting operations. The system focuses on handling high‑volume, repetitive document types such as invoices, purchase orders, receipts, and delivery notes, which are common in enterprise resource planning (ERP) environments. The core function of Rossum is its ability to extract, validate, and transform data from structured and semi‑structured documents without requiring manual templates or pre‑defined rules. Using deep learning models trained on millions of document samples, the AI reads key fields—such as invoice numbers, dates, line items, totals, tax amounts, vendor names, and payment terms—from PDFs, scanned images, emails, or digital attachments. The extraction process is adaptive: the system learns from corrections made by human reviewers, gradually improving accuracy over time for each specific client’s document layout. Beyond simple data capture, Rossum integrates with existing business systems to execute end‑to‑end transactional workflows. For example, after extracting invoice data, the AI can automatically match it against purchase orders and goods receipt notes (three‑way matching), flag discrepancies, route exceptions to approvers, send confirmation emails to vendors, and post the final data directly to an ERP system such as SAP, Oracle NetSuite, Microsoft Dynamics, or Coupa. The platform also handles more complex processes like multi‑currency conversions, tax code assignment, and GL coding based on user‑defined standard operating procedures (SOPs). One key feature is the ability to define custom validation rules and approval chains without coding.