AI-powered document processing platform that automates complex transactional document workflows using cognitive data capture, reducing manual data entry by up to 90% and achieving extraction accuracy rates above 98% for invoices, purchase orders, and logistics documents.
Rossum is an AI-native intelligent document processing platform purpose-built for automating transactional documents such as invoices, purchase orders, receipts, and logistics paperwork, offering enterprises a no-template alternative to legacy OCR tools that dramatically reduces manual data entry while continuously improving accuracy through human-in-the-loop active learning. Founded in 2017 in Prague by a team of AI researchers, Rossum has grown into a leading IDP solution serving mid-to-large enterprises across finance, logistics, and shared services.
Unlike traditional OCR-based document capture tools that require manual template configuration for every new document format, Rossum's cognitive data capture engine uses deep learning trained on millions of real-world business documents to understand document context, layout, and semantics automatically. This means new supplier invoices, carrier bills of lading, or purchase order formats can be processed without any upfront template setup, significantly reducing time-to-value for organizations dealing with thousands of document variations.
The platform's 2025-launched Aurora AI engine brings large language model capabilities into the document understanding pipeline, enabling higher accuracy on previously unseen document layouts and more sophisticated extraction of complex tables, line items with header cross-referencing, and multi-page documents. Aurora represents a generational leap in Rossum's processing capabilities, particularly for edge cases that previously required manual handling.
Rossum integrates into enterprise workflows through pre-built connectors for SAP, Oracle, Microsoft Dynamics, NetSuite, and RPA platforms like UiPath and Automation Anywhere. The Rossum Flows no-code workflow builder allows business users to configure validation rules, approval chains, and routing logic without developer involvement. For data validation, the human-in-the-loop interface lets operators review and correct AI predictions on exception cases, with every correction automatically fed back into the model to improve future accuracy.
Deployment options include cloud hosting in EU and US regions, private cloud, and on-premises installation for organizations with strict data residency or compliance requirements. Rossum holds SOC 2 Type II certification and maintains full GDPR compliance with encryption at rest and in transit. The platform supports over 100 languages, making it well-suited for shared services centers and multinational operations processing documents across diverse geographies and languages.
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Rossum's core AI reads documents contextually rather than relying on fixed-coordinate templates. Trained on millions of real-world business documents, it interprets fields based on surrounding layout and semantic cues, enabling automatic extraction from new document formats without manual configuration. This eliminates the template maintenance burden that plagues traditional OCR tools when dealing with thousands of supplier or carrier variations.
Introduced in 2025, Aurora brings large language model capabilities to document understanding. It processes documents with higher variability, extracts data from previously unseen layouts with minimal configuration, and handles complex edge cases like multi-page tables, merged cells, and ambiguous field labels that challenged earlier AI models. Aurora represents Rossum's transition from specialized deep learning to hybrid LLM-augmented extraction.
Rossum provides a validation interface where operators review and correct AI predictions for exception cases. Every correction is automatically fed back into the model, creating a continuous improvement loop that increases accuracy over time. This approach ensures that the system adapts to each customer's specific document patterns and reduces the exception rate progressively as more documents are processed.
A visual, no-code tool for configuring validation rules, routing logic, and document processing workflows without developer involvement. Flows enables business users to set up approval chains, field-level validation against master data, conditional routing based on document attributes, and multi-step processing pipelines that connect extraction to downstream systems like ERPs and accounting platforms.
Pre-built connectors for SAP, Oracle, Microsoft Dynamics, NetSuite, and RPA platforms like UiPath and Automation Anywhere allow organizations to plug Rossum into existing enterprise workflows. A REST API and webhook framework support custom integrations, enabling bidirectional data flow between Rossum and virtually any business system for end-to-end document processing automation.
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In 2025, Rossum launched its Aurora AI engine, which integrates large language model capabilities into the document processing pipeline for improved handling of variable layouts, previously unseen document formats, and complex multi-page table extraction. Aurora represents the platform's most significant AI upgrade since its founding, enabling higher straight-through processing rates and reduced exception handling for edge-case documents. Additionally, Rossum expanded its ERP connector library and enhanced the Rossum Flows no-code workflow builder with new conditional routing and multi-step validation capabilities for more sophisticated document processing pipelines.
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