Rossum vs Lettria

Rossum reads invoices, purchase orders, bills of lading, and other transactional documents, then extracts, validates, and posts the data to your ERP. AI agents ingest files from email, scanners, PEPPOL, or shared drives, run them through the Aurora Document AI engine, and route exceptions to a human validation screen when needed. The platform supports 276 languages plus handwriting and learns from user corrections over time.

OCR tools that only pull text leave your team to fix errors in spreadsheets. Rossum cross-checks extracted fields against master data, ERP records, and business rules, infers GL codes and tax codes, and triggers approval workflows or vendor emails automatically. Business and Enterprise tiers add duplicate detection, intelligent mailboxes, custom webhooks, and certified connectors for SAP, Coupa, Workday, and Oracle.

Rossum targets finance and operations teams drowning in AP paperwork, logistics companies processing shipping documents, and enterprises facing e-invoicing mandates. More than 450 brands use it, Everest Group named Rossum a Leader in its 2026 IDP PEAK Matrix, and Coupa acquired Rossum to extend its spend management stack.

Lettria builds a graph context layer that turns enterprise documents and databases into ontology-backed knowledge graphs for automation teams. Its Knowledge Studio GraphRAG product parses PDFs, tables, SAP exports, and scanned annexes, then answers multi-hop questions with source citations. Perseus is the developer platform for generating ontologies and graphs without hand-modeling every entity.

Vector RAG tools retrieve similar chunks; Lettria follows explicit relationships across structured and unstructured data. The company publishes benchmark comparisons showing graph agents at 81.7% overall accuracy versus 57.5% for vector agents, plus text-to-graph claims of 30% higher accuracy and up to 400x faster extraction than general LLMs. That trade-off favors regulated teams that need audit trails over quick semantic search.

Finance, healthcare, legal, and engineering groups use Lettria for ESG filings, biomedical literature, contract corpora, and technical manuals. Case studies cite Alfa Laval (+30% extraction accuracy), AP-HP (+60% faster research), and Wisecube processing 108 GB of biomedical text into 500+ monitored classes.