Intelligent document processing & OCR
Turn your stacks of Arabic and French files into structured, reliable, usable data.
The challenge
Administrations, banks and law firms are buried under paper or scanned documents: contracts, deeds, forms, statements, civil-registry files. Manual data entry is slow, costly and error-prone, while the information stays locked inside images that systems cannot use.
The difficulty is compounded by Arabic/French bilingualism, cursive connected Arabic script, complex layouts (tables, stamps, handwritten signatures) and uneven scan quality. Generic OCR fails on Arabic and does not understand the logical structure of documents.
Our approach
Shift builds an end-to-end document-processing pipeline. We start with layout understanding using LayoutLM-style models that identify text blocks, tables, signature areas and key fields, even on degraded documents.
Next comes a bilingual OCR specifically adapted to cursive Arabic and French, followed by LLM-based information extraction: the large language model reads the recognised text and extracts structured entities (parties, amounts, dates, clauses), with a per-field confidence score and business-rule validation.
Uncertain cases are routed to human review in a dedicated interface, and every correction feeds continuous improvement. The output integrates with your systems (ECM, core banking, ERP) via API, with a dramatic cut in processing times and full traceability.