Hook: GDPR doesn't end at the Bosphorus. Arab-language PII in EU business workflows is systematically unprotected.
The Challenge
Right-to-left languages (Arabic, Hebrew, Persian, Urdu) present unique challenges for NER systems designed around left-to-right text flow. Beyond directionality, Arabic and Hebrew use root-based morphology where names can appear in multiple inflected forms, making both regex and standard NLP models unreliable. Organizations in the MENA region processing Arabic-language customer data for GDPR compliance (for EU operations) or handling bilingual Arabic/English documents face systematic PII invisibility. The problem affects financial services (KYC documents), healthcare (patient records), and government (identity documents) across the entire Arab world and Israel.
By the Numbers
- Organizations in the MENA region processing Arabic-language customer data for GDPR compliance (for EU operations) or handling bilingual Arabic/English documents face systematic PII invisibility.
Real-World Scenario
A fintech company in Dubai processing KYC documents for EU clients. Documents contain Arabic customer names and UAE Emirates IDs alongside English business data. GDPR applies to the EU client relationship data. Without RTL PII detection, Arabic name fields are invisible to the compliance system.
Technical Approach
XLM-RoBERTa provides cross-lingual entity recognition for Arabic and Hebrew with full RTL text handling. The platform includes Arabic, Hebrew, Persian, and Urdu in its 48-language support stack.
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