Zakhir
Fintech AI Transformation Case Study
Arabic support AI that works in production - dialect-tuned and self-hosted
AI Responses in Production
A bilingual AI support layer for a digital wallet serving thousands of users - handling inbound across WhatsApp, Instagram, Messenger, and web chat in Arabic and English. The Arabic side is powered by a custom Sudanese-dialect model we fine-tuned on open weights and self-hosted, so replies sound native rather than stiff formal Arabic. It handles 87% of inbound conversations end-to-end, escalating the complex cases to human agents.
The Problem
- Off-the-shelf Arabic AI defaults to formal Modern Standard Arabic and sounds foreign to Sudanese users
- Support tickets flooding across disconnected channels - WhatsApp, social media, web chat - with no unified view
- Agents overwhelmed by repetitive queries in both Arabic and English
- No after-hours coverage - customers left waiting outside business hours
Our Solution
Generic Arabic AI answers in stiff, formal Modern Standard Arabic that reads as foreign to Sudanese customers - so we built a dialect model instead. We fine-tuned an open-weight LLM on a purpose-built Sudanese-Arabic dataset and self-hosted it, keeping the model on infrastructure we control rather than a third-party API. On top of it we built a unified AI support layer across WhatsApp, Instagram DMs, Facebook Messenger, and web chat, with RAG-powered knowledge retrieval, a secure OTP delivery API for the mobile app, automated issue classification, and smart escalation to human agents for the complex cases. The system is hardened against prompt injection and manipulation attempts.
What We Delivered
ROI & Impact
87%
Of inbound conversations handled end-to-end by AI
42,000+
AI responses in production
8,500+
Support sessions handled
24/7
Two languages, zero night-shift hires
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