Arabic needs context, not translation
Dialect, measurement, and user experience in conversational automation.
Arabic in production is rarely MSA-only. Gulf customers write the way they speak; a bot trained on formal news corpora can sound grammatically correct and still fail the conversation.
We pair dialect-aware design with evaluation: grounded answers, clear handoffs to humans, and model choices that survive cost and compliance reviews — the essays below walk through that stack.
- Why most Arabic AI bots fail.
It is not the model. It is that we train it on Arabic no one actually speaks, then act surprised when no one understands it back.
- GPT-4 vs Claude vs Gemini — an objective comparison.
This is not a popularity vote. It is a decision frame: what differentiates each family, where each leads, where each weakens, and how to choose without buying the myth of a single "best" model.