Field notes · Topic
Turkish & multilingual.
In Türkiye and the Gulf, work often moves between languages in the same day, sometimes in the same sentence. These notes cover what changes when an AI system has to read, search, listen and answer in more than one language.
6 notes
Notes on this topic
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What makes Turkish hard for AI, and how to design around it.
Turkish builds meaning with suffixes, has a dotted and dotless i that breaks naive software, and often shares a sentence with English. None of that stops a good system; it means testing on real Turkish text and designing search, casing and tone on purpose.
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Designing AI for teams that work in Turkish and English.
In many organizations the question arrives in Turkish, the policy is in English and the customer writes in both. Decide which language answers go out in, search across languages, cite the source in its original language and evaluate in both.
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Reading Turkish documents with AI: OCR, tables, stamps and signatures.
Most document errors start before the model: a scanner that reads ş as s, a table flattened into a paragraph, a stamp over an amount. Route each document type deliberately, measure errors on Turkish characters and key fields, and send unreadable pages to a person.
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Turkish speech-to-text for calls and meetings: what affects accuracy.
Transcription quality decides everything downstream in call and meeting intelligence. Errors cluster in phone audio, accents, crosstalk, numbers, names and English terms inside Turkish speech; measure on your own recordings and design review around the words that matter.
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AI translation at work: when it’s good enough and when it isn’t.
AI translation is good enough for understanding and internal drafts, and risky for contracts, regulated text and anything published under your name without review. A glossary, a reviewer for high-stakes text and a clear rule on what may be sent where make the difference.
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Arabic and English in one AI system: what to plan for in the Gulf.
In the Gulf, work moves between Arabic and English, and Arabic itself spans formal written Arabic, dialects and Latin-script chat. Plan for script and direction, name spellings across scripts and native reviewers, and test quality per language instead of assuming it.