Arabic LLM Training Data: SFT, RLHF and Evaluation in Real Dialects
Instruction data, preference rankings and evaluation sets written and judged by native speakers of Gulf, Egyptian, Levantine and Maghrebi Arabic, not translated English. Free pilot batch before you commit.
Why Arabic LLMs need dialect-native data
Most Arabic training data is Modern Standard Arabic or machine-translated English. Users don't talk like that. They write in Saudi, Emirati, Egyptian or Moroccan dialect, switch into English mid-sentence, and use Arabizi (Arabic in Latin letters). A model trained on translated data sounds stiff, misreads intent and fails cultural checks.
AI Taggers produces Arabic LLM training data with native speakers of each dialect: supervised fine-tuning (SFT) pairs written from scratch, RLHF and DPO preference judgements, and evaluation and red-teaming sets that test dialect fluency, factuality and cultural appropriateness.
Projects are run under Australian-led QA with dialect-specific guidelines, agreement checks and data handling that can meet Saudi PDPL and UAE data-protection requirements.
Arabic LLM data we deliver
Arabic SFT / instruction data
Prompt-response pairs and multi-turn conversations written natively per dialect, across domains like government services, banking, retail and healthcare.
Arabic RLHF & DPO preferences
Pairwise rankings, rubric scores and rewrites judged by native speakers for fluency, accuracy and cultural fit.
Arabic evaluation sets
Human-scored benchmarks for dialect understanding, factuality and safety, beyond MSA-only public leaderboards.
Arabic red teaming
Adversarial prompts in dialect and Arabizi to find safety bypasses English-only red teams miss.
Code-switching & Arabizi
Data reflecting how Arabic users really type: Arabic-English mixing, Latin-script Arabic and regional slang.
Arabic speech & RAG data
Dialect speech transcription and Arabic retrieval-QA pairs for voice assistants and RAG systems.
How a project runs
- 1
Dialect and domain scoping
We agree target dialects, domains, task types and the output schema your pipeline needs.
- 2
Free pilot batch
25-50 items produced by native speakers of your target dialects, returned in 24-48 hours.
- 3
Guideline calibration
Dialect-specific edge cases (code-switching, honorifics, religious and cultural references) are written into the guidelines.
- 4
Production with QA
Scaled delivery with native-speaker review, agreement tracking and regular quality reports.
How Arabic LLM data pricing works
Arabic LLM data is priced per item (per written pair, per comparison, per evaluated response) or per hour for open-ended writing. We quote after the free pilot.
Typical per-unit rates for image, text, audio and video work are on our pricing page.
Best fit for
- Teams building or fine-tuning Arabic or bilingual LLMs
- Gulf government and enterprise AI programs (Vision 2030, UAE AI strategy)
- Global labs adding Arabic to a multilingual model
- Chatbot and voice products serving Arabic-speaking customers
Frequently asked questions
Which Arabic dialects do you cover?
Gulf dialects (Saudi Najdi and Hijazi, Emirati, Kuwaiti, Qatari), Egyptian, Levantine (Syrian, Lebanese, Jordanian, Palestinian), Iraqi and Maghrebi (Moroccan Darija, Algerian, Tunisian), plus Modern Standard Arabic and Classical/Quranic Arabic.
Why not translate English instruction data into Arabic?
Translated data teaches the model translated Arabic: formal, unnatural and missing dialect, code-switching and cultural context. Native-written data produces responses that read like a local speaker wrote them.
Can you handle Arabizi and Arabic-English code-switching?
Yes. We write and label data that mixes Arabic and English and uses Latin-script Arabic, because that is how many users in the Gulf and Egypt actually type.
Do you meet Saudi PDPL and UAE data rules?
We design data handling to the requirements of each project, including access controls, retention limits and residency constraints. Tell us your obligations during scoping and we build the workflow around them.
How do we start?
Send a sample of prompts or a description of the data you need. We return a free pilot batch in your target dialects within 24-48 hours, then quote for production.
Get a free Arabic LLM data pilot
Tell us your target dialects and task type (SFT, preference ranking, evaluation). We return 25-50 native-speaker items in 24-48 hours.
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