Use Cases
Natural Language Processing (NLP)
Decode and process language.
Back to Solutions
Arabic NLP is underserved: rich morphology, broken plurals, optional diacritics, and dialectal variation make off-the-shelf datasets too thin for serious models.
We build NLP datasets from scratch — annotated by trained linguists — covering the full pipeline from pretraining corpora to instruction-tuning and preference data.
What we deliver
- NER, sentiment & POS-annotated corpora
- Parallel and comparable translation corpora
- SFT prompt/response pairs
- RLHF preference rankings
- Dialect identification & normalization datasets
How we work
Our linguistic team defines annotation guidelines with your researchers, trains annotators per dialect, and enforces quality through gold-standard insertion and agreement metrics on every batch.
Ready when you are
Let's build the next generation of Arabic AI together.
Tell us about your project — speech, text, image, video, or LLM data. We'll scope volumes, languages, and delivery — usually within one business day.