Arzi

Pre-launch

Building the Arabic data engine for AI

Curated, human-generated datasets across text, speech, and conversation, created by native speakers from every major Arabic dialect. We are not live yet. Join the waitlist to get early access and updates.

What is Arzi?

Arzi produces high-quality, multimodal Arabic data created by native speakers to support the next generation of Arabic foundation models. We focus on dialect diversity, cultural context, and rigorous quality assurance to improve model performance across the Gulf and the region.

Data Types

Text corpora

curated editorial + web, de-dup, license-aware, PII scrub

Speech & ASR

read and conversational; GCC/Levant/North Africa accents; varied noise profiles

Human-Human Conversations

multi-turn, task and open-domain, safety-screened

RLHF & Preference Data

pairwise rankings, critiques, instruction following

Evaluation Packs

Arabic benchmarks for dialect coverage, safety, hallucination, reasoning

The Problem

Arabic models lag due to low-quality or MSA-only data that ignores dialects and cultural context.

Our Vision

A native, dialect-rich, human-first data layer for Arabic AI across pretraining, fine-tuning, RLHF, and evaluation.

Tell us what you need. We will notify you when datasets and pilots are ready.