Deep-Tech AI Lab

Advancing Arabic AI,
Openly

Nomeda is a deep-tech AI lab building Arabic-first language models, tokenizers, and orchestration systems. We create open-source tools for Arabic NLP — from dialect-aware tokenizers to coding orchestrators that understand Egyptian Arabic, MSA, and English.

Our Focus

Arabic AI Infrastructure,
Built in the Open

Fattah-Orch Family

A suite of lightweight orchestrator models (XS 0.6B to L 8B) that decompose Arabic and English coding requests into structured JSON task graphs. Built on Qwen3, fine-tuned on the first Egyptian Arabic software task dataset — each model routes directly to downstream coding agents.

Arabic-First Tokenizers

Specialized tokenizers for Modern Standard Arabic and Egyptian Arabic — Nomeda-MSA-64K and Nomeda-Egyptian-16K. Designed to capture the full linguistic spectrum from formal text to everyday dialect with high fidelity and low compression loss.

Open Arabic Datasets

We release training data openly to accelerate Arabic AI research. The Fattah Orchestrator Dataset is the first Egyptian Arabic software task decomposition dataset, and Hindawi Arabic Sections provides 52K+ labeled book passages for general Arabic NLP.

Enterprise-Grade Deployment

Designed with production in mind. Our models can run on any target device — from CPU to GPU — and deploy on-premise or in secure cloud environments, giving organizations full control over their AI infrastructure.

Who We Are

Deep-Tech AI Lab

We build the Fattah-Orch family of Arabic-first coding orchestrators, specialized Arabic tokenizers, and open datasets — all released openly on HuggingFace to accelerate Arabic AI research and real-world applications.

Learn more about us

Arabic-Native by Design

Built from the ground up for Arabic and its dialects. Our models understand Egyptian Arabic and MSA natively — not as a translation afterthought — making them more accurate and contextually aware.

Open by Default

Model weights, tokenizer configurations, and datasets are publicly available on HuggingFace. We believe Arabic AI research progresses fastest when the community can build on shared foundations.

Practical by Design

From lightweight 0.6B models running on any CPU to 8B models for GPU inference — our ecosystem is built for real-world deployment, not just benchmarks. Task routing and model specialization keep costs low.

Ready to upgrade your software infrastructure?

Join the developers and enterprises building the future with Nomeda's AI ecosystem.