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Somast, short for Somali Science and Technology, is an open Somali-AI research lab. We make it easy for developers, researchers, and learners to build with language technology that understands Somali: open datasets, foundation models, and a free, hands-on data-science and ML training path, all released in the open.
Why we started
Somali is spoken by more than 20 million people, yet it holds an almost invisible share of the data that trains modern AI, a fraction of a percent of what English alone contributes. Every model, tokenizer, and benchmark we tried to use for Somali either didn't exist or quietly failed on the language's morphology and dialects.
So in 2023 we started building the missing layer ourselves: collecting and annotating text and speech, publishing it under open licenses, and training the first Somali-native benchmarks and models on top of it. Alongside the research, we opened a free Data Science & ML bootcamp so the people who will build Somali AI next could learn the skills to do it themselves.
Three years in, that combination (open data, open models, open education) has grown into a corpus of 1.1B+ tokens, 320+ hours of speech, a handful of Somali-native models, and 200+ alumni from our cohorts. We're still at the beginning of closing the gap.
Open AI infrastructure for the Somali language, built with the community.
We believe a language shouldn't need a trillion-dollar company behind it to be understood by AI. Every dataset, model, and benchmark we publish is meant to lower that bar for the next person building in Somali.
- Company name
- Somast
- Legal name
- Somast LLC
- Name stands for
- Somali Science and Technology
- Founded
- 2023
- Headquarters
- Mogadishu, Somalia
- Website
- somast.so
One-liner
Open AI infrastructure for the Somali language.
Short (25 words)
Somast is an open Somali-AI research lab building datasets, foundation models, and a free data-science training path, all released in the open.
Long (100 words)
Somast, short for Somali Science and Technology, is an open research lab building the AI infrastructure the Somali language has never had. Instead of leaving Somali as an afterthought in models trained mostly on English, Somast collects and publishes open datasets, text and speech, and trains Somali-native tokenizers, models, and benchmarks on top of them, all under permissive open licenses. Alongside the research, Somast runs a free, hands-on Data Science & Machine Learning bootcamp so Somali engineers and researchers can build on that foundation themselves. Everything is public: the data, the model cards, the benchmark results, and the curriculum.
The people building it
Brand colors
Deep Teal accent on a calm, neutral base.
Logo usage
Keep clear space around the mark of at least the logo's own height. Use on white, soft neutral, or near-black backgrounds.
Use the SVG wherever possible so it stays crisp at any size.
Don't recolor, recreate, add effects to, or stretch/skew the mark.
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For press inquiries, interviews, or additional information, our team is glad to help.