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Building the foundations of Somali AI

We build datasets, language and speech models, benchmarks, and research that help AI understand Somali. We publish datasets and models for others to use.

3
Open datasets
67.2h
Speech hours
1.1B+
Corpus tokens
Live demo
Why it matters

Language technology shapes who can take part

Somast is a research company building the datasets, language and speech models, and benchmarks that teach AI to understand Somali.

When AI doesn't understand a language, its speakers are left out of the tools shaping education, work, and public life. Closing that gap is what we build for, and we publish what we build for others to build on.

20M+

Somali speakers worldwide

0.005%

of language-identified web data, vs. 45.5% for English

Education

Students can learn AI and build with technology in their own language, instead of only in English.

Research

Somali data and benchmarks let researchers study a low-resource language rigorously and reproducibly.

Accessibility

Speech models bring reading, writing, and search to millions who communicate mainly by voice.

Digital inclusion

As daily life moves online, Somali speakers need tools that understand how they speak and write.

Partners

Partners and supporters

The organisations that back and build with Somast.

Our approach

From raw data to published models in three steps

01

Collect & annotate

Community contributors, radio archives, and web crawls feed raw Somali text and speech into our pipeline. Every source is documented and licensed.

02

Clean, align & train

Data is deduplicated, filtered for quality, and used to train tokenizers, ASR models, and language models.

03

Publish

Datasets, model checkpoints, evaluation code, and research notes are published under permissive licenses for anyone to use, study, and improve.

Build with us

Build Somali AI with Somast

Use our published datasets and models, contribute to the research, or partner with us.

Somast
995+
GitHub stars
522+
Forks
0
Contributors
  • Researchers

    Use our datasets and benchmarks, co-author studies, and push low-resource NLP forward.

  • Developers

    Build on published models and tokenizers, file issues, and ship Somali-language features.

  • Students

    Join fellowships and bootcamps to learn ML and contribute to real research.

  • Contributors

    Help collect, transcribe, and verify data. Every contribution improves the models.

Need software built, or want to partner with us? Services · Partners

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