QOSI — Qazaq Open Source Initiative is a non-profit organization focused on advancing open-source technology adoption across Kazakhstan and Central Asia.
We work at the intersection of open-source AI, cloud-native infrastructure, digital sovereignty, education, and public-sector innovation. Our mission is to make modern technology more accessible, transparent, and reusable for governments, universities, startups, enterprises, and local developer communities.
On Hugging Face, QOSI aims to publish and support open resources for:
We support the development of open Kazakh-language resources, including datasets, evaluation benchmarks, models, tokenization experiments, OCR workflows, speech resources, and practical NLP tooling.
QOSI promotes AI literacy through open learning materials, practical labs, model demos, and infrastructure patterns that can be reused by schools, universities, companies, and public organizations.
We advocate for transparent, auditable, and locally deployable AI systems built on open-source foundations — especially for sensitive, regulated, or public-interest workloads.
We believe responsible AI development requires high-quality datasets, clear documentation, transparent evaluation, and reproducible benchmarks.
QOSI supports collaboration between engineers, researchers, policymakers, students, and open-source communities across Kazakhstan and Central Asia.
This Hugging Face organization may include:
| Repository Type | Purpose |
|---|---|
| Datasets | Kazakh-language, regional, educational, and public-interest datasets |
| Models | Fine-tuned or experimental open models for Kazakh and regional use cases |
| Spaces | Interactive demos, prototypes, and educational tools |
| Benchmarks | Evaluation suites for language, reasoning, OCR, speech, and domain tasks |
| Collections | Curated open-source AI resources relevant to Kazakhstan and Central Asia |
QOSI follows a practical open-source philosophy:
We encourage every model and dataset published under QOSI to include clear documentation covering:
For sensitive use cases, we recommend local review, domain validation, and compliance checks before production deployment.
We welcome collaboration with:
Potential collaboration topics include Kazakh NLP, OCR, speech recognition, open datasets, public-sector AI assistants, AI education, and cloud-native AI infrastructure.
Building open technology capacity for Kazakhstan and Central Asia.