Keep AI data on your own servers
Keep AI data on your own servers with Prometheus: a practical, on-prem approach built for Azerbaijani teams.
Secure On-Premise AI for the Azerbaijani Language
Prometheus is the first large language model built natively for the Azerbaijani language, specifically engineered for organizations that prioritize data sovereignty and security. Unlike cloud-based alternatives, Prometheus is deployed fully on-premise, ensuring that every query, document, and output is processed entirely within your own network. This architecture eliminates the risk of sensitive data leaving your infrastructure, providing Azerbaijani-speaking teams with a powerful, compliant AI foundation that maintains absolute control over corporate intelligence. By moving beyond translated models, Prometheus offers a deep linguistic understanding rooted in the unique structure of the Azerbaijani language. It is trained on over 651 million curated Azerbaijani words and validated against the rigorous TUMLU benchmark, which encompasses 38,139 native questions across 11 distinct disciplines. Whether you require a massive 587B parameter model for complex reasoning or a streamlined 39B version for efficiency, Prometheus delivers a high-performance AI experience tailored to the specific morphological and grammatical needs of Azerbaijani users.
Advantages of Native On-Premise Azerbaijani AI
Absolute Data Sovereignty: Your data never leaves your network, ensuring full security and compliance from day one.
Native Linguistic Precision: Built-in support for Azerbaijani eliminates the need for inefficient translation layers or workarounds.
Optimized Performance: Processes Azerbaijani text 4.6× more efficiently than general-purpose models, reducing latency and compute costs.
Scalable Infrastructure: Choose from 587B, 99B, or 39B parameter sizes to perfectly match your hardware capacity and workload.
Proven Accuracy: Validated on the TUMLU benchmark with 38,139 native questions across 11 disciplines for objective quality assurance.
Curated Knowledge Base: Trained on 651M+ curated Azerbaijani words to ensure reliable, high-quality language generation.
Core Technical Capabilities
True on-premise deployment
Prometheus runs entirely within your own servers. No cloud calls, no third-party data processing — your documents, queries and outputs stay inside your network boundary at all times.
Native Azerbaijani tokenizer
A purpose-built tokenizer correctly handles the ə character and the agglutinative morphology of Azerbaijani, so the model reads and generates the language as it is actually written and spoken.
Flexible model sizes
Available in 587B, 99B and 39B parameter configurations, allowing your team to match model capability to available hardware without over-provisioning or under-serving your use case.
Azerbaijani-first training data
Trained on more than 651 million curated Azerbaijani words, Prometheus reflects the vocabulary, grammar and context of the language rather than relying on translated or approximated content.
TUMLU benchmark validation
Performance is verified on TUMLU, a benchmark of 38,139 native Azerbaijani questions spanning 11 disciplines — giving you an objective, domain-broad measure of model quality.
Efficiency on Azerbaijani text
Prometheus processes Azerbaijani text 4.6× more efficiently than general-purpose models, reducing compute costs and latency for teams working primarily in the language.
Deployment Workflow
Frequently Asked Questions
Does any data ever leave our servers when using Prometheus?
No. Prometheus is deployed fully on-premise. Every query, document and response is processed within your own network and never transmitted to an external service, ensuring total data privacy.
Why is a native Azerbaijani tokenizer critical for performance?
General-purpose tokenizers often struggle with Azerbaijani's agglutinative structure and specific characters like 'ə'. A native tokenizer handles these correctly, which directly improves accuracy and makes the model 4.6× more efficient on Azerbaijani text.
How do I determine which parameter size (587B, 99B, or 39B) is right for me?
The choice depends on your available hardware and the complexity of your tasks. Larger models offer deeper reasoning, while smaller models provide faster response times. The Allmaz team can help evaluate your infrastructure to recommend the best fit.
What makes the TUMLU benchmark a reliable measure of quality?
Unlike translated tests, TUMLU consists of 38,139 native Azerbaijani questions across 11 different disciplines. This provides an objective, broad-spectrum measure of how the model actually reasons in the native language.
Can Prometheus be integrated into our existing internal software?
Yes. Prometheus provides an API that allows it to be integrated seamlessly with your internal applications, document management systems, and custom workflows, all while remaining within your network.
Deploy Secure AI in Your Infrastructure
Talk to the Allmaz team about deploying Prometheus on your servers — no data leaves your network, and your team works in native Azerbaijani from day one.
Request a demo