On-premise Azerbaijani LLM for Government
On-premise Azerbaijani LLM for government. Public bodies require on-premise systems so citizen data never leaves the country.
A Sovereign AI Foundation Built for Azerbaijani Government
Public institutions handle the most sensitive data a nation holds — citizen records, legal documents, procurement files, and audit trails. Allmaz delivers the first large language model built natively for the Azerbaijani language and deployed entirely on-premise, so that data never leaves your network, your jurisdiction, or your control. Trained on more than 651 million curated Azerbaijani words and validated on the TUMLU benchmark across 38,139 native questions spanning 11 disciplines, the model is purpose-built to understand the formal registers, legal terminology, and administrative language that government work demands — not adapted from a general-purpose system as an afterthought.
Why Government Bodies Choose Allmaz
Complete data sovereignty: all inference runs inside your own infrastructure, with no citizen data transmitted to external servers, third-party clouds, or Allmaz systems at any point during installation or operation.
Native Azerbaijani language accuracy: trained on over 651 million curated Azerbaijani words, the model reliably interprets official documents, legal terminology, administrative correspondence, and public-service language as it is actually written and spoken in Azerbaijan.
Proven processing efficiency: the native tokenizer handles the ə character and agglutinative morphology correctly, making Allmaz 4.6 times more efficient on Azerbaijani text — directly reducing processing time and infrastructure load when handling large government document volumes.
Scalable parameter configurations: the 587B model serves central ministries with complex, high-volume workloads; the 99B and 39B options suit regional offices and specialized applications where hardware capacity is more constrained, with all sizes sharing the same sovereign deployment model.
Benchmark-validated reliability: performance is independently verified on the TUMLU benchmark — 38,139 native Azerbaijani questions across 11 academic and professional disciplines — giving procurement officers and audit teams an objective, reproducible quality reference.
Faster public-service delivery: automating document review, records search, entity extraction, and citizen inquiry drafting frees civil servants to focus on higher-value casework, reduces response backlogs, and supports measurable improvements in service throughput.
Core Capabilities for Public Sector Workflows
True On-Premise Deployment
The model runs entirely within your data center or government private cloud. No API calls leave the network perimeter, satisfying data-residency requirements and eliminating exposure to external breaches or policy changes by third-party vendors.
Azerbaijani-Native Tokenizer
Most general-purpose models fragment Azerbaijani words incorrectly, losing meaning and inflating token counts. Allmaz's tokenizer correctly handles the ə character and the language's agglutinative morphology, producing accurate outputs on official Azerbaijani text from the first token.
Large-Scale Document Processing
Government archives contain millions of pages of regulations, case files, and correspondence. The model can summarize, classify, extract key entities, and cross-reference records at scale, reducing the manual burden on civil servants handling high document volumes.
Procurement and Audit Support
Automate the review of tender documents, flag inconsistencies in supplier submissions, and generate structured audit summaries — all within your secure environment, with a full local log for transparency and accountability.
Citizen-Facing Service Drafting
Draft responses to citizen inquiries, generate plain-language summaries of regulatory decisions, and prepare multilingual notices — with human review remaining in the loop before any communication is issued.
Flexible Parameter Sizing
The 587B model suits central ministries requiring maximum capability; the 99B and 39B options are appropriate for regional offices or specialized applications where hardware resources are more constrained. All sizes share the same sovereign deployment model.
From Procurement to Production
Frequently Asked Questions
How can we be certain that citizen data never leaves our infrastructure?
The model is installed and runs entirely on servers you own and operate. There are no outbound API calls, no telemetry sent to Allmaz, and no dependency on external cloud services during inference. Your network and security teams retain full visibility and control at every stage, from initial installation through day-to-day operation.
What objective evidence exists that the model performs reliably on Azerbaijani-language content?
The model has been validated on the TUMLU benchmark, which comprises 38,139 native Azerbaijani questions spanning 11 academic and professional disciplines. This provides a reproducible, discipline-specific measure of language quality that procurement officers, IT leads, and audit teams can reference when evaluating the system against institutional standards.
Which parameter size is appropriate for a central ministry versus a regional office?
The 587B parameter model is suited to institutions with high-volume, complex document workloads and the hardware infrastructure to support it. The 99B and 39B models are designed for environments with more constrained on-premise resources while still delivering strong Azerbaijani-language performance. Allmaz conducts a structured requirements assessment with your IT and legal teams to identify the configuration that best matches your workload and hardware capacity before any procurement decision is made.
Can the model accurately handle the formal and legal register used in official Azerbaijani government documents?
Yes. The model was trained on over 651 million curated Azerbaijani words, including formal, official, and legal text. The native tokenizer correctly processes Azerbaijani agglutinative morphology, which is essential for accurately interpreting the compound and inflected word forms that appear frequently in legal statutes, administrative regulations, and procurement documentation.
How does Allmaz support procurement transparency and audit requirements?
Because the model operates entirely on your infrastructure, all inputs, outputs, and system logs remain within your own systems and are governed by your existing audit and records-management policies. Allmaz retains no access to your usage data, ensuring that complete audit trails stay solely under your institution's custody and are available for internal or external review at any time.
What happens when the model needs to be updated or patched after deployment?
Allmaz delivers maintenance releases, security patches, and model updates through your institution's approved change-management process. All updates are applied within your network boundary using the same sovereign deployment model as the initial installation, so no data leaves your environment and your security and compliance posture is maintained throughout the lifecycle of the system.
Ready to Deploy a Sovereign AI for Your Institution?
Contact the Allmaz team to discuss your institution's requirements, review deployment options, and arrange a technical demonstration — entirely within your secure environment.
Request a demo