Prometheus for Banking
The first large language model built natively for Azerbaijani, deployed entirely on your own infrastructure. Available in 587B, 99B and 39B sizes.
Prometheus for Banking: Enterprise AI That Never Leaves Your Network
Azerbaijani banks operate under strict Central Bank supervision and banking-secrecy obligations that make transmitting customer data to foreign cloud services a compliance risk, not merely a preference. Prometheus is the first large language model built natively for the Azerbaijani language and deployed entirely on your own infrastructure, meaning every customer query, transaction record, and audit log remains within your network perimeter at all times. Its native tokenizer correctly handles the ə character and the agglutinative morphology that defines Azerbaijani grammar, capabilities absent from general-purpose models trained predominantly on other languages. Trained on more than 651 million curated Azerbaijani words and validated on the TUMLU benchmark across 38,139 native questions spanning 11 disciplines, Prometheus delivers language understanding that is both linguistically precise and independently verifiable.
Why Azerbaijani Banks Choose Prometheus
Full data residency by architecture: model weights run on your own servers and no customer data, query, or output is ever transmitted to an external network, satisfying banking-secrecy rules and Central Bank of Azerbaijan requirements at the infrastructure level rather than by policy alone.
Linguistically accurate Azerbaijani processing: the native tokenizer correctly handles the ə character and agglutinative word forms, ensuring that customer communications, contract language, and regulatory documents are parsed with the precision that financial workflows demand.
4.6 times greater efficiency on Azerbaijani text compared with general-purpose models, directly reducing the compute cost of running AI across high-volume use cases such as call-center assistance, complaint triage, and document review.
Right-sized deployment flexibility: the 39B model serves real-time customer interactions, the 99B model supports balanced back-office workflows, and the 587B model handles complex compliance analysis and large-document tasks, allowing your institution to align infrastructure investment with actual workload requirements.
Benchmark-validated quality: performance is independently measured on the TUMLU benchmark, comprising 38,139 native Azerbaijani questions across 11 disciplines, providing a transparent and auditable quality reference that compliance officers and regulators can examine directly.
Deep domain vocabulary from day one: training on more than 651 million curated Azerbaijani words gives the model the financial, legal, and customer-service terminology your staff and customers actually use, reducing the gap between out-of-the-box performance and production-ready accuracy.
Capabilities Built for Banking Operations
On-Premise Deployment
Prometheus runs entirely within your own data center. No API calls to external servers, no shared cloud tenancy. Your customer records, transaction histories, and internal documents remain under your control at all times, satisfying banking-secrecy obligations by design.
Azerbaijani-Native Call Center Assistance
High call volumes in support and collections put pressure on staff. Prometheus understands natural Azerbaijani speech transcripts and text, enabling intelligent routing, suggested responses, and post-call summarization — all processed on your infrastructure without exposing sensitive account data.
Fraud and Complaint Signal Detection
The model can analyze customer communications and transaction narratives in Azerbaijani to surface patterns associated with complaints or potential fraud, helping compliance and risk teams prioritize cases before they escalate.
Regulatory Audit Evidence Generation
Prometheus can draft structured summaries, decision rationales, and audit trails from internal data, giving compliance officers ready-made documentation for Central Bank examinations — produced entirely within your secure environment.
Flexible Model Sizing
Choose the 39B model for latency-sensitive customer-facing tasks, the 99B model for balanced back-office workflows, or the 587B model for complex regulatory analysis and large-document review. All three share the same native Azerbaijani tokenizer and training foundation.
Benchmark-Validated Quality
Performance is independently measured on the TUMLU benchmark — 38,139 questions spanning 11 disciplines — so you have a transparent, auditable quality reference to share with internal governance committees and external regulators.
How Prometheus Integrates with Your Bank
Frequently Asked Questions
How does Prometheus satisfy banking-secrecy and Central Bank of Azerbaijan data-residency requirements?
Prometheus is deployed fully on your own infrastructure. The model weights run on your servers, and no customer data, query, or output is transmitted to Allmaz or any external service. This architecture enforces data residency at the infrastructure level rather than relying on contractual policy alone, which means compliance is structural and demonstrable to auditors rather than dependent on third-party assurances.
Why does native Azerbaijani language support matter specifically for banking use cases?
General-purpose models are typically optimized for languages with large training corpora and routinely struggle with Azerbaijani morphology, including agglutinative word forms and the ə character. Errors at the tokenization level cascade into misread customer names, misclassified complaint categories, and inaccurate document summaries — all of which carry operational and regulatory consequences. Prometheus was built natively for Azerbaijani from the ground up, making it 4.6 times more efficient on Azerbaijani text and significantly more accurate on the financial and legal vocabulary your staff and customers actually use.
Which model size should our bank start with?
The 39B model is well suited to high-throughput, latency-sensitive tasks such as call-center assistance and real-time complaint routing, where response speed directly affects customer experience. The 99B model balances performance and resource consumption for back-office workflows such as document classification and internal reporting. The 587B model is appropriate for complex regulatory analysis, large-document review, and audit evidence generation where output quality is the primary concern. Allmaz can help you assess the right fit based on your specific workload profile during the deployment planning process.
What evidence can we present to regulators and internal governance committees about model quality?
Prometheus has been validated on the TUMLU benchmark, which comprises 38,139 native Azerbaijani questions across 11 disciplines. These results are transparent and reproducible, giving your compliance and governance teams an auditable quality reference that does not rely on vendor self-reporting. You can additionally run internal evaluations on your own domain-specific test sets entirely within your secure environment, producing institution-specific quality evidence that complements the external benchmark data.
Can Prometheus be fine-tuned on our bank's proprietary data, and does that process expose our data externally?
Yes, and no data leaves your network during fine-tuning. Because the model runs entirely on your infrastructure, you can fine-tune it on your internal documents, transaction narratives, customer communications, and regulatory filings without that data ever transiting to an external system. This allows Prometheus to learn your institution's specific terminology, product names, and internal processes while your data remains under full institutional control throughout the entire training and inference lifecycle.
Ready to Bring AI Inside Your Perimeter?
Talk to the Allmaz team about deploying Prometheus in your bank. We will help you select the right model size, plan the integration with your existing systems, and establish the governance documentation your compliance team needs — all without your data leaving your network.
Request a demo