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Prometheus for Oil, Gas & Energy

The first large language model built natively for Azerbaijani, deployed entirely on your own infrastructure. Available in 587B, 99B and 39B sizes.

Prometheus for Oil and Gas Operations

Energy operators running safety-critical field sites carry an enormous documentation burden: layered safety SOPs, sprawling equipment and materials catalogues, multi-vendor supplier records, and shift handovers that must be precise and fast. Prometheus is the first large language model built natively for the Azerbaijani language, trained on more than 651 million curated Azerbaijani words and deployed entirely on your own infrastructure so that sensitive operational data never leaves your network. Its native tokenizer correctly handles the ə character and the agglutinative morphology of Azerbaijani, making it 4.6× more efficient on Azerbaijani text than adapted general-purpose models — and ensuring that field staff and engineers can interact in their working language without accuracy loss or translation overhead.

Capabilities

Why Energy Operators Choose Prometheus

Safety procedures and runbooks become instantly searchable and queryable in natural Azerbaijani, reducing the risk of misinterpretation during critical operations and cutting the time operators spend navigating multi-hundred-page documents under time pressure.

Complex technical nomenclature found in equipment catalogues, spare-parts lists, and materials specifications is handled accurately by a native tokenizer built for Azerbaijani morphology, eliminating the errors that arise when general-purpose models misparse agglutinative compound terms.

Multi-vendor supplier records can be queried, cross-referenced, and summarised in plain Azerbaijani without manual data wrangling or translation overhead, giving procurement and logistics teams faster, more reliable access to the information they need.

Shift-based field teams receive consistent, document-grounded answers from a single authoritative source, improving handover quality, reducing knowledge gaps between shifts, and supporting operational continuity across distributed sites.

Full on-premise deployment means proprietary well data, reservoir models, operational logs, and supplier contracts remain inside your network at all times, satisfying the data-sovereignty requirements that are standard across the energy sector.

Three model sizes — 39B, 99B, and 587B — let you match compute resources precisely to task criticality, from edge deployments on field-site servers with limited capacity to enterprise-scale reasoning across large, cross-domain document sets.

Capabilities Built for the Energy Sector

Native Azerbaijani Language Engine

Prometheus is the first LLM built natively for Azerbaijani, trained on over 651 million curated words. Its native tokenizer correctly handles the ə character and the agglutinative morphology of the language, making it 4.6× more efficient on Azerbaijani text than adapted general-purpose models. Field staff and engineers can interact in their working language without accuracy loss.

SOP and Runbook Intelligence

Upload your safety procedures, permit-to-work documents, and emergency response runbooks. Prometheus indexes and understands them so operators can ask plain-language questions and receive precise, procedure-grounded answers — reducing the time spent searching through multi-hundred-page documents during time-sensitive situations.

Equipment and Materials Catalogue Search

Energy sites maintain thousands of equipment records, spare-parts lists, and materials specifications. Prometheus navigates this master data in natural language, helping procurement teams, maintenance engineers, and field technicians locate the right item, specification, or supplier record quickly and accurately.

Fully On-Premise Deployment

Prometheus runs entirely within your own infrastructure. No data is transmitted to external servers or third-party cloud environments. This architecture satisfies the data-sovereignty requirements common in the energy sector and keeps commercially sensitive operational information under your direct control.

Scalable Model Sizes

Choose from 587B, 99B, or 39B parameter configurations. Deploy the 39B model on field-site servers with limited compute, the 99B model for departmental knowledge assistants, and the 587B model for complex cross-domain reasoning tasks such as multi-document regulatory analysis or supplier contract review.

Validated Benchmark Performance

Prometheus has been evaluated on the TUMLU benchmark — 38,139 native Azerbaijani questions spanning 11 disciplines — providing a transparent, independently structured measure of its language understanding capabilities across technical and general domains relevant to energy operations.

How Prometheus Integrates into Your Operations

1Select the model size that matches your infrastructure capacity and operational requirements — 39B for edge or site-level deployments, 99B for departmental use, or 587B for enterprise-wide knowledge tasks.
2Deploy Prometheus entirely on your own servers or private cloud environment; the installation process keeps all data, queries, and outputs within your network boundary.
3Connect your existing document repositories — safety SOPs, equipment catalogues, supplier records, shift logs — so Prometheus can index and understand your operational knowledge base.
4Field operators, engineers, and procurement teams interact with Prometheus in natural Azerbaijani, asking questions and receiving grounded, document-referenced answers in real time.
5Integrate Prometheus responses into existing workflows such as shift handover reports, maintenance work orders, or procurement requests through standard API connections.
6Monitor usage and refine the knowledge base over time as procedures are updated, new equipment is commissioned, or supplier records change — keeping the model's answers current and accurate.

Frequently Asked Questions

Does Prometheus require an internet connection to operate?

No. Prometheus is deployed fully on-premise and operates entirely within your own infrastructure. It does not require an internet connection at any point during inference or normal operation, and no queries, outputs, or internal documents are transmitted outside your network boundary. This makes it suitable for field sites and secure facilities where external connectivity is restricted or prohibited.

How does Prometheus handle the technical terminology found in oil and gas documentation?

Prometheus uses a native Azerbaijani tokenizer that correctly processes the language's agglutinative morphology, including the specialised compound terms and technical nomenclature common in engineering and energy contexts. When connected to your own document repositories, it grounds its answers in your specific procedures and terminology rather than relying on generic training data alone, which significantly reduces the risk of misinterpretation in safety-critical situations.

Which model size is appropriate for a field site with limited server capacity?

The 39B parameter model is designed for deployments where compute resources are constrained, such as field-site or edge servers. It retains strong native Azerbaijani language capability while requiring substantially less hardware than the 99B or 587B configurations. For departmental knowledge assistants or broader site-level use, the 99B model offers a balance between capability and resource requirements. Your infrastructure team can assess specific hardware requirements in detail during the deployment planning phase with the Allmaz team.

Can Prometheus work with documents in the formats our teams already use?

Prometheus is designed to connect to existing document repositories and data sources used in energy operations. Integration with common document formats is part of the standard deployment scope. During onboarding, the Allmaz team works directly with your IT and operations staff to ensure your existing knowledge base — including safety SOPs, equipment catalogues, and supplier records — is properly indexed and accessible to the model.

How was Prometheus validated to ensure reliable performance on technical content?

Prometheus was evaluated on the TUMLU benchmark, which comprises 38,139 native Azerbaijani questions across 11 disciplines, providing a structured and transparent measure of language understanding across both technical and general domains. In addition to this benchmark evaluation, Allmaz supports a pilot evaluation phase using your own operational documents and real use cases, so you can assess performance directly against the content and workflows that matter to your organisation before full deployment.

Ready to Bring Native Azerbaijani AI to Your Energy Operations?

Talk to the Allmaz team about deploying Prometheus on your infrastructure. We will help you identify the right model size, plan the integration with your existing documentation and data systems, and run a pilot evaluation against your real operational use cases.

Request a demo