Private LLM Consulting Services

A private large language model (LLM) operates within a secure environment where an organisation retains full control over access rights, data management, and deployment strategies. This setup enables the creation of internal AI tools that leverage corporate infrastructure or a dedicated hosted environment.

Where private LLMs deliver value

• Internal knowledge retrieval: Empowers staff to locate specific information within company documents, operational procedures, and technical manuals, ensuring that responses strictly adhere to existing document access permissions.
• Document processing: Facilitates the summarisation of reports, extraction of key data, and drafting of content from internal materials. Human oversight remains critical in scenarios where errors could impact significant business decisions.
• Software development: Assists with code explanation, documentation creation, and development tasks, ensuring that source code remains secured within an approved, isolated environment.

Deployment options and strategic considerations

• Location and control: On-premise deployment offers direct oversight of hardware and network access. Alternatively, dedicated hosting minimises the burden of physical infrastructure management but necessitates rigorous verification of provider access rights and data residency.
• Cost and capacity: Operating expenses encompass hardware, power, hosting fees, and maintenance. The required capacity is determined by model size, document length, and the volume of concurrent users.
• Performance and quality: Smaller models typically demand fewer resources. It is essential to benchmark these against representative tasks to verify that accuracy and response times meet business standards.
• Security and maintenance: Private deployment alone does not ensure security. Continuous attention is required for access controls, logging, software updates, and the protection of stored conversations.

How NobleConsul can assist

• NobleConsul can assist in evaluating use cases, comparing deployment strategies, and testing models against specific business requirements.
• NobleConsul can also procure and configure server hardware for private LLM deployments, tailoring GPU, memory, storage, and networking selections to fit workload demands and budget constraints.
• Support services may include integration with internal systems, as well as planning for ongoing operations, maintenance, and capacity expansions.

Private LLM Consulting Frequently Asked Questions

When should an organisation consider private LLM consulting?

When it intends to utilise AI for handling sensitive data, such as internal documents, source code, or customer information, without relying on public AI services. It is also beneficial when transitioning an AI pilot to production, allowing for the assessment of appropriate models, hardware, and infrastructure.

What hardware is required to run a private LLM?

Primarily, GPUs with sufficient memory to accommodate the model. A compact model (7–8 billion parameters) can operate on a single GPU with 16–24 GB of memory. A large model (70 billion parameters) requires 40 GB or more, typically distributed across multiple GPUs. Higher user concurrency and longer documents necessitate greater capacity.

What are the costs associated with running an on-premise LLM?

Expenses are dictated by model size, user count, and performance expectations. Smaller models can run on a single GPU server, whereas larger ones require more costly hardware. Recurring costs include electricity, cooling, software updates, and maintenance. Conducting a pilot with real-world workloads aids in estimating the total investment.

How does a private LLM differ from ChatGPT Enterprise?

A private LLM operates on your organisation’s own infrastructure, granting you control over how and where data is processed. ChatGPT Enterprise is hosted by OpenAI under its specific contractual terms. Private LLMs typically utilise open-source models such as Llama, Mistral, or Qwen, which are managed and maintained directly by your organisation.

Is it possible to view a prototype before making a commitment?

Yes. Following an initial consultation regarding your requirements and current systems, NobleConsul will develop a prototype based on a real task, such as searching internal documents. This is accompanied by a proposal outlining implementation costs, total cost of ownership, and training needs.

Who retains ownership of the model, hardware, and data subsequently?

Your organisation. NobleConsul transfers ownership of the hardware, code, credentials, and documentation, then revokes its own access. Any subsequent support is provided only with your explicit approval.