Bring your own LLM: five best practices for enterprise success

Enterprises are taking greater control over the AI models they use. They’re weighing the cost of proprietary models against open alternatives and evaluating which models perform best for particular tasks. AT&T, for example, has reportedly expanded its use of open AI models to reduce costs and gain greater flexibility.

But what happens when an enterprise that has already invested in its preferred large language models wants to work with an AI vendor that offers specialized capabilities? Must the enterprise abandon its existing investments to accommodate the vendor’s preferred model?

Increasingly, enterprises have another option: Bring Your Own LLM (BYO-LLM). Under this approach, enterprises select and control their preferred language models while relying on specialized vendors to provide the technology and expertise needed to put those models to work.

BYO-LLM is particularly relevant to the multilingual content and localization work that I do. Enterprises may already have approved models for generating and adapting content across languages and markets. They want to retain those investments while benefiting from a localization partner’s linguistic expertise, workflow orchestration, and quality assurance.

In my experience, getting BYO-LLM right requires careful decisions about model selection, governance, and the responsibilities of the enterprise and its localization partner. Here are five best practices for making the approach successful.

1. Maintain Control Over Your AI Strategy and Technology

Your choice of LLM should reflect your enterprise’s business priorities, not the preferences of an individual vendor. Models vary in their capabilities and costs. Some may excel at languages or specialized terminology, while others offer advantages in speed or compatibility with existing enterprise infrastructure.

Enterprises adopting BYO-LLM need clear criteria for selecting and approving models, ranging from performance to compatibility with existing technology. Vendors must be able to work within those requirements. An enterprise should know which models a prospective partner supports and how the partner integrates them. It should also understand how easily it can upgrade or replace a model as its needs change. These decisions should remain under enterprise control without limiting the vendor’s ability to deliver its specialized capabilities.

2. Improve Domain-Specific Performance

A powerful general-purpose LLM isn’t necessarily proficient in your industry’s terminology, your company’s brand voice, or the cultural nuances of every market you serve. For instance, a pharmaceutical company translating medical information into multiple languages requires accuracy more than grammatical fluency. The content must use approved medical terminology, preserve precise meanings, and satisfy applicable regulatory requirements.

BYO-LLM gives enterprises greater control over the models used for these tasks. Localization partners can improve performance by connecting those models to approved terminology, translation memories, style guides, and other enterprise knowledge assets. Evaluation criteria should reflect the enterprise’s industry, content types, languages, and business risks.

Linguistic expertise also plays an important role in continuous improvement. When experts correct an output, their decisions should inform future work. For example, a recurring translation error might prompt an update to the company’s terminology guidelines. Controlling the model alone doesn’t guarantee quality. Enterprises also need effective workflows and human expertise to ensure the content meets their requirements.

3. Strengthen Data Security and Governance

BYO-LLM can help enterprises maintain greater control over how their data is processed, but it doesn’t eliminate security risks. Sensitive information may still pass through vendor applications, integrations, and supporting infrastructure. Enterprises need visibility into the entire process, which includes how their data moves between the model and the vendor’s technology.

Enterprise security requirements should specify which data the model can access, where that data can be processed, and how long it can be retained. Factors like encryption, access permissions, logging, and regulatory compliance must extend to the vendor’s technology and operations. A localization partner must demonstrate that its applications and processes comply with those requirements.

A global financial services company, for example, may need to document how its AI processes sensitive information. Which model handled a particular document? What information did it receive? Did a human reviewer approve the final content? The company needs an auditable record of these activities, including the quality checks performed along the way. Its localization partner must follow the same governance requirements across every market where the company operates.

4. Rely on Your Localization Partner for Orchestration and Linguistic Expertise

An LLM can generate a translation. But delivering accurate, culturally appropriate content across dozens of markets requires specialized expertise and coordination. A global retailer preparing a product launch across 30 countries may supply its preferred LLM, but its localization partner still needs to manage the translation process. That includes ensuring consistent terminology, evaluating quality, and coordinating human review before content reaches each market. A qualified localization partner brings the necessary expertise and technology to manage the work.

The localization partner must also determine how much human oversight different types of content require. Routine translations may need only automated quality checks. Legal documents, on the other hand, often require expert review. Regardless of the approach, the finished content must preserve the intended meaning and resonate with local audiences.

As a company enters new markets, its localization needs grow more complex. Its partner should be able to handle the additional work without requiring major changes to existing processes. With BYO-LLM, the company retains control over its AI models while its localization partner manages the work of delivering content to each market.

5. Design for Portability

Today’s preferred LLM may not be tomorrow’s best choice. As new models become available, enterprises may find that another option delivers better performance at a lower cost. The challenge is adopting that model without disrupting existing multilingual content operations.

A vendor’s ability to support different models is therefore essential to BYO-LLM. How easily can the enterprise replace its current model? Would doing so require substantial redevelopment, or could the new model work within the existing technology environment? These questions need to be resolved before committing to a localization partner.

Portability extends beyond the LLM itself. Over time, enterprises accumulate valuable knowledge through translation memories, terminology databases, and decisions made by linguistic experts. That knowledge belongs to the enterprise and should remain accessible even if the company changes models or vendors.

Of course, switching models is rarely as simple as plugging in a replacement. A new LLM may interpret instructions differently or produce inconsistent results in languages where the previous model performed well. Enterprises should test the replacement against their established quality standards before putting it into production.

Make BYO-LLM a Business Advantage

BYO-LLM gives enterprises an opportunity to take greater ownership of their AI investments while continuing to benefit from specialized vendor expertise. For multilingual content, enterprises need to produce more content across more markets while maintaining quality, consistency, and control.

A qualified localization partner helps enterprises turn their preferred models into reliable multilingual content operations. Your enterprise should control its AI strategy, and your partners should help you make that strategy successful.