How we automated technical documentation translation using tools around the model

The development team shares their experience in automating technical documentation translation using LLMs. Instead of relying on direct calls to the language model, the authors built a specialized software layer that handles data preparation, context management, and post-processing. This approach significantly improved translation quality while maintaining technical terminology accuracy and documentation structure. The article details the solution's architecture, integration tool selection, and quality control methods used to minimize errors typical of generative models. The company's experience demonstrates how building a wrapper around an LLM allows for effectively solving applied business tasks, turning universal neural networks into reliable tools for handling highly specialized content. This solution marks a significant step in optimizing internal company processes and accelerating the release of localized documentation versions for users.