Building and deploying monolingual NLP systems for low-resource languages presents challenges, especially in handling diverse scripts and optimizing for production-scale environments. This session explores trans-tokenization, a novel method for transforming tokens across languages, enhancing large language models for monolingual capabilities. Using parallel corpora like English-Hindi, we’ll demonstrate how tools such as Unsloth and Mistral enable fine-tuning to handle non-Latin scripts effectively. A major focus will be on leveraging Kubernetes to scale monolingual NLP systems. Attendees will learn how Kubernetes facilitates resource allocation, supports distributed training, and simplifies model deployment at scale. Topics include managing workloads for parallel corpora, optimizing GPU utilization, and ensuring high availability of NLP services in production environments.