Case Study: Large Foundational Model Developer achieves faster LLM development and fine-tuning with Welocalize

Accelerating LLM Development & Fine-Tuning

The Large Foundational Model Developer partnered with Welocalize to improve the accuracy, fluency, and safety of its large language model output amid surging demand for generative AI in 2023. The customer needed fast support for cultural adaptation, supervised fine-tuning (SFT), and reinforcement learning from human feedback (RLHF), while also managing inconsistent workloads and sensitive content.

Welocalize quickly trained and deployed remote workers across 35+ locations to handle input evaluation, fact verification, fluency review, open writing, and model output evaluation. The engagement mobilized more than 9,500 remote workers and supported 4 LLM evaluation workflows across 35 locales, helping the customer achieve reliable 12–24 hour turnaround times and more efficient LLM refinement.