Cohere has recently introduced fine-tuning capabilities to its Rerank model, enhancing its performance in complex domains such as legal, medical, and technical fields, where domain-specific jargon and intricate concepts are prevalent. The Rerank model, a semantic relevance scoring system, benefits from fine-tuning tailored to specific domains, improving search result relevance significantly. This enhancement addresses challenges posed by complex terminologies and domain-specific knowledge, outperforming large generative models like GPT-4 in terms of cost, speed, and predictability. The fine-tuned Rerank model demonstrated notable performance improvements, particularly in the legal domain using the CaseHOLD benchmark, where its accuracy doubled compared to the base model. Developers can access this fine-tuning feature through Cohere's SDK or a new interface, offering a cost-effective solution without the need for extensive computational resources.