Ever wonder how businesses gauge customer feedback from online reviews? It's a goldmine of insights, but deciphering the nuances of language can be tricky. This is especially true for less-resourced languages like Lithuanian, where the subtleties of sentiment expression add another layer of complexity. Researchers tackled this challenge head-on by exploring the power of Large Language Models (LLMs) for sentiment analysis of Lithuanian online reviews. The team focused on fine-tuning pre-trained transformer models like BERT and T5, tailoring them to understand the specifics of Lithuanian. The results? These fine-tuned LLMs performed remarkably well, especially when sentiments were clear-cut, like overwhelmingly positive or negative reviews. Interestingly, they even outperformed industry giants like GPT-4, showing the value of specialization. The research revealed that even with the inherent subjectivity of human language, AI can effectively analyze complex sentiment patterns. While challenges remain, this work opens doors for businesses to better understand Lithuanian customers and tailor their services based on real-time feedback. This has broader implications for market research and understanding consumer behavior in niche markets, highlighting AI’s potential to enhance customer experience and bridge language barriers in an increasingly interconnected world.