Prem Studio's Datasets capability offers a comprehensive solution for organizations aiming to enhance AI model performance by addressing challenges in creating domain-specific training data. It provides tools for synthetic data generation and data augmentation, enabling the transformation of raw content, such as text files and videos, into structured, training-ready datasets at scale. The platform supports manual file uploads and automated pipelines, facilitating the preparation of data for large language model (LLM) evaluation or small language model (SLM) fine-tuning. Synthetic data generation is particularly useful for domain-specific content, converting static documents into structured question-answer datasets, thus embedding domain knowledge into models and reducing retrieval overhead during inference. Data augmentation expands existing datasets by generating additional data while maintaining the original style and structure, thereby increasing dataset volume without manual input. Additionally, Prem Studio offers dataset versioning to ensure reproducibility and safe experimentation, mirroring familiar version control systems. Overall, Prem Studio streamlines the creation and management of high-quality datasets, making AI development more accessible for enterprise teams without specialized technical expertise.