On-premises AI

On-premises AI offers a viable solution for companies in regulated industries that require strict data governance and compliance, such as finance, healthcare, and the public sector, by allowing AI workloads to run within the company's infrastructure rather than relying on cloud-based solutions. This approach provides increased data security, control over infrastructure, and the ability to quickly implement AI projects without the need for extensive data migration. On-premises AI leverages technologies like Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to enhance data accuracy and relevance while maintaining data sovereignty and regulatory compliance. Starburst's hybrid architecture, including the use of Apache Iceberg and Trino, supports these AI initiatives by enabling fast access to data across multiple sources, thereby enhancing governance and performance. This strategy is particularly beneficial for organizations that need to maintain data within specific geographic locations due to data sovereignty laws, enabling them to adopt AI more efficiently and securely.