KX, a provider of vector and time-series data management, has announced general availability of KDB.AI Server, a highly-performant, scalable, vector database for time-orientated generative AI and contextual search. Deployable in a single container via Docker, KDB.AI Server offers a smooth setup for various environments, including cloud, on-premises, and hybrid systems, allowing businesses to quickly adopt and use its AI capabilities without complex setup processes.
Built to handle high-speed, time-oriented data and multi-modal data processing, KDB.AI Server handles both structured and unstructured enterprise data and enables developers to bring temporal and semantic context and relevancy to AI-powered applications. The server is also optimised for Retrieval Augmented Generation (RAG) patterns, which ensures that, rather than continuously training or fine-tuning Large Language Models (LLM), developers can bring data relevancy to their prompts delivering better accuracy, lower cost, and less need for GPUs.
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