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KX has announced the general availability of KDB.AI Server, a highly-performant, scalable, vector database for time-orientated generative AI and contextual search.
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Combine similarity, exact, and literal search within a single query to maintain result relevance as content evolves.
Leverage hybrid, semantic, keyword, and temporal search to execute queries faster and achieve more accurate results.
Reduce memory and on-disk storage by 100x for slow-changing time-based data sets, accelerating search by 10x.
Seamlessly connect with Large Language Models (LLMs) to enhance and personalize search outcomes.
Perform search 17x faster with 12x less memory than HNSW, eliminating the complexity of embeddings in environments with fast changing temporal data.
Obtain all the advantages of KDB.AI using CPUs for a performant alternative to AI processing.
Detect anomalies or outliers and forecast future events with unprecedented efficiency. Analyze trends and data behavior over time for faster decision-making. View signatures of time through similarity searches
Integrate easily with LLMs for better, more personalized search results. Utilize unstructured data (text, image, video, and audio data) harmoniously. No limit on metadata or time windows
Build applications with both structured and unstructured data. Execute queries for structured and unstructured data against a single database for faster results.
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