KDB.AI
Enhance search accuracy and analytics with a vector database designed for AI.
KDB.AI
Features
Dynamic hybrid search
Combine similarity, exact, and literal search within a single query to maintain result relevance as content evolves.
Mixed search
Leverage hybrid, semantic, keyword, and temporal search to execute queries faster and achieve more accurate results.
Killer compression
Reduce memory and on-disk storage by 100x for slow-changing time-based data sets, accelerating search by 10x.
Multimodal RAG
Seamlessly connect with Large Language Models (LLMs) to enhance and personalize search outcomes.
Zero embedding
Perform search 17x faster with 12x less memory than HNSW, eliminating the complexity of embeddings in environments with fast changing temporal data.
CPU centric
Obtain all the advantages of KDB.AI using CPUs for a performant alternative to AI processing.
Use Cases
Behavioral analytics
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
Multi-modal retrieval augmented generation (RAG)
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
Advanced search
Build applications with both structured and unstructured data. Execute queries for structured and unstructured data against a single database for faster results.
Integrates with GenAI tools
