KX Rolls Out KDB.AI Cloud, Allows Developers to Build Temporal and Semantic Context to AI-Powered Applications

KX, a provider of vector and time-series data management, is releasing KDB.AI Cloud, a vector database for real-time contextual AI designed with a commitment to provide a superior developer experience.

Unique among vector databases, KDB.AI Cloud enables developers to bring temporal and semantic context and relevancy to their AI-powered application, according to the company.

“KDB.AI Cloud exemplifies our commitment to elevate the developer experience, setting them at the forefront of generative AI's future, further enhanced by discriminative AI,” said Ashok Reddy, CEO of KX. “Our platform infuses time-awareness and situational understanding into vector database-driven AI processes, ensuring unmatched precision for generative AI applications. I eagerly anticipate the ground-breaking solutions that developers worldwide will forge with KDB.AI Cloud, reshaping industries and establishing fresh standards for innovation.”

Built to handle high-speed, time-series data and multi-mode query data processing, it allows business users, for example, to query real-time financial market data using natural language search with semantic relevance.

Temporal awareness means KDB.AI Cloud answers questions based on ad-hoc time windows such as data creation, modification recency, or periodic comparisons. This helps applications find and return more relevant data and allows for point-in-time and like-for-like comparisons.

KDB.AI Cloud works seamlessly with popular LLMs and machine learning workflows and tools, including LangChain and ChatGPT, while native support for Python and RESTful APIs means developers can perform common operations like data ingestion, search, and analytics using their preferred applications and languages, according to the company.

Key use cases include:

  • Multi-modal unstructured data search – similarity search between objects in any data format—video, image, text, time series, or unstructured.
  • Automation with digital twins - by providing situational awareness based on time, vectors can be applied to provide context into streams of IoT data from digital twins, to automate with confidence.
  • Pattern matching and anomaly detection – spot anomalies in data sets to build data integrity and boost performance.
  • Recommendation systems – refine algorithms based on feedback loops for adaptive user experiences.
  • Sentiment analysis – detect customer patterns and improve user experiences.

KDB.AI is used across multiple industries, including finance, energy, manufacturing, and telecommunications.

KDB.AI Cloud is available now as a free to use, SaaS-based service from KX, and is ideal for getting started with vector databases.

For more information about this news, visit