Kx launches early access programme for kdb.ai vector database

Kx has introduced an early access programme for kdb.ai, a vector native database designed for real time and high volume time series analytics. The initiative allows developers to experiment with advanced vector search capabilities integrated into high performance data environments.

For enterprise teams, this provides a pathway to combine temporal data with vector embeddings for more accurate production AI. It is particularly relevant for sectors like finance where time series context is essential for retrieval augmented generation.

  • Kx opens early access for its vector native database kdb.ai
  • The platform handles high volume time series and real time data analytics
  • Developers can now integrate vector search with existing temporal data workflows
  • Aims to support high performance enterprise generative AI applications
Machine Learning Generative AI AI Apps & Platforms
All AI news

More AI news

Models

Major artificial intelligence providers release wave of latest models

Between 29 and 30 September 2026, major artificial intelligence companies OpenAI, Google, and Anthropic successively unveiled their latest model releases. The back-to-back announcements mark a concentrated burst of updates from the sector's leading frontier laboratories.

Research

OpenAI executive apologises after automated agent accesses Australian government website

An OpenAI executive has apologised to Australians after one of the firm's automated agents was permitted to run on an official government website. Addressing scrutiny during formal questioning, the representative acknowledged the failure and admitted the automated incident should not have happened. The episode highlights lapses in operational controls when testing autonomous systems against public web infrastructure.

Tooling

Open-source AI adoption grows amid enterprise security and licensing hurdles

Open-source artificial intelligence models are seeing rapid enterprise uptake, offering organisations stronger data privacy, predictable cost control, and deep customisation capabilities. Despite these advantages, engineering teams encounter considerable operational friction when taking open models to production. Businesses must actively manage complex licensing terms, software vulnerabilities, and substantial deployment hurdles across their workflows.

Ready to build something
extraordinary?

15 minutes. No pitch deck. Just a conversation about what AI can do for your team.

Talk directly with our AI specialists

15 min, no strings
No sales pressure
Prototype in 7 days