KDB-X: The Next-Gen of kdb+
End analytics complexity with a unified platform where time-series, vector, and AI converge—and data, models, and logic move as one.
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End analytics complexity with a unified platform where time-series, vector, and AI converge—and data, models, and logic move as one.
Learn how to build an advanced PDF parsing solution for RAG using LlamaParse and revolutionize how you learn and interact with information.
Revolutionize video search with multimodal AI for accurate, contextually relevant searches that transform video archives into active knowledge bases.
In this session we invite industry peers from both buy and sell side financial institutions to address real-world challenges in trading research and execution performance.
Augmenting LLMs with query-relevant information via RAG produces high-quality responses, significantly cheaper than ingesting your entire dataset.
Discover how hybrid search in KDB-X combines BM25 keyword precision with semantic embeddings to boost accuracy, delivering smarter and more relevant results.
This one-hour session with Conor Twomey and Mark Palmer explores the innovative ways Wall Street is leveraging high-frequency data in applications such as: Trade ideation, Trade execution, and Continuous risk management.
We’re excited to host this webinar alongside ICE, a global leader in cross asset market data, pricing and analytics. We’ll discuss different approaches to optimizing your algo trade models using real-time & historical data analytics .
Explore a methodical approach to addressing RAG retrieval inconsistency and generation inaccuracy for non-text elements like images and table heavy documents.
Gain a deeper understanding of market drivers and unlock new business insights by combining structured and unstructured data in KDB-X