If your AI feels slow, expensive or risky, the problem isn’t the models — it’s the data, and cognitive data architecture is ...

AI initiatives don’t stall because models aren’t good enough, but because data architecture lags the requirements of agentic systems.

Enterprise voice AI has fractured into three architectural paths. The choice you make now will determine whether your agents ...

Time flies in the world of data analytics and artificial intelligence (AI). Seemingly every day, new technologies rise, new use cases emerge, and new frontiers unfurl themselves before a world that ...

In the first quarter of 2025, nearly 60% of DBTA subscribers told us they were actively researching GenAI with LLMs, including RAG and knowledge graphs. On top of this, when asked which technologies ...

In an AI-first architecture, intelligence isn’t a feature. It’s part of the plumbing. Data moves in ways that support long-running decisions. Schemas evolve. Agents need context that lasts longer than ...

With AI ambitions outpacing data readiness, CIOs must renovate their data strategies to create unified, AI-ready foundations capable of supporting enterprise-wide use cases.

Large language models like ChatGPT and Llama-2 are notorious for their extensive memory and computational demands, making them costly to run. Trimming even a small fraction of their size can lead to ...

The headless data architecture is the formalization of a data access layer at the center of your organization. Encompassing both streams and tables, it provides consistent data access for both ...

Over the past decade, the data boom has created exciting strategic opportunities for adaptive companies and enabled the development of entirely new enterprises. This wave was the result of the ...