True personalization starts with context, not attributes. See how scenario-based design bridges behavioral segments and ...

• Invest in data readiness. Informatica’s CDO survey notes that data quality and readiness (43%), technical maturity (43%) and skill shortages (35%) are the top obstacles to AI success. Winning ...

In the post‑pandemic news cycle, it became easy to treat charts as a kind of journalistic spell: visualize the data and legitimacy will follow. But the flood of partisan “stat dumps” has trained ...

Credit: Image generated by VentureBeat with FLUX-pro-1.1-ultra Enterprise AI agents today face a fundamental timing problem: They can't easily act on critical business events because they aren't ...

What is conspicuously absent from debates about AI? Any serious discussion about the operational data that AI agents need to perceive and navigate their environment.

As the CEO of Arango, Shekhar Iyer leads the company’s mission to make enterprise AI contextual, scalable and trusted. As AI moves from hype to measurable results, one truth is becoming clear: ...

Confluent is positioning itself as the "context layer for enterprise AI" with new capabilities that aim to solve the problem plaguing generative AI investments—lack of fresh, trustworthy data—by ...

Onboarding new AI hires calls for context engineering - here's your 3-step action plan ...

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results. In ...

Governments can’t scale artificial intelligence safely without trusted data foundations, minimum viable governance and clear ...