How Can You Trust Your AI Answers | Centerprise AI

Most AI can answer what the data says. But is that answer governed, accurate, and traceable enough to act on? Centerprise AI gives enterprises the data foundation they need to scale AI with confidence. One platform that brings together every data source, models it into a governed warehouse, and encodes your business logic as Skills.

How Endpoint Clinical Closed the Embedded Analytics Revenue Gap

I'll be honest: one number from the latest embedded analytics research stopped the entire planning conversation for this webinar. 57% of teams with embedded analytics report no measurable business impact, and that means not low impact or underwhelming impact, but no measurable impact at all.

The Reason Behind Stalled AI Projects

As enterprises race to adopt AI, weak data foundations are preventing more than half (58%) of organizations in the United States and Canada from realizing value and contributing to an estimated $108 billion in wasted global AI investment each year, according to a report from Hitachi Vantara. The reason is rarely bad models or lack of ambition.

How Cloudera Powers Agentic Workflows? #DataInMotion #Cloudera

Ready to eliminate data delays and fuel your AI models with trusted, real-time insights? In this video, we break down how Cloudera Data in Motion allows organizations to unlock the full potential of their data fabric. Whether your corporate datasets are scattered across diverse storage systems, multiple cloud vendors, or on-premises data centers, Cloudera provides the scalable, engine-agnostic data services required to stream and process information instantly—without needing to redesign or refactor your existing pipelines.

AI to Write Rules, or AI to Make Decisions?

Last April FloQast, an American maker of accounting software, published something unusual: a detailed engineering post on Amazon Web Services’ machine-learning blog, co-authored with AWS personnel, explaining precisely how its AI-powered transaction-matching feature works under the hood. The post described cloud infrastructure, model selection, and the specific technique (generating matching rules from user-supplied examples) that powers its AutoRec product.