Building a Clinical Decision Engine Platform with Red Hat Decision Manager (Case Study)

Companies that develop or support products in the field need to transition from reactive to predictive maintenance and service. Such a transition is possible using ubiquitous connectivity and predictive analytics on machine data. Here’s how.

Although edge architectures differ fundamentally from conventional cloud and on-premises environments, edge isn’t an alternative to traditional infrastructure strategies as much as it is an augmentation of them.

The relationships banks have with their customers can last for decades, but too many banks fail to use the data they have to provide personalized digital banking services. 

Every transaction, order, customer interaction, and internal operation depends on decisions. At a time when businesses are under pressure to improve efficiencies, cut costs, and be more responsive, automating decisions becomes essential. While many businesses have picked off the low-hanging fruit when automating, most need to add more. Specifically, businesses want to automate complex decisions, involving multiple steps, multiple data sources and many rules.

Washington and Big Tech signed a pledge but missed an opportunity to lower the tab.

The latest MLPerf benchmark results paint a clear picture of an AI infrastructure ecosystem in rapid transition.

Stop building your RAG pipelines to process what your models already know. Let the models capture the knowledge itself.

As the pace and complexity of operations accelerate, organizations are rethinking architectures to enable real-time, human-in-the-loop decision-making.