How agencies can use on-premises AI models to detect fraud faster, prove control effectiveness and turn overwhelming data ...

Many engineering teams still rely on architecture optimized for transactional apps, not for AI systems that mix structured and unstructured data and live event streams. This legacy architecture has ...

It seems like everyone wants to get an AI tool developed and deployed for their organization quickly—like yesterday. Several customers I’m working with are rapidly designing, building and testing ...

The end goal of database design is to be able to transform a logical data model into an actual physical database. A logical data model is required before you can even begin to design a physical ...

To make productive use of the ever-growing volumes of data, businesses and organizations need the right database systems to manage all that data and make it available for transactional and analytical ...

With the growing interest in adopting best practices across IT departments, particularly according to standards such as the Information Technology Infrastructure Library (ITIL), many organizations are ...

A practical overview of security architectures, threat models, and controls for protecting proprietary enterprise data in retrieval-augmented generation (RAG) systems.