AI - Further Information

Fluree is a data fabric vendor that also includes an intriguing approach to improving AI LLM answers that use the RAG approach.

SingleStoreDB is a translytical, multi-model database. Its support for vector data is particularly notable.

We examine the interplay between graph and AI technology, and highlight a particularly effective example of addressing this interplay: Ultipa.

Experian continue to incorporate data governance technology Intozetta into their portfolio, including AI capabilities.

AI is all the rage but what are the issues with retrieval augmented generation (RAG) and SQL generated by AI?

SnapLogic has data integration capabilities that support data fabric and data mesh.

Informatica continues to build on its data quality offering with additional AI features.

This white paper will outline the technical, organisational and cultural challenges that need to be addressed to be able to provide realistic, evidence-based, Digital Experience Assurance.

How the InterSystems IRIS platform plays within a data fabric architecture.

This survey of 180 enterprises assess the current state of generative AI implementations, including which areas are of most interest and the challenges involved.

Collibra continues to evolve its data governance platform with artificial intelligence extensions and other enhancements in the next release.

An Enterprise Information Architecture can be viewed as the operating system of the Enterprise by means of which all applications are deployed and executed.

Alation is a modern data catalog product with artificial intelligence underpinnings.

Generative AI has many use cases across industries as well as some limitations.

Generative AI is the latest computing technology to take the world by storm. In this report, we discuss various data architectures for generative AI.

Generative AI (GAI) has emerged as another transformative technology. It offers dramatic benefits, but may also foster chaos.

Modernisation is better than rip and replace, taking advantage of Low Code, AI (Augmented Intelligence), DevOps etc.

How does ML/AI work, who are the vendors and why you should care?