Actian’s Ole Olesen-Bagneux explains why AI agents need metadata, lineage, context, and governance before enterprises can ...

Good afternoon, and thank you for joining us on Snowflake's First Quarter Fiscal 2027 Earnings Call. Joining me on the call today a ...

Arvix AI rewrites code, tunes infrastructure, and eliminates storage waste autonomously, validating every change before it reaches productionSAN FRANCISCO--(BUSINESS WIRE)--Unravel Data, the data ...

Aaron Erickson discusses the evolution of AI workflows, shifting from "vibe checking" to building reliable, multi-agent ...

I’ve spent a lot of time inside enterprise AI deployments, and one thing that has become clear is that IT departments are leading the charge. Of course, enterprises are starting to consolidate ...

AI agents can’t just guess what your data means; they need an "ontology" to act as a shared rulebook so they don't make confident, expensive mistakes.

Enterprises modernize legacy mainframe systems with AI agents, leveraging existing infrastructure while overcoming integration challenges.

Over the past few years, database and analytics vendors have hopped on a bandwagon that may take us all to a destination where common data queries are free from the constraints of the specialist query ...

As AI adoption accelerates, financial institutions must strike a delicate balance between innovation and compliance, building systems are intelligent as well as secure. IT leaders must also meet heavy ...

Artificial intelligence and related technologies are evolving rapidly, but until recently, Java developers had few options for integrating AI capabilities directly into Spring-based applications.

The next wave of AI will be defined by agentic systems that can take actions: query databases, navigate portals, retrieve records, and increasingly interact with public digital infrastructure at scale ...