Eric Avidon

Without relevant, AI-ready data, agents are doomed to fail. In response, as agentic AI became the focal point of many enterprises' development

Starburst simplifies, speeds AI development with new platform that enables users to feed AI with contextually relevant data from distributed environments.

The combined capabilities of the newly formed company provide the infrastructure, including data integration and preparation, for agents and other cutting-edge applications.

A streaming data service and tools that provide agents with contextual awareness highlight the latest avalanche of Snowflake's data and AI capabilities.

With new features that fuel agents with contextually relevant data, Microsoft is making its Fabric platform a foundation layer for AI.

Long a respected graph database specialist, Neo4j is adding analysis capabilities for government agencies with its acquisition of GraphAware.

Unstructured data can be the difference between a trusted agent and a failed AI project, but many organizations struggle to operationalize unstructured data.

With the launch of OpenSharing, Databricks is adding an open standard for sharing AI assets across platforms aimed at modernizing collaboration.

New Databricks features, such as Genie Ontology to connect agents with needed context and cost control measures, aid AI development.

With context key to agentic AI tools performing well enough to reach production, AWS is the latest to unveil capabilities that connect agents with context.