Eric Avidon

One after another throughout 2026, data management vendors have unveiled new tools targeting a single goal: connecting AI agents with context.

When connected with relevant context, agents can increase organizational efficiency and reduce spending. When left to guess, they can cause significant harm.

The vendor's Web Search Agents autonomously learn domain-specific use cases to help enterprises collect contextually relevant information for AI and analytics.

Web data search specialist Nimble launches self-learning agents that enable customers to collect contextually relevant information for AI and analytics.

Connecting AI agents with proper context is key for them to deliver on their potential while avoiding consequences such as financial and reputational harm.

MongoDB's latest new features unify frequently disparate capabilities to simplify and speed developing agents and other AI applications.

Flush with funding, the data management and AI vendor continues to make purchases that add capabilities aimed at aiding users building and deploying agents.

After raising yet another $5B in VC funding, an IPO is inevitable for Databricks, with the benefits of going public outweighing those of staying private.

With spending on AI spiraling out of control for many organizations, the vendor's latest new feature automates model selection to balance cost and performance.

With agentic AI costing more than many organizations expected, the data observability specialist's latest alerts users when the expense of an agent suddenly changes.