ToolsThe story, in brief

Context intelligence for your data and AI agents at scale

AWS just solved the $2T problem keeping AI agents from making real decisions: trusted context at scale.

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AI agents and the coordination of work.AI illustration by KeyNews
The KeyNews take

Why it matters

AWS is shipping infrastructure to give AI agents safe, trustworthy access to scattered enterprise data — removing a critical blocker for agents to move from pilots to production workflows.

The key facts

9 to know
  1. AWS Summit NYC announcement

  2. Focus on agent context access across data lakes, warehouses, lakehouses, databases, and streams

  3. Problem: agents lack institutional knowledge needed for trusted decision-making

  4. Solution framed as 'safe way' for agents to access context

  5. Positioning around agent trust and decision reliability at scale

  6. AWS announces agent context intelligence suite at AWS Summit NYC

  7. Focus on multi-source context integration (data lakes, warehouses, lakehouses, databases, streams, institutional knowledge)

  8. Positions context access as foundational to agent trustworthiness and decision quality

  9. Targets enterprise scale deployment of AI agents

Go to the source

AWS Machine Learning Blogaws.amazon.com

Publisher excerpt: Agents are only as intelligent as the context they can reason over. Today, that context is scattered across data lakes, data warehouses, lakehouses, databases, and streams, and in institutional knowledge that has never been written down. You want to trust the decisions made by your AI agents, but…
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