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.
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 knowAWS Summit NYC announcement
Focus on agent context access across data lakes, warehouses, lakehouses, databases, and streams
Problem: agents lack institutional knowledge needed for trusted decision-making
Solution framed as 'safe way' for agents to access context
Positioning around agent trust and decision reliability at scale
AWS announces agent context intelligence suite at AWS Summit NYC
Focus on multi-source context integration (data lakes, warehouses, lakehouses, databases, streams, institutional knowledge)
Positions context access as foundational to agent trustworthiness and decision quality
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…